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<header>
<h1 class="title">Networking TS changes to enable better DynamicBuffer composition</h1>
</header>
<pre>
Document number: P1790R1
Date:            2020-01-13
Project:         Programming Language C++
Audience:        SG4 - Networking, LEWG
Reply-to:        Christopher Kohlhoff &lt;chris&#x40;kohlhoff.com&gt;
</pre>
<h1 id="networking-ts-changes-to-enable-better-dynamicbuffer-composition">Networking TS changes to enable better DynamicBuffer composition</h1>
<h2 id="introduction">Introduction</h2>
<p>P1100r0 <em>Efficient composition with DynamicBuffer</em> showed how the current specification of the DynamicBuffer type requirements inhibits layered composition of synchronous and asynchronous I/O operations. This new paper captures the LEWGI discussion of P1100r0 at the Kona 2019 meeting, wherein the root cause of the design issue was explored, and an alternative approach was discussed and accepted.</p>
<h2 id="background">Background</h2>
<p>The DynamicBuffer type requirements, and its supporting algorithms and implementations, have the following goals:</p>
<ul>
<li>To automatically grow to accommodate data</li>
<li>To efficiently support delimited protocols</li>
<li>To be adaptable to support circular buffers</li>
</ul>
<p>A trivial use of a DynamicBuffer is illustrated in this example:</p>
<pre><code>vector&lt;unsigned char&gt; data;
// ...
size_t n = net::read(my_socket,
    net::dynamic_buffer(data, MY_MAX),
    net::transfer_at_least(1));</code></pre>
<p>The <code>net::dynamic_buffer</code> function creates a DynamicBuffer as a view on to the underlying memory associated with the vector <code>data</code>. The vector <code>data</code> is then automatically resized to accommodate newly received bytes, and following the <code>read</code> operation will contain these bytes.</p>
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" style="width:14cm" /></p>
<p>For delimited protocols, a typical use may look similar to the following example:</p>
<pre><code>string data;
// ...
size_t n = net::read_until(my_socket
    net::dynamic_buffer(data, MY_MAX),
    &#39;\n&#39;);</code></pre>
<p>After <code>read_until</code> completes, the vector contains all newly received bytes, while <code>n</code> denotes the position of the first delimiter:</p>
<p><img src="data:image/png;base64,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" style="width:14cm" /></p>
<p>Before issuing another <code>read_until</code> to obtain the next delimited record, the application should remove the first record from the buffer:</p>
<pre><code>data.erase(0, n);
// issue next read_until ...</code></pre>
<p>Similarly, use of a DynamicBuffer with a <code>write</code> operation will automatically shrink the underlying memory as the data from it is consumed:</p>
<pre><code>size_t n = net::write(my_socket,
    net::dynamic_buffer(data));
// data is now empty</code></pre>
<p>Both the statically sized buffer sequences, which are created by <code>net::buffer()</code>, and the dynamic buffers created by <code>net::dynamic_buffer</code>, should be considered as views on to some underlying memory. The difference between the two is that a dynamic buffer will resize the underlying memory as required.</p>
<p>To support this a DynamicBuffer is defined as follows:</p>
<blockquote>
<p>A <em>dynamic buffer</em> encapsulates memory storage that may be automatically resized as required, where the memory is divided into two regions: readable bytes followed by writable bytes. These memory regions are internal to the dynamic buffer, but direct access to the elements is provided to permit them to be efficiently used with I/O operations. [<em>Note:</em> Such as the <code>send</code> or <code>receive</code> operations of a socket. The readable bytes would be used as the constant buffer sequence for <code>send</code>, and the writable bytes used as the mutable buffer sequence for <code>receive</code>. <em>–end note</em>] Data written to the writable bytes of a dynamic buffer object is appended to the readable bytes of the same object.</p>
</blockquote>
<p>A DynamicBuffer type is required to satisfy the requirements of <code>Destructible</code> and <code>MoveConstructible</code>, as well as the requirements shown in the table below.</p>
<blockquote>
<table>
<colgroup>
<col style="width: 28%" />
<col style="width: 37%" />
<col style="width: 34%" />
</colgroup>
<thead>
<tr class="header">
<th>expression</th>
<th>type</th>
<th style="text-align: left;">assertion/note pre/post-conditions</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td><code>X::const_buffers_type</code></td>
<td>type meeting ConstBufferSequence requirements.</td>
<td style="text-align: left;">This type represents the memory associated with the readable bytes.</td>
</tr>
<tr class="even">
<td><code>X::mutable_buffers_type</code></td>
<td>type meeting MutableBufferSequence requirements.</td>
<td style="text-align: left;">This type represents the memory associated with the writable bytes.</td>
</tr>
<tr class="odd">
<td><code>x1.size()</code></td>
<td><code>size_t</code></td>
<td style="text-align: left;">Returns the number of readable bytes.</td>
</tr>
<tr class="even">
<td><code>x1.max_size()</code></td>
<td><code>size_t</code></td>
<td style="text-align: left;">Returns the maximum number of bytes, both readable and writable, that can be held by <code>x1</code>.</td>
</tr>
<tr class="odd">
<td><code>x1.capacity()</code></td>
<td><code>size_t</code></td>
<td style="text-align: left;">Returns the maximum number of bytes, both readable and writable, that can be held by <code>x1</code> without requiring reallocation.</td>
</tr>
<tr class="even">
<td><code>x1.data()</code></td>
<td><code>X::const_buffers_type</code></td>
<td style="text-align: left;">Returns a constant buffer sequence <code>u</code> that represents the readable bytes, and where <code>buffer_size(u) == size()</code>.</td>
</tr>
<tr class="odd">
<td><code>x.prepare(n)</code></td>
<td><code>X::mutable_buffers_type</code></td>
<td style="text-align: left;">Returns a mutable buffer sequence <code>u</code> representing the writable bytes, and where <code>buffer_size(u) == n</code>. The dynamic buffer reallocates memory as required. All constant or mutable buffer sequences previously obtained using <code>data()</code> or <code>prepare()</code> are invalidated. Throws: <code>length_error</code> if <code>size() + n</code> exceeds <code>max_size()</code>.</td>
</tr>
<tr class="even">
<td><code>x.commit(n)</code></td>
<td></td>
<td style="text-align: left;">Appends <code>n</code> bytes from the start of the writable bytes to the end of the readable bytes. The remainder of the writable bytes are discarded. If <code>n</code> is greater than the number of writable bytes, all writable bytes are appended to the readable bytes. All constant or mutable buffer sequences previously obtained using <code>data()</code> or <code>prepare()</code> are invalidated.</td>
</tr>
<tr class="odd">
<td><code>x.consume(n)</code></td>
<td></td>
<td style="text-align: left;">Removes <code>n</code> bytes from beginning of the readable bytes. If <code>n</code> is greater than the number of readable bytes, all readable bytes are removed. All constant or mutable buffer sequences previously obtained using <code>data()</code> or <code>prepare()</code> are invalidated.</td>
</tr>
</tbody>
</table>
</blockquote>
<p>This separation between the readable and writable bytes can be visualised in the following sequence of operations:</p>
<p><img src="data:image/png;base64,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" style="width:18cm" /></p>
<p>Historically, the separation of readable bytes and writable bytes originally followed the design model of <code>std::streambuf</code>, which divides its memory into input and output sequences. This design was preserved even though DynamicBuffer was ultimately decoupled from concrete streambuf classes.</p>
<h2 id="problem">Problem</h2>
<p>Dynamic buffers are intended to be used in compositions, such as an algorithm that reads a sequence of delimited headers from a socket:</p>
<pre><code>void read_headers(std::string&amp; data)
{
  size_t n = net::read_until(my_socket, net::dynamic_buffer(data), &#39;\n&#39;);
  // process 1st header and consume it
  n = net::read_until(my_socket, net::dynamic_buffer(data), &#39;\n&#39;);
  // process 2nd header and consume it
}</code></pre>
<p>However, a problem arises when we want to make our algorithm generic across all DynamicBuffer types:</p>
<pre>
template &lt;typename DynamicBuffer&gt;
void read_headers(DynamicBuffer buf)
{
  size_t n = net::read_until(my_socket, std::move(buf), '\n');
  // process 1st header and consume it
  n = net::read_until(my_socket, <font color="red">???</font>, '\n');
  // process 2nd header and consume it
}
</pre>
<p>As highlighted by P1100r0, we can see here that the current specification of the DynamicBuffer requirements inhibits layered composition of I/O operations. This is a consequence of the type requirements stipulating move-constructibility.</p>
<p>It is worth noting that this problem has no direct impact on the Networking TS itself, as DynamicBuffer is already sufficient for the needs of algorithms defined in the TS). However, we feel it is still worth addressing this problem to enable the development of higher layer algorithms that use dynamic buffers.</p>
<h2 id="analysis">Analysis</h2>
<p>The DynamicBuffer requirements embody two distinct responsibilities:</p>
<ol type="1">
<li>The ability to dynamically resize underlying memory regions.</li>
<li>To separate the buffer into two parts: readable bytes and writable bytes.</li>
</ol>
<p>It is this second requirement that is the source of the problem, in that it requires a dynamic buffer class to be stateful. Specifically, the dynamic buffer has to maintain state, namely the boundary between the readable and writable regions of memory, across the operations that use it.</p>
<p><img 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" style="width:15cm" /></p>
<p>This statefulness can be observed in the implementation of concrete dynamic buffers, such as <code>dynamic_string_buffer</code>:</p>
<pre>
template &lt;...&gt;
class dynamic_string_buffer
{
  // ...
private:
  basic_string&lt;...&gt;& string_;
  <font color="blue">size_t size_;</font>
  const size_t max_size_;
};
</pre>
<h2 id="solution-proposed-by-p1100r0">Solution proposed by P1100r0</h2>
<p>P1100r0 proposed removing the <code>MoveConstructible</code> requirement from DynamicBuffer, and instead stipulating that DynamicBuffer types be used exclusively by reference.</p>
<p>This changes the typical use of a dynamic buffer as shown below:</p>
<pre>
<del>string data;</del>
<del>// ...</del>
<del>size_t n = net::read_until(my_socket</del>
<del>    net::dynamic_buffer(data, MY_MAX),</del>
<del>    '\n');</del>

net::dynamic_string_buffer data;
size_t n = net::read_until(my_socket, data, '\n');
std::string s = data.release();
</pre>
<p>but does enable the development of higher level abstractions:</p>
<pre>
template &lt;typename DynamicBuffer&gt;
void read_headers(DynamicBuffer<ins>&amp;</ins> buf)
{
  size_t n = net::read_until(my_socket, <del>std::move(buf)</del><ins>buf</ins>, '\n');
  // process 1st header and consume it
  n = net::read_until(my_socket, <ins>buf</ins>, '\n');
  // process 2nd header and consume it
}

// ...

net::dynamic_string_buffer data;
read_headers(data);
std::string s = data.release();
</pre>
<h2 id="alternate-solution-discussed-and-accepted-by-lewgi">Alternate solution discussed and accepted by LEWGI</h2>
<p>If we consider the way in which these two parts are used within networking TS I/O operations, we see that the distinction between readable and writable parts is actually only important for the duration of an operation.</p>
<p>For example, a DynamicBuffer-enabled read operation:</p>
<ol type="1">
<li>Prepares writable memory to be used as a target for the underlying read operation.</li>
<li>Performs the underlying operation.</li>
<li>Commits the number of bytes transferred by the operation.</li>
</ol>
<p>Following the operation, the entire DynamicBuffer consists of readable bytes.</p>
<p>Thus, the alternative solution is to change the DynamicBuffer requirements to have one responsibility only:</p>
<ul>
<li>To dynamically resize the underlying memory.</li>
</ul>
<p>The responsibility for distinguishing between readable and writable bytes is moved to the operations and algorithms that work with DynamicBuffer. This removes the statefulness requirement from DynamicBuffer, and allows DynamicBuffer to be considered a lightweight, copy-constructible type (just as the statically sized ConstBufferSequence and MutableBufferSequence are).</p>
<p>Thus, the DynamicBuffer type requirements are changed from <code>MoveConstructible</code> to <code>CopyConstructible</code>, as well as the changes shown in the updated table below.</p>
<blockquote>
<table>
<colgroup>
<col style="width: 28%" />
<col style="width: 37%" />
<col style="width: 34%" />
</colgroup>
<thead>
<tr class="header">
<th>expression</th>
<th>type</th>
<th style="text-align: left;">assertion/note pre/post-conditions</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td><code>X::const_buffers_type</code></td>
<td>type meeting ConstBufferSequence requirements.</td>
<td style="text-align: left;">This type represents the <ins>underlying</ins> memory <del>associated with the readable bytes</del> <ins>as non-modifiable bytes</ins>.</td>
</tr>
<tr class="even">
<td><code>X::mutable_buffers_type</code></td>
<td>type meeting MutableBufferSequence requirements.</td>
<td style="text-align: left;">This type represents the <ins>underlying</ins> memory <del>associated with the writable bytes</del> <ins>as modifiable bytes</ins>.</td>
</tr>
<tr class="odd">
<td><code>x1.size()</code></td>
<td><code>size_t</code></td>
<td style="text-align: left;">Returns the number of <del>readable</del> bytes.</td>
</tr>
<tr class="even">
<td><code>x1.max_size()</code></td>
<td><code>size_t</code></td>
<td style="text-align: left;">Returns the maximum number of bytes<del>, both readable and writable,</del> that can be held by <code>x1</code>.</td>
</tr>
<tr class="odd">
<td><code>x1.capacity()</code></td>
<td><code>size_t</code></td>
<td style="text-align: left;">Returns the maximum number of bytes<del>, both readable and writable,</del> that can be held by <code>x1</code> without requiring reallocation.</td>
</tr>
<tr class="even">
<td><del><code>x1.data()</code></del></td>
<td><del><code>X::const_buffers_type</code></del></td>
<td style="text-align: left;"><del>Returns a constant buffer sequence <code>u</code> that represents the readable bytes, and where <code>buffer_size(u) == size()</code>.</del></td>
</tr>
<tr class="odd">
<td><del><code>x.prepare(n)</code></del></td>
<td><del><code>X::mutable_buffers_type</code></del></td>
<td style="text-align: left;"><del>Returns a mutable buffer sequence <code>u</code> representing the writable bytes, and where <code>buffer_size(u) == n</code>. The dynamic buffer reallocates memory as required. All constant or mutable buffer sequences previously obtained using <code>data()</code> or <code>prepare()</code> are invalidated. Throws: <code>length_error</code> if <code>size() + n</code> exceeds <code>max_size()</code>.</del></td>
</tr>
<tr class="even">
<td><del><code>x.commit(n)</code></del></td>
<td></td>
<td style="text-align: left;"><del>Appends <code>n</code> bytes from the start of the writable bytes to the end of the readable bytes. The remainder of the writable bytes are discarded. If <code>n</code> is greater than the number of writable bytes, all writable bytes are appended to the readable bytes. All constant or mutable buffer sequences previously obtained using <code>data()</code> or <code>prepare()</code> are invalidated.</del></td>
</tr>
<tr class="odd">
<td><ins><code>x1.data(pos, n)</code></ins></td>
<td><ins><code>X::const_buffers_type</code></ins></td>
<td style="text-align: left;"><ins>Returns a constant buffer sequence <code>u</code> that represents the region of underlying memory at offset <code>pos</code> and length <code>n</code>.</ins></td>
</tr>
<tr class="even">
<td><ins><code>x.data(pos, n)</code></ins></td>
<td><ins><code>X::mutable_buffers_type</code></ins></td>
<td style="text-align: left;"><ins>Returns a mutable buffer sequence <code>u</code> that represents the region of underlying memory at offset <code>pos</code> and length <code>n</code>.</ins></td>
</tr>
<tr class="odd">
<td><ins><code>x.grow(n)</code></ins></td>
<td></td>
<td style="text-align: left;"><ins>Adds <code>n</code> bytes of space at the end of the underlying memory. All constant or mutable buffer sequences previously obtained using <code>data()</code> are invalidated.</ins></td>
</tr>
<tr class="even">
<td><ins><code>x.shrink(n)</code></ins></td>
<td></td>
<td style="text-align: left;"><ins>Removes <code>n</code> bytes of space from the end of the underlying memory. If <code>n</code> is greater than the number of bytes, all bytes are discarded. All constant or mutable buffer sequences previously obtained using <code>data()</code> are invalidated.</ins></td>
</tr>
<tr class="odd">
<td><code>x.consume(n)</code></td>
<td></td>
<td style="text-align: left;">Removes <code>n</code> bytes from beginning of the <del>readable</del> bytes. If <code>n</code> is greater than the number of <del>readable</del> bytes, all <del>readable</del> bytes are removed. All constant or mutable buffer sequences previously obtained using <code>data()</code> <del>or <code>prepare()</code></del> are invalidated.</td>
</tr>
</tbody>
</table>
</blockquote>
<p>These new requirements are illustrated by the following sequence of operations:</p>
<p><img 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" style="width:15cm" /></p>
<p>Concrete dynamic buffer implementations such as <code>dynamic_string_buffer</code> now no longer need to maintain the state representing the marker between readable and writable bytes:</p>
<pre>
template &lt;...&gt;
class dynamic_string_buffer
{
  // ...
private:
  basic_string&lt;...&gt;& string_;
  <del>size_t size_;</del>
  const size_t max_size_;
};
</pre>
<p>Existing dynamic buffer uses are unchanged by this solution:</p>
<pre><code>string data;
// ...
size_t n = net::read_until(my_socket
    net::dynamic_buffer(data, MY_MAX),
    &#39;\n&#39;);</code></pre>
<p>and higher level abstractions are now possible:</p>
<pre>
template &lt;typename DynamicBuffer&gt;
void read_headers(DynamicBuffer buf)
{
  size_t n = net::read_until(my_socket, <del>std::move(buf)</del><ins>buf</ins>, '\n');
  // process 1st header and consume it
  n = net::read_until(my_socket, <ins>buf</ins>, '\n');
  // process 2nd header and consume it
}

// ...

std::string data;
read_headers(net::dynamic_buffer(data));
</pre>
<p>A further advantage of this solution is that, by moving the distinction between the readable and writable bytes from the DynamicBuffer to the algorithms that use it, we now enable algorithms that need to update the notionally “committed” bytes. A simple example of this would be an algorithm that decodes base64-encoded data from a stream-based source: an additional byte of input may require an update to the final byte of output in the buffer. This capability has been requested by Asio users in the past.</p>
<h2 id="naming">Naming</h2>
<p>We may wish to consider other options for the names <code>grow</code>, <code>shrink</code>, and <code>consume</code>. The author has no better suggestions to offer at this time.</p>
<h2 id="implementation-experience">Implementation experience</h2>
<p>The accepted solution was implemented in Asio 1.14.0, which was delivered as part of the Boost 1.70 release.</p>
<h2 id="proposed-changes-to-wording">Proposed changes to wording</h2>
<p>In summary, the following changes would be made to the Networking TS wording:</p>
<ul>
<li>The DynamicBuffer requirements are changed as shown above.</li>
<li>The <code>dynamic_string_buffer</code> and <code>dynamic_vector_buffer</code> classes are altered to satisfy these new requirements.</li>
<li>The DynamicBuffer algorithms (<code>read</code>, <code>async_read</code>, <code>read_until</code>, <code>async_read_until</code>, <code>write</code>, and <code>async_write</code>) are changed to take DynamicBuffer objects by value, and to use the new <code>grow</code> and <code>shrink</code> member functions as required.</li>
</ul>
<p>These changes are relative to N4771.</p>
<p><em>Update the <code>&lt;experimental/buffer&gt;</code> synopsis [buffer.synop] as follows:</em></p>
<div class="wording">
<pre class='codeblock'>
  <span class='comment'>// <a href='#'>[buffer.read]</a>, synchronous read operations:</span>
</pre>
</div>
<p><em>[…]</em></p>
<div class="wording">
<pre class='codeblock'>
  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncReadStream, <span class='keyword'>class</span> DynamicBuffer<span class='anglebracket'>&gt;</span>
    size_t read<span class='parenthesis'>(</span>SyncReadStream<span class='operator'>&amp;</span> stream, DynamicBuffer<del ><span class='tcode_in_codeblock'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b<span class='parenthesis'>)</span>;
  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncReadStream, <span class='keyword'>class</span> DynamicBuffer<span class='anglebracket'>&gt;</span>
    size_t read<span class='parenthesis'>(</span>SyncReadStream<span class='operator'>&amp;</span> stream, DynamicBuffer<del ><span class='tcode_in_codeblock'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b, error_code<span class='operator'>&amp;</span> ec<span class='parenthesis'>)</span>;
  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncReadStream, <span class='keyword'>class</span> DynamicBuffer, <span class='keyword'>class</span> CompletionCondition<span class='anglebracket'>&gt;</span>
    size_t read<span class='parenthesis'>(</span>SyncReadStream<span class='operator'>&amp;</span> stream, DynamicBuffer<del ><span class='tcode_in_codeblock'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b,
                CompletionCondition completion_condition<span class='parenthesis'>)</span>;
  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncReadStream, <span class='keyword'>class</span> DynamicBuffer, <span class='keyword'>class</span> CompletionCondition<span class='anglebracket'>&gt;</span>
    size_t read<span class='parenthesis'>(</span>SyncReadStream<span class='operator'>&amp;</span> stream, DynamicBuffer<del ><span class='tcode_in_codeblock'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b,
                CompletionCondition completion_condition, error_code<span class='operator'>&amp;</span> ec<span class='parenthesis'>)</span>;

  <span class='comment'>// <a href='#'>[buffer.async.read]</a>, asynchronous read operations:</span>
</pre>
</div>
<p><em>[…]</em></p>
<div class="wording">
<pre class='codeblock'>
  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> AsyncReadStream, <span class='keyword'>class</span> DynamicBuffer, <span class='keyword'>class</span> CompletionToken<span class='anglebracket'>&gt;</span>
    <span class='textit'><span class='texttt'>DEDUCED</span></span> async_read<span class='parenthesis'>(</span>AsyncReadStream<span class='operator'>&amp;</span> stream,
                       DynamicBuffer<del ><span class='tcode_in_codeblock'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b, CompletionToken<span class='operator'>&amp;</span><span class='operator'>&amp;</span> token<span class='parenthesis'>)</span>;
  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> AsyncReadStream, <span class='keyword'>class</span> DynamicBuffer,
    <span class='keyword'>class</span> CompletionCondition, <span class='keyword'>class</span> CompletionToken<span class='anglebracket'>&gt;</span>
      <span class='textit'><span class='texttt'>DEDUCED</span></span> async_read<span class='parenthesis'>(</span>AsyncReadStream<span class='operator'>&amp;</span> stream,
                         DynamicBuffer<del ><span class='tcode_in_codeblock'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b,
                         CompletionCondition completion_condition,
                         CompletionToken<span class='operator'>&amp;</span><span class='operator'>&amp;</span> token<span class='parenthesis'>)</span>;

  <span class='comment'>// <a href='#'>[buffer.write]</a>, synchronous write operations:</span>
</pre>
</div>
<p><em>[…]</em></p>
<div class="wording">
<pre class='codeblock'>
  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncWriteStream, <span class='keyword'>class</span> DynamicBuffer<span class='anglebracket'>&gt;</span>
    size_t write<span class='parenthesis'>(</span>SyncWriteStream<span class='operator'>&amp;</span> stream, DynamicBuffer<del ><span class='tcode_in_codeblock'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b<span class='parenthesis'>)</span>;
  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncWriteStream, <span class='keyword'>class</span> DynamicBuffer<span class='anglebracket'>&gt;</span>
    size_t write<span class='parenthesis'>(</span>SyncWriteStream<span class='operator'>&amp;</span> stream, DynamicBuffer<del ><span class='tcode_in_codeblock'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b, error_code<span class='operator'>&amp;</span> ec<span class='parenthesis'>)</span>;
  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncWriteStream, <span class='keyword'>class</span> DynamicBuffer, <span class='keyword'>class</span> CompletionCondition<span class='anglebracket'>&gt;</span>
    size_t write<span class='parenthesis'>(</span>SyncWriteStream<span class='operator'>&amp;</span> stream, DynamicBuffer<del ><span class='tcode_in_codeblock'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b,
                 CompletionCondition completion_condition<span class='parenthesis'>)</span>;
  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncWriteStream, <span class='keyword'>class</span> DynamicBuffer, <span class='keyword'>class</span> CompletionCondition<span class='anglebracket'>&gt;</span>
    size_t write<span class='parenthesis'>(</span>SyncWriteStream<span class='operator'>&amp;</span> stream, DynamicBuffer<del ><span class='tcode_in_codeblock'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b,
                 CompletionCondition completion_condition, error_code<span class='operator'>&amp;</span> ec<span class='parenthesis'>)</span>;

  <span class='comment'>// <a href='#'>[buffer.async.write]</a>, asynchronous write operations:</span>
</pre>
</div>
<p><em>[…]</em></p>
<div class="wording">
<pre class='codeblock'>
  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> AsyncWriteStream, <span class='keyword'>class</span> DynamicBuffer, <span class='keyword'>class</span> CompletionToken<span class='anglebracket'>&gt;</span>
    <span class='textit'><span class='texttt'>DEDUCED</span></span> async_write<span class='parenthesis'>(</span>AsyncWriteStream<span class='operator'>&amp;</span> stream,
                     DynamicBuffer<del ><span class='tcode_in_codeblock'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b, CompletionToken<span class='operator'>&amp;</span><span class='operator'>&amp;</span> token<span class='parenthesis'>)</span>;
  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> AsyncWriteStream, <span class='keyword'>class</span> DynamicBuffer,
    <span class='keyword'>class</span> CompletionCondition, <span class='keyword'>class</span> CompletionToken<span class='anglebracket'>&gt;</span>
      <span class='textit'><span class='texttt'>DEDUCED</span></span> async_write<span class='parenthesis'>(</span>AsyncWriteStream<span class='operator'>&amp;</span> stream,
                          DynamicBuffer<del ><span class='tcode_in_codeblock'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b,
                          CompletionCondition completion_condition,
                          CompletionToken<span class='operator'>&amp;</span><span class='operator'>&amp;</span> token<span class='parenthesis'>)</span>;

  <span class='comment'>// <a href='#'>[buffer.read.until]</a>, synchronous delimited read operations:</span>

  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncReadStream, <span class='keyword'>class</span> DynamicBuffer<span class='anglebracket'>&gt;</span>
    size_t read_until<span class='parenthesis'>(</span>SyncReadStream<span class='operator'>&amp;</span> s, DynamicBuffer<del ><span class='tcode_in_codeblock'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b, <span class='keyword'>char</span> delim<span class='parenthesis'>)</span>;
  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncReadStream, <span class='keyword'>class</span> DynamicBuffer<span class='anglebracket'>&gt;</span>
    size_t read_until<span class='parenthesis'>(</span>SyncReadStream<span class='operator'>&amp;</span> s, DynamicBuffer<del ><span class='tcode_in_codeblock'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b,
                      <span class='keyword'>char</span> delim, error_code<span class='operator'>&amp;</span> ec<span class='parenthesis'>)</span>;
  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncReadStream, <span class='keyword'>class</span> DynamicBuffer<span class='anglebracket'>&gt;</span>
    size_t read_until<span class='parenthesis'>(</span>SyncReadStream<span class='operator'>&amp;</span> s, DynamicBuffer<del ><span class='tcode_in_codeblock'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b, string_view delim<span class='parenthesis'>)</span>;
  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncReadStream, <span class='keyword'>class</span> DynamicBuffer<span class='anglebracket'>&gt;</span>
    size_t read_until<span class='parenthesis'>(</span>SyncReadStream<span class='operator'>&amp;</span> s, DynamicBuffer<del ><span class='tcode_in_codeblock'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b,
                      string_view delim, error_code<span class='operator'>&amp;</span> ec<span class='parenthesis'>)</span>;

  <span class='comment'>// <a href='#'>[buffer.async.read.until]</a>, asynchronous delimited read operations:</span>

  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> AsyncReadStream, <span class='keyword'>class</span> DynamicBuffer, <span class='keyword'>class</span> CompletionToken<span class='anglebracket'>&gt;</span>
    <span class='textit'><span class='texttt'>DEDUCED</span></span> async_read_until<span class='parenthesis'>(</span>AsyncReadStream<span class='operator'>&amp;</span> s,
                             DynamicBuffer<del ><span class='tcode_in_codeblock'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b, <span class='keyword'>char</span> delim,
                             CompletionToken<span class='operator'>&amp;</span><span class='operator'>&amp;</span> token<span class='parenthesis'>)</span>;
  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> AsyncReadStream, <span class='keyword'>class</span> DynamicBuffer, <span class='keyword'>class</span> CompletionToken<span class='anglebracket'>&gt;</span>
    <span class='textit'><span class='texttt'>DEDUCED</span></span> async_read_until<span class='parenthesis'>(</span>AsyncReadStream<span class='operator'>&amp;</span> s,
                             DynamicBuffer<del ><span class='tcode_in_codeblock'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b, string_view delim,
                             CompletionToken<span class='operator'>&amp;</span><span class='operator'>&amp;</span> token<span class='parenthesis'>)</span>;
</pre>
</div>
<p><em>Update the DynamicBuffer requirements [buffer.reqmts.dynamicbuffer] as follows:</em></p>
<div class="wording">
<h3>
<a class='secnum' style='min-width:103pt'>16.2.4</a> Dynamic buffer requirements <a class='abbr_ref' href='#'>[buffer.reqmts.dynamicbuffer]</a>
</h3>
<div class="para">
<div class="marginalizedparent">
<a class='marginalized' href='buffer.reqmts.dynamicbuffer.html#1'>1</a>
</div>
A <a class='hidden_link' href='#def:dynamic_buffer' id='def:dynamic_buffer'><i >dynamic buffer</i></a> encapsulates memory storage that may be automatically resized as required<ins >.</ins><del >, where the memory is divided into two regions: readable bytes followed by writable bytes. These memory regions are internal to the dynamic buffer, but d</del><ins >D</ins>irect access to the elements is provided to permit them to be efficiently used with I/O operations.
<div id="buffer.reqmts.dynamicbuffer-1.note-1" class="note">
[ <a class='note_link' href='#buffer.reqmts.dynamicbuffer-1.note-1'><span class="textit">Note</span></a>
<div class="noteBody">
<span class="textit">:</span> Such as the <span class="texttt">send</span> or <span class="texttt">receive</span> operations of a socket. <del > The readable bytes would be used as the constant buffer sequence for <span class="texttt">send</span>, and the writable bytes used as the mutable buffer sequence for <span class="texttt">receive</span>.</del> — <i>end note</i>
</div>
 ]
</div>
<del > Data written to the writable bytes of a dynamic buffer object is appended to the readable bytes of the same object.</del>
</div>
<div class="para">
<div class="marginalizedparent">
<a class='marginalized' href='buffer.reqmts.dynamicbuffer.html#2'>2</a>
</div>
A type <span class="texttt">X</span> meets the <span class="texttt">DynamicBuffer</span> requirements if it satisfies the requirements of <span class="texttt">Destructible</span> (C++2014[destructible]) and <del ><span class="texttt">MoveConstructible</span> (C++2014[moveconstructible])</del><ins ><span class="texttt">CopyConstructible</span> (C++2014[copyconstructible])</ins>, as well as the additional requirements listed in Table <a href='#tab:buffer.reqmts.dynamicbuffer.requirements'>14</a>.
</div>
<div class="para">
<div class="marginalizedparent">
<a class='marginalized' href='buffer.reqmts.dynamicbuffer.html#3'>3</a>
</div>
<p>In Table <a href='#tab:buffer.reqmts.dynamicbuffer.requirements'>14</a>, <span class="texttt">x</span> denotes a value of type <span class="texttt">X</span>, <span class="texttt">x1</span> denotes a (possibly const) value of type <span class="texttt">X</span>, <ins ><span class="texttt">pos</span> denotes a (possibly const) value of type <span class="texttt">size_­t</span>,</ins> and <span class="texttt">n</span> denotes a (possibly const) value of type <span class="texttt">size_­t</span>.<span class="indexparent"><a class='index' id=':requirements,DynamicBuffer'></a></span></p>
<div id="tab:buffer.reqmts.dynamicbuffer.requirements" class="numberedTable">
Table <a href='#tab:buffer.reqmts.dynamicbuffer.requirements'>14</a>: DynamicBuffer requirements<br>
<table>
<tr class="rowsep">
<td class="center">
<b>expression</b>
</td>
<td class="center">
<b>type</b>
</td>
<td class="center">
<b>assertion/note pre/post-conditions</b>
</td>
</tr>
<tr class="capsep">
<td class="left">
<div style="height:0.6em;display:block">

</div>
<span class="texttt">X<span class="operator">​::​</span>const_­buffers_­type</span>
</td>
<td class="left">
type meeting ConstBufferSequence (<a href='#buffer.reqmts.constbuffersequence'>[buffer.reqmts.constbuffersequence]</a>) requirements.
</td>
<td class="left">
This type represents the <ins >underlying</ins> memory <del >associated with the readable bytes</del><ins >as non-modifiable bytes</ins>.
</td>
</tr>
<tr class="rowsep">
<td class="left">
<span class="texttt">X<span class="operator">​::​</span>mutable_­buffers_­type</span>
</td>
<td class="left">
type meeting MutableBufferSequence (<a href='#buffer.reqmts.constbuffersequence'>[buffer.reqmts.constbuffersequence]</a>) requirements.
</td>
<td class="left">
This type represents the <ins >underlying</ins> memory <del >associated with the writable bytes</del><ins >as modifiable bytes</ins>.
</td>
</tr>
<tr class="rowsep">
<td class="left">
<span class="texttt">x1<span class="operator">.</span>size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>
</td>
<td class="left">
<span class="texttt">size_­t</span>
</td>
<td class="left">
Returns the number of <del >readable</del> bytes.
</td>
</tr>
<tr class="rowsep">
<td class="left">
<span class="texttt">x1<span class="operator">.</span>max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>
</td>
<td class="left">
<span class="texttt">size_­t</span>
</td>
<td class="left">
Returns the maximum number of bytes<del >, both readable and writable,</del> that can be held by <span class="texttt">x1</span>.
</td>
</tr>
<tr class="rowsep">
<td class="left">
<span class="texttt">x1<span class="operator">.</span>capacity<span class="parenthesis">(</span><span class="parenthesis">)</span></span>
</td>
<td class="left">
<span class="texttt">size_­t</span>
</td>
<td class="left">
Returns the maximum number of bytes<del >, both readable and writable,</del> that can be held by <span class="texttt">x1</span> without requiring reallocation.
</td>
</tr>
<tr class="rowsep">
<td class="left">
<del>
<span class="texttt">x1<span class="operator">.</span>data<span class="parenthesis">(</span><span class="parenthesis">)</span></span>
</del>
</td>
<td class="left">
<del>
<span class="texttt">X<span class="operator">​::​</span>const_­buffers_­type</span>
</del>
</td>
<td class="left">
<del>
Returns a constant buffer sequence <span class="texttt">u</span> that represents the readable bytes, and where <span class="texttt">buffer_­size<span class="parenthesis">(</span>u<span class="parenthesis">)</span> <span class="operator">=</span><span class="operator">=</span> size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>.
</del>
</td>
</tr>
<tr class="rowsep">
<td class="left">
<del>
<span class="texttt">x<span class="operator">.</span>prepare<span class="parenthesis">(</span>n<span class="parenthesis">)</span></span>
</del>
</td>
<td class="left">
<del>
<span class="texttt">X<span class="operator">​::​</span>mutable_­buffers_­type</span>
</del>
</td>
<td class="left">
<del>
Returns a mutable buffer sequence <span class="texttt">u</span> representing the writable bytes, and where <span class="texttt">buffer_­size<span class="parenthesis">(</span>u<span class="parenthesis">)</span> <span class="operator">=</span><span class="operator">=</span> n</span>. The dynamic buffer reallocates memory as required. All constant or mutable buffer sequences previously obtained using <span class="texttt">data<span class="parenthesis">(</span><span class="parenthesis">)</span></span> or <span class="texttt">prepare<span class="parenthesis">(</span><span class="parenthesis">)</span></span> are invalidated.<br/><span class="textit">Throws:</span> <span class="texttt">length_­error</span> if <span class="texttt">size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">+</span> n</span> exceeds <span class="texttt">max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>.
</del>
</td>
</tr>
<tr class="rowsep">
<td class="left">
<del>
<span class="texttt">x<span class="operator">.</span>commit<span class="parenthesis">(</span>n<span class="parenthesis">)</span></span>
</del>
</td>
<td class="empty left">
</td>
<td class="left">
<del>
Appends <span class="texttt">n</span> bytes from the start of the writable bytes to the end of the readable bytes. The remainder of the writable bytes are discarded. If <span class="texttt">n</span> is greater than the number of writable bytes, all writable bytes are appended to the readable bytes. All constant or mutable buffer sequences previously obtained using <span class="texttt">data<span class="parenthesis">(</span><span class="parenthesis">)</span></span> or <span class="texttt">prepare<span class="parenthesis">(</span><span class="parenthesis">)</span></span> are invalidated.
</del>
</td>
</tr>
<tr class="rowsep">
<td class="left">
<ins>
<span class="texttt">x1<span class="operator">.</span>data<span class="parenthesis">(</span>pos, n<span class="parenthesis">)</span></span>
</ins>
</td>
<td class="left">
<ins>
<span class="texttt">X<span class="operator">​::​</span>const_­buffers_­type</span>
</ins>
</td>
<td class="left">
<ins>
Returns a constant buffer sequence <span class="texttt">u</span> that represents the region of underlying memory at offset <span class="texttt">pos</span> and length <span class="texttt">n</span>.
</ins>
</td>
</tr>
<tr class="rowsep">
<td class="left">
<ins>
<span class="texttt">x<span class="operator">.</span>data<span class="parenthesis">(</span>pos, n<span class="parenthesis">)</span></span>
</ins>
</td>
<td class="left">
<ins>
<span class="texttt">X<span class="operator">​::​</span>mutable_­buffers_­type</span>
</ins>
</td>
<td class="left">
<ins>
Returns a mutable buffer sequence <span class="texttt">u</span> that represents the region of underlying memory at offset <span class="texttt">pos</span> and length <span class="texttt">n</span>.
</ins>
</td>
</tr>
<tr class="rowsep">
<td class="left">
<ins>
<span class="texttt">x<span class="operator">.</span>grow<span class="parenthesis">(</span>n<span class="parenthesis">)</span></span>
</ins>
</td>
<td class="empty left">
</td>
<td class="left">
<ins>
Adds <span class="texttt">n</span> bytes of space at the end of the underlying memory. All constant or mutable buffer sequences previously obtained using <span class="texttt">data<span class="parenthesis">(</span><span class="parenthesis">)</span></span> are invalidated.
</ins>
</td>
</tr>
<tr class="rowsep">
<td class="left">
<ins>
<span class="texttt">x<span class="operator">.</span>shrink<span class="parenthesis">(</span>n<span class="parenthesis">)</span></span>
</ins>
</td>
<td class="empty left">
</td>
<td class="left">
<ins>
Removes <span class="texttt">n</span> bytes of space from the end of the underlying memory. If <span class="texttt">n</span> is greater than the number of bytes, all bytes are discarded. All constant or mutable buffer sequences previously obtained using <span class="texttt">data<span class="parenthesis">(</span><span class="parenthesis">)</span></span> are invalidated.
</ins>
</td>
</tr>
<tr class="rowsep">
<td class="left">
<span class="texttt">x<span class="operator">.</span>consume<span class="parenthesis">(</span>n<span class="parenthesis">)</span></span>
</td>
<td class="empty left">
</td>
<td class="left">
Removes <span class="texttt">n</span> bytes from beginning of the <del >readable</del> bytes. If <span class="texttt">n</span> is greater than the number of <del >readable</del> bytes, all <del >readable</del> bytes are removed. All constant or mutable buffer sequences previously obtained using <span class="texttt">data<span class="parenthesis">(</span><span class="parenthesis">)</span></span> <del >or <span class="texttt">prepare<span class="parenthesis">(</span><span class="parenthesis">)</span></span> </del>are invalidated.
</td>
</tr>
</table>
</div>
</div>
</div>
<p><em>Modify the <code>dynamic_vector_buffer</code> class [buffer.dynamic.vector] as follows:</em></p>
<div class="wording">
<h2>
<a class='secnum' style='min-width:88pt'>16.12</a> Class template <span class="texttt">dynamic_­vector_­buffer</span> <a class='abbr_ref' href='#'>[buffer.dynamic.vector]</a>
</h2>
<span class="indexparent"><a class='index' id='lib:dynamic_vector_buffer'></a></span>
<div class="para">
<div class="marginalizedparent">
<a class='marginalized' href='buffer.dynamic.vector.html#1'>1</a>
</div>
<div class="sourceLinkParent">
<a class='sourceLink' href='#'>#</a>
</div>
Class template <span class="texttt">dynamic_­vector_­buffer</span> is an adaptor used to automatically grow or shrink a <span class="texttt">vector</span> object, to reflect the data successfully transferred in an I/O operation.
<pre class='codeblock'>
<span class='keyword'>namespace</span> std <span class='curlybracket'>{</span>
<span class='keyword'>namespace</span> experimental <span class='curlybracket'>{</span>
<span class='keyword'>namespace</span> net <span class='curlybracket'>{</span>
<span class='keyword'>inline</span> <span class='keyword'>namespace</span> v1 <span class='curlybracket'>{</span>

  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> T, <span class='keyword'>class</span> Allocator<span class='anglebracket'>&gt;</span>
  <span class='keyword'>class</span> dynamic_vector_buffer
  <span class='curlybracket'>{</span>
  <span class='keyword'>public</span><span class='operator'>:</span>
    <span class='comment'>// types:</span>
    <span class='keyword'>using</span> const_buffers_type <span class='operator'>=</span> const_buffer;
    <span class='keyword'>using</span> mutable_buffers_type <span class='operator'>=</span> mutable_buffer;

    <span class='comment'>// constructors:</span>
    <span class='keyword'>explicit</span> dynamic_vector_buffer<span class='parenthesis'>(</span>vector<span class='anglebracket'>&lt;</span>T, Allocator<span class='anglebracket'>&gt;</span><span class='operator'>&amp;</span> vec<span class='parenthesis'>)</span> <span class='keyword'>noexcept</span>;
    dynamic_vector_buffer<span class='parenthesis'>(</span>vector<span class='anglebracket'>&lt;</span>T, Allocator<span class='anglebracket'>&gt;</span><span class='operator'>&amp;</span> vec,
                          size_t maximum_size<span class='parenthesis'>)</span> <span class='keyword'>noexcept</span>;
    <del ><span class='tcode_in_codeblock'>dynamic_&shy;vector_&shy;buffer<span class='parenthesis'>(</span>dynamic_&shy;vector_&shy;buffer<span class='operator'>&amp;</span><span class='operator'>&amp;</span><span class='parenthesis'>)</span> <span class='operator'>=</span> <span class='keyword'>default</span>;</span></del>

    <span class='comment'>// members:</span>
    size_t size<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;
    size_t max_size<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;
    size_t capacity<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;
    <del ><span class='tcode_in_codeblock'>const_&shy;buffers_&shy;type data<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;</span></del>
    <ins ><span class='tcode_in_codeblock'>mutable_&shy;buffers_&shy;type data<span class='parenthesis'>(</span>size_&shy;t pos, size_&shy;t n<span class='parenthesis'>)</span> <span class='keyword'>noexcept</span>;</span></ins>
    <ins ><span class='tcode_in_codeblock'>const_&shy;buffers_&shy;type data<span class='parenthesis'>(</span>size_&shy;t pos, size_&shy;t n<span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;</span></ins>
    <del ><span class='tcode_in_codeblock'>mutable_&shy;buffers_&shy;type prepare<span class='parenthesis'>(</span>size_&shy;t n<span class='parenthesis'>)</span>;</span></del>
    <del ><span class='tcode_in_codeblock'><span class='keyword'>void</span> commit<span class='parenthesis'>(</span>size_&shy;t n<span class='parenthesis'>)</span> <span class='keyword'>noexcept</span>;</span></del>
    <ins ><span class='tcode_in_codeblock'><span class='keyword'>void</span> grow<span class='parenthesis'>(</span>size_&shy;t n<span class='parenthesis'>)</span>;</span></ins>
    <ins ><span class='tcode_in_codeblock'><span class='keyword'>void</span> shrink<span class='parenthesis'>(</span>size_&shy;t n<span class='parenthesis'>)</span>;</span></ins>
    <span class='keyword'>void</span> consume<span class='parenthesis'>(</span>size_t n<span class='parenthesis'>)</span>;

  <span class='keyword'>private</span><span class='operator'>:</span>
    vector<span class='anglebracket'>&lt;</span>T, Allocator<span class='anglebracket'>&gt;</span><span class='operator'>&amp;</span> vec_; <span class='comment'>// <span class='textit'>exposition only</span></span>
    <del ><span class='tcode_in_codeblock'>size_&shy;t size_&shy;; <span class='comment'>// <span class='textit'>exposition only</span></span></span></del>
    <span class='keyword'>const</span> size_t max_size_; <span class='comment'>// <span class='textit'>exposition only</span></span>
  <span class='curlybracket'>}</span>;

<span class='curlybracket'>}</span> <span class='comment'>// inline namespace v1</span>
<span class='curlybracket'>}</span> <span class='comment'>// namespace net</span>
<span class='curlybracket'>}</span> <span class='comment'>// namespace experimental</span>
<span class='curlybracket'>}</span> <span class='comment'>// namespace std</span>
</pre>
</div>
<div class="para">
<div class="marginalizedparent">
<a class='marginalized' href='buffer.dynamic.vector.html#2'>2</a>
</div>
<div class="sourceLinkParent">
<a class='sourceLink' href='#'>#</a>
</div>
The <span class="texttt">dynamic_­vector_­buffer</span> class template meets the requirements of <span class="texttt">DynamicBuffer</span> (<a href='#buffer.reqmts.dynamicbuffer'>[buffer.reqmts.dynamicbuffer]</a>).
</div>
<div class="para">
<div class="marginalizedparent">
<a class='marginalized' href='buffer.dynamic.vector.html#3'>3</a>
</div>
<div class="sourceLinkParent">
<a class='sourceLink' href='#'>#</a>
</div>
The <span class="texttt">dynamic_­vector_­buffer</span> class template requires that <span class="texttt">T</span> is a trivially copyable or standard-layout type (C++2014[basic.types]) and that <span class="texttt"><span class="keyword">sizeof</span><span class="parenthesis">(</span>T<span class="parenthesis">)</span> <span class="operator">=</span><span class="operator">=</span> <span class="literal">1</span></span>. <span class="indexparent"><a class='index' id='lib:dynamic_vector_buffer,constructor'></a></span>
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<div id="buffer.dynamic.vector-itemdecl:1" class="itemdecl">
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<pre class='itemdeclcode'><span class='keyword'>explicit</span> dynamic_vector_buffer<span class='parenthesis'>(</span>vector<span class='anglebracket'>&lt;</span>T, Allocator<span class='anglebracket'>&gt;</span><span class='operator'>&amp;</span> vec<span class='parenthesis'>)</span> <span class='keyword'>noexcept</span>;
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<span class="textit">Effects:</span>Initializes <span class="texttt">vec_­</span> with <span class="texttt">vec</span><del >, <span class="texttt">size_­</span> with <span class="texttt">vec<span class="operator">.</span>size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>,</del> and <span class="texttt">max_­size_­</span> with <span class="texttt">vec<span class="operator">.</span>max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>.
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<span class="indexparent"><a class='index' id='lib:dynamic_vector_buffer,constructor_'></a></span>
<div id="buffer.dynamic.vector-itemdecl:2" class="itemdecl">
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<pre class='itemdeclcode'>dynamic_vector_buffer<span class='parenthesis'>(</span>vector<span class='anglebracket'>&lt;</span>T, Allocator<span class='anglebracket'>&gt;</span><span class='operator'>&amp;</span> vec,
                      size_t maximum_size<span class='parenthesis'>)</span> <span class='keyword'>noexcept</span>;
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<span class="textit">Requires:</span><span class="texttt">vec<span class="operator">.</span>size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="anglebracket">&lt;</span><span class="operator">=</span> maximum_­size</span>.
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<span class="textit">Effects:</span>Initializes <span class="texttt">vec_­</span> with <span class="texttt">vec</span><del >, <span class="texttt">size_­</span> with <span class="texttt">vec<span class="operator">.</span>size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>,</del> and <span class="texttt">max_­size_­</span> with <span class="texttt">maximum_­size</span>.
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<span class="indexparent"><a class='index' id='lib:size,dynamic_vector_buffer'></a></span><span class="indexparent"><a class='index' id='lib:dynamic_vector_buffer,size'></a></span>
<div id="buffer.dynamic.vector-itemdecl:3" class="itemdecl">
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<pre class='itemdeclcode'>size_t size<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;
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<span class="textit">Returns:</span><del ><span class="texttt">size_­</span></del><ins ><span class="texttt">min<span class="parenthesis">(</span>vec_­<span class="operator">.</span>size<span class="parenthesis">(</span><span class="parenthesis">)</span>, max_­size_­<span class="parenthesis">)</span></span></ins>.
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<span class="indexparent"><a class='index' id='lib:max_size,dynamic_vector_buffer'></a></span><span class="indexparent"><a class='index' id='lib:dynamic_vector_buffer,max_size'></a></span>
<div id="buffer.dynamic.vector-itemdecl:4" class="itemdecl">
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<pre class='itemdeclcode'>size_t max_size<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;
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<span class="textit">Returns:</span><span class="texttt">max_­size_­</span>.
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<span class="indexparent"><a class='index' id='lib:capacity,dynamic_vector_buffer'></a></span><span class="indexparent"><a class='index' id='lib:dynamic_vector_buffer,capacity'></a></span>
<div id="buffer.dynamic.vector-itemdecl:5" class="itemdecl">
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<pre class='itemdeclcode'>size_t capacity<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;
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<span class="textit">Returns:</span><del ><span class="texttt">vec_­<span class="operator">.</span>capacity<span class="parenthesis">(</span><span class="parenthesis">)</span></span></del><ins ><span class="texttt">min<span class="parenthesis">(</span>vec_­<span class="operator">.</span>capacity<span class="parenthesis">(</span><span class="parenthesis">)</span>, max_­size_­<span class="parenthesis">)</span></span></ins>.
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<span class="indexparent"><a class='index' id='lib:data,dynamic_vector_buffer'></a></span><span class="indexparent"><a class='index' id='lib:dynamic_vector_buffer,data'></a></span>
<div id="buffer.dynamic.vector-itemdecl:6" class="itemdecl">
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<pre class='itemdeclcode'><del ><span class='texttt'>const_&shy;buffers_&shy;type data<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;</span></del>
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<del>
<span class="textit">Returns:</span><span class="texttt">buffer<span class="parenthesis">(</span>vec_­, size_­<span class="parenthesis">)</span></span>.
</del>
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<pre class='itemdeclcode'><ins ><span class='texttt'>mutable_&shy;buffers_&shy;type data<span class='parenthesis'>(</span>size_&shy;t pos, size_&shy;t n<span class='parenthesis'>)</span> <span class='keyword'>noexcept</span>;</span></ins>
<ins ><span class='texttt'>const_&shy;buffers_&shy;type data<span class='parenthesis'>(</span>size_&shy;t pos, size_&shy;t n<span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;</span></ins>
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<div class="itemdescr">

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<div class="itemdescr">
<ins>
<span class="textit">Returns:</span><span class="texttt">buffer<span class="parenthesis">(</span>buffer<span class="parenthesis">(</span>vec_­, max_­size_­<span class="parenthesis">)</span> <span class="operator">+</span> pos, n<span class="parenthesis">)</span></span>.
</ins>
</div>
<span class="indexparent"><a class='index' id='lib:prepare,dynamic_vector_buffer'></a></span><span class="indexparent"><a class='index' id='lib:dynamic_vector_buffer,prepare'></a></span>
<div id="buffer.dynamic.vector-itemdecl:8" class="itemdecl">
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<pre class='itemdeclcode'><del ><span class='texttt'>mutable_&shy;buffers_&shy;type prepare<span class='parenthesis'>(</span>size_&shy;t n<span class='parenthesis'>)</span>;</span></del>
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<del>
<span class="textit">Effects:</span>Performs <span class="texttt">vec_­<span class="operator">.</span>resize<span class="parenthesis">(</span>size_­ <span class="operator">+</span> n<span class="parenthesis">)</span></span>.
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<del>
<span class="textit">Returns:</span><span class="texttt">buffer<span class="parenthesis">(</span>buffer<span class="parenthesis">(</span>vec_­<span class="parenthesis">)</span> <span class="operator">+</span> size_­, n<span class="parenthesis">)</span></span>.
</del>
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<a class='marginalized' href='buffer.dynamic.vector.html#13'>13</a>
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<del>
<span class="textit">Remarks:</span><span class="texttt">length_­error</span> if <span class="texttt">size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">+</span> n</span> exceeds <span class="texttt">max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>.
</del>
</div>
</div>
<span class="indexparent"><a class='index' id='lib:commit,dynamic_vector_buffer'></a></span><span class="indexparent"><a class='index' id='lib:dynamic_vector_buffer,commit'></a></span>
<div id="buffer.dynamic.vector-itemdecl:9" class="itemdecl">
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<pre class='itemdeclcode'><del ><span class='texttt'><span class='keyword'>void</span> commit<span class='parenthesis'>(</span>size_&shy;t n<span class='parenthesis'>)</span>;</span></del>
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<del>
<span class="textit">Effects:</span>Performs:
</del>
<pre class='codeblock'>
<del ><span class='tcode_in_codeblock'>size_&shy; <span class='operator'>+</span><span class='operator'>=</span> min<span class='parenthesis'>(</span>n, vec_&shy;<span class='operator'>.</span>size<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='operator'>-</span> size_&shy;<span class='parenthesis'>)</span>;</span></del>
<del ><span class='tcode_in_codeblock'>vec_&shy;<span class='operator'>.</span>resize<span class='parenthesis'>(</span>size_&shy;<span class='parenthesis'>)</span>;</span></del>
</pre>
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</div>
<span class="indexparent"><a class='index' id='lib:grow,dynamic_vector_buffer'></a></span><span class="indexparent"><a class='index' id='lib:dynamic_vector_buffer,grow'></a></span>
<div id="buffer.dynamic.vector-itemdecl:10" class="itemdecl">
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<pre class='itemdeclcode'><ins ><span class='texttt'><span class='keyword'>void</span> grow<span class='parenthesis'>(</span>size_&shy;t n<span class='parenthesis'>)</span>;</span></ins>
</pre>
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<div class="itemdescr">

</div>
<div class="itemdescr">
<ins>
<span class="textit">Effects:</span>Performs <ins ><span class="texttt">vec_­<span class="operator">.</span>resize<span class="parenthesis">(</span>size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">+</span> n<span class="parenthesis">)</span>;</span>
</ins>
.</ins>
</div>
<div class="itemdescr">
<ins>
<span class="textit">Throws:</span><span class="texttt">length_­error</span> if <ins ><span class="texttt">size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="anglebracket">&gt;</span> max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">|</span><span class="operator">|</span> max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">-</span> size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="anglebracket">&lt;</span> n</span>
</ins>
.</ins>
</div>
<span class="indexparent"><a class='index' id='lib:shrink,dynamic_vector_buffer'></a></span><span class="indexparent"><a class='index' id='lib:dynamic_vector_buffer,shrink'></a></span>
<div id="buffer.dynamic.vector-itemdecl:11" class="itemdecl">
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<pre class='itemdeclcode'><ins ><span class='texttt'><span class='keyword'>void</span> shrink<span class='parenthesis'>(</span>size_&shy;t n<span class='parenthesis'>)</span>;</span></ins>
</pre>
</div>
<div class="itemdescr">

</div>
<div class="itemdescr">
<ins>
<span class="textit">Effects:</span>Performs <ins ><span class="texttt">vec_­<span class="operator">.</span>resize<span class="parenthesis">(</span>n <span class="anglebracket">&gt;</span> size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">?</span> <span class="literal">0</span> <span class="operator">:</span> size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">-</span> n<span class="parenthesis">)</span>;</span>
</ins>
.</ins>
</div>
<span class="indexparent"><a class='index' id='lib:consume,dynamic_vector_buffer'></a></span><span class="indexparent"><a class='index' id='lib:dynamic_vector_buffer,consume'></a></span>
<div id="buffer.dynamic.vector-itemdecl:12" class="itemdecl">
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<pre class='itemdeclcode'><span class='keyword'>void</span> consume<span class='parenthesis'>(</span>size_t n<span class='parenthesis'>)</span>;
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<span class="textit">Effects:</span>Performs:
<pre class='codeblock'>
<del ><span class='tcode_in_codeblock'>size_&shy;t m <span class='operator'>=</span> min<span class='parenthesis'>(</span>n, size_&shy;<span class='parenthesis'>)</span>;</span></del>
<del ><span class='tcode_in_codeblock'>vec_&shy;<span class='operator'>.</span>erase<span class='parenthesis'>(</span>vec_&shy;<span class='operator'>.</span>begin<span class='parenthesis'>(</span><span class='parenthesis'>)</span>, vec_&shy;<span class='operator'>.</span>begin<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='operator'>+</span> m<span class='parenthesis'>)</span>;</span></del>
<del ><span class='tcode_in_codeblock'>size_&shy; <span class='operator'>-</span><span class='operator'>=</span> m;</span></del>
<ins ><span class='tcode_in_codeblock'>vec_&shy;<span class='operator'>.</span>erase<span class='parenthesis'>(</span>vec_&shy;<span class='operator'>.</span>begin<span class='parenthesis'>(</span><span class='parenthesis'>)</span>, vec_&shy;<span class='operator'>.</span>begin<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='operator'>+</span> min<span class='parenthesis'>(</span>n, size<span class='parenthesis'>(</span><span class='parenthesis'>)</span><span class='parenthesis'>)</span><span class='parenthesis'>)</span>;</span></ins>
</pre>
</div>
</div>
</div>
<p><em>Modify the <code>dynamic_string_buffer</code> class [buffer.dynamic.string] as follows:</em></p>
<div class="wording">
<h2>
<a class='secnum' style='min-width:88pt'>16.13</a> Class template <span class="texttt">dynamic_­string_­buffer</span> <a class='abbr_ref' href='#'>[buffer.dynamic.string]</a>
</h2>
<span class="indexparent"><a class='index' id='lib:dynamic_string_buffer'></a></span>
<div class="para">
<div class="marginalizedparent">
<a class='marginalized' href='buffer.dynamic.string.html#1'>1</a>
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<div class="sourceLinkParent">
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Class template <span class="texttt">dynamic_­string_­buffer</span> is an adaptor used to automatically grow or shrink a <span class="texttt">basic_­string</span> object, to reflect the data successfully transferred in an I/O operation.
<pre class='codeblock'>
<span class='keyword'>namespace</span> std <span class='curlybracket'>{</span>
<span class='keyword'>namespace</span> experimental <span class='curlybracket'>{</span>
<span class='keyword'>namespace</span> net <span class='curlybracket'>{</span>
<span class='keyword'>inline</span> <span class='keyword'>namespace</span> v1 <span class='curlybracket'>{</span>

  <span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> CharT, <span class='keyword'>class</span> Traits, <span class='keyword'>class</span> Allocator<span class='anglebracket'>&gt;</span>
  <span class='keyword'>class</span> dynamic_string_buffer
  <span class='curlybracket'>{</span>
  <span class='keyword'>public</span><span class='operator'>:</span>
    <span class='comment'>// types:</span>
    <span class='keyword'>using</span> const_buffers_type <span class='operator'>=</span> const_buffer;
    <span class='keyword'>using</span> mutable_buffers_type <span class='operator'>=</span> mutable_buffer;

    <span class='comment'>// constructors:</span>
    <span class='keyword'>explicit</span> dynamic_string_buffer<span class='parenthesis'>(</span>basic_string<span class='anglebracket'>&lt;</span>CharT, Traits, Allocator<span class='anglebracket'>&gt;</span><span class='operator'>&amp;</span> str<span class='parenthesis'>)</span> <span class='keyword'>noexcept</span>;
    dynamic_string_buffer<span class='parenthesis'>(</span>basic_string<span class='anglebracket'>&lt;</span>CharT, Traits, Allocator<span class='anglebracket'>&gt;</span><span class='operator'>&amp;</span> str,
                          size_t maximum_size<span class='parenthesis'>)</span> <span class='keyword'>noexcept</span>;
    <del ><span class='tcode_in_codeblock'>dynamic_&shy;string_&shy;buffer<span class='parenthesis'>(</span>dynamic_&shy;string_&shy;buffer<span class='operator'>&amp;</span><span class='operator'>&amp;</span><span class='parenthesis'>)</span> <span class='operator'>=</span> <span class='keyword'>default</span>;</span></del>

    <span class='comment'>// members:</span>
    size_t size<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;
    size_t max_size<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;
    size_t capacity<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;
    <del ><span class='tcode_in_codeblock'>const_&shy;buffers_&shy;type data<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;</span></del>
    <ins ><span class='tcode_in_codeblock'>mutable_&shy;buffers_&shy;type data<span class='parenthesis'>(</span>size_&shy;t pos, size_&shy;t n<span class='parenthesis'>)</span> <span class='keyword'>noexcept</span>;</span></ins>
    <ins ><span class='tcode_in_codeblock'>const_&shy;buffers_&shy;type data<span class='parenthesis'>(</span>size_&shy;t pos, size_&shy;t n<span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;</span></ins>
    <del ><span class='tcode_in_codeblock'>mutable_&shy;buffers_&shy;type prepare<span class='parenthesis'>(</span>size_&shy;t n<span class='parenthesis'>)</span>;</span></del>
    <del ><span class='tcode_in_codeblock'><span class='keyword'>void</span> commit<span class='parenthesis'>(</span>size_&shy;t n<span class='parenthesis'>)</span> <span class='keyword'>noexcept</span>;</span></del>
    <ins ><span class='tcode_in_codeblock'><span class='keyword'>void</span> grow<span class='parenthesis'>(</span>size_&shy;t n<span class='parenthesis'>)</span>;</span></ins>
    <ins ><span class='tcode_in_codeblock'><span class='keyword'>void</span> shrink<span class='parenthesis'>(</span>size_&shy;t n<span class='parenthesis'>)</span>;</span></ins>
    <span class='keyword'>void</span> consume<span class='parenthesis'>(</span>size_t n<span class='parenthesis'>)</span>;

  <span class='keyword'>private</span><span class='operator'>:</span>
    basic_string<span class='anglebracket'>&lt;</span>CharT, Traits, Allocator<span class='anglebracket'>&gt;</span><span class='operator'>&amp;</span> str_; <span class='comment'>// <span class='textit'>exposition only</span></span>
    <del ><span class='tcode_in_codeblock'>size_&shy;t size_&shy;; <span class='comment'>// <span class='textit'>exposition only</span></span></span></del>
    <span class='keyword'>const</span> size_t max_size_; <span class='comment'>// <span class='textit'>exposition only</span></span>
  <span class='curlybracket'>}</span>;

<span class='curlybracket'>}</span> <span class='comment'>// inline namespace v1</span>
<span class='curlybracket'>}</span> <span class='comment'>// namespace net</span>
<span class='curlybracket'>}</span> <span class='comment'>// namespace experimental</span>
<span class='curlybracket'>}</span> <span class='comment'>// namespace std</span>
</pre>
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The <span class="texttt">dynamic_­string_­buffer</span> class template meets the requirements of <span class="texttt">DynamicBuffer</span> (<a href='#buffer.reqmts.dynamicbuffer'>[buffer.reqmts.dynamicbuffer]</a>).
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The <span class="texttt">dynamic_­string_­buffer</span> class template requires that <span class="texttt"><span class="keyword">sizeof</span><span class="parenthesis">(</span>CharT<span class="parenthesis">)</span> <span class="operator">=</span><span class="operator">=</span> <span class="literal">1</span></span>. <span class="indexparent"><a class='index' id='lib:dynamic_string_buffer,constructor'></a></span>
</div>
<div id="buffer.dynamic.string-itemdecl:1" class="itemdecl">
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<a class='itemDeclLink' href='#buffer.dynamic.string-itemdecl:1'>🔗</a>
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<pre class='itemdeclcode'><span class='keyword'>explicit</span> dynamic_string_buffer<span class='parenthesis'>(</span>basic_string<span class='anglebracket'>&lt;</span>CharT, Traits, Allocator<span class='anglebracket'>&gt;</span><span class='operator'>&amp;</span> str<span class='parenthesis'>)</span> <span class='keyword'>noexcept</span>;
</pre>
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<span class="textit">Effects:</span>Initializes <span class="texttt">str_­</span> with <span class="texttt">str</span><del >, <span class="texttt">size_­</span> with <span class="texttt">str<span class="operator">.</span>size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>,</del> and <span class="texttt">max_­size_­</span> with <span class="texttt">str<span class="operator">.</span>max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>.
</div>
</div>
<span class="indexparent"><a class='index' id='lib:dynamic_string_buffer,constructor_'></a></span>
<div id="buffer.dynamic.string-itemdecl:2" class="itemdecl">
<div class="marginalizedparent">
<a class='itemDeclLink' href='#buffer.dynamic.string-itemdecl:2'>🔗</a>
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<pre class='itemdeclcode'>dynamic_string_buffer<span class='parenthesis'>(</span>basic_string<span class='anglebracket'>&lt;</span>CharT, Traits, Allocator<span class='anglebracket'>&gt;</span><span class='operator'>&amp;</span> str,
                      size_t maximum_size<span class='parenthesis'>)</span> <span class='keyword'>noexcept</span>;
</pre>
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<span class="textit">Requires:</span><span class="texttt">str<span class="operator">.</span>size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="anglebracket">&lt;</span><span class="operator">=</span> maximum_­size</span>.
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<span class="textit">Effects:</span>Initializes <span class="texttt">str_­</span> with <span class="texttt">str</span><del >, <span class="texttt">size_­</span> with <span class="texttt">str<span class="operator">.</span>size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>,</del> and <span class="texttt">max_­size_­</span> with <span class="texttt">maximum_­size</span>.
</div>
</div>
<span class="indexparent"><a class='index' id='lib:size,dynamic_string_buffer'></a></span><span class="indexparent"><a class='index' id='lib:dynamic_string_buffer,size'></a></span>
<div id="buffer.dynamic.string-itemdecl:3" class="itemdecl">
<div class="marginalizedparent">
<a class='itemDeclLink' href='#buffer.dynamic.string-itemdecl:3'>🔗</a>
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<pre class='itemdeclcode'>size_t size<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;
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<span class="textit">Returns:</span><del ><span class="texttt">size_­</span></del><ins ><span class="texttt">min<span class="parenthesis">(</span>str_­<span class="operator">.</span>size<span class="parenthesis">(</span><span class="parenthesis">)</span>, max_­size_­<span class="parenthesis">)</span></span></ins>.
</div>
</div>
<span class="indexparent"><a class='index' id='lib:max_size,dynamic_string_buffer'></a></span><span class="indexparent"><a class='index' id='lib:dynamic_string_buffer,max_size'></a></span>
<div id="buffer.dynamic.string-itemdecl:4" class="itemdecl">
<div class="marginalizedparent">
<a class='itemDeclLink' href='#buffer.dynamic.string-itemdecl:4'>🔗</a>
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<pre class='itemdeclcode'>size_t max_size<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;
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<span class="textit">Returns:</span><span class="texttt">max_­size_­</span>.
</div>
</div>
<span class="indexparent"><a class='index' id='lib:capacity,dynamic_string_buffer'></a></span><span class="indexparent"><a class='index' id='lib:dynamic_string_buffer,capacity'></a></span>
<div id="buffer.dynamic.string-itemdecl:5" class="itemdecl">
<div class="marginalizedparent">
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<pre class='itemdeclcode'>size_t capacity<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;
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<span class="textit">Returns:</span><del ><span class="texttt">vec_­<span class="operator">.</span>capacity<span class="parenthesis">(</span><span class="parenthesis">)</span></span></del><ins ><span class="texttt">min<span class="parenthesis">(</span>str_­<span class="operator">.</span>capacity<span class="parenthesis">(</span><span class="parenthesis">)</span>, max_­size_­<span class="parenthesis">)</span></span></ins>.
</div>
</div>
<span class="indexparent"><a class='index' id='lib:data,dynamic_string_buffer'></a></span><span class="indexparent"><a class='index' id='lib:dynamic_string_buffer,data'></a></span>
<div id="buffer.dynamic.string-itemdecl:6" class="itemdecl">
<div class="marginalizedparent">
<a class='itemDeclLink' href='#buffer.dynamic.string-itemdecl:6'>🔗</a>
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<pre class='itemdeclcode'><del ><span class='texttt'>const_&shy;buffers_&shy;type data<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;</span></del>
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<del>
<span class="textit">Returns:</span><span class="texttt">buffer<span class="parenthesis">(</span>str_­, size_­<span class="parenthesis">)</span></span>.
</del>
</div>
</div>
<div id="buffer.dynamic.string-itemdecl:7" class="itemdecl">
<div class="marginalizedparent">
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<pre class='itemdeclcode'><ins ><span class='texttt'>mutable_&shy;buffers_&shy;type data<span class='parenthesis'>(</span>size_&shy;t pos, size_&shy;t n<span class='parenthesis'>)</span> <span class='keyword'>noexcept</span>;</span></ins>
<ins ><span class='texttt'>const_&shy;buffers_&shy;type data<span class='parenthesis'>(</span>size_&shy;t pos, size_&shy;t n<span class='parenthesis'>)</span> <span class='keyword'>const</span> <span class='keyword'>noexcept</span>;</span></ins>
</pre>
</div>
<div class="itemdescr">

</div>
<div class="itemdescr">
<ins>
<span class="textit">Returns:</span><span class="texttt">buffer<span class="parenthesis">(</span>buffer<span class="parenthesis">(</span>str_­, max_­size_­<span class="parenthesis">)</span> <span class="operator">+</span> pos, n<span class="parenthesis">)</span></span>.
</ins>
</div>
<span class="indexparent"><a class='index' id='lib:prepare,dynamic_string_buffer'></a></span><span class="indexparent"><a class='index' id='lib:dynamic_string_buffer,prepare'></a></span>
<div id="buffer.dynamic.string-itemdecl:8" class="itemdecl">
<div class="marginalizedparent">
<a class='itemDeclLink' href='#buffer.dynamic.string-itemdecl:8'>🔗</a>
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<pre class='itemdeclcode'><del ><span class='texttt'>mutable_&shy;buffers_&shy;type prepare<span class='parenthesis'>(</span>size_&shy;t n<span class='parenthesis'>)</span>;</span></del>
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<del>
<span class="textit">Effects:</span>Performs <span class="texttt">str_­<span class="operator">.</span>resize<span class="parenthesis">(</span>size_­ <span class="operator">+</span> n<span class="parenthesis">)</span></span>.
</del>
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<del>
<span class="textit">Returns:</span><span class="texttt">buffer<span class="parenthesis">(</span>buffer<span class="parenthesis">(</span>str_­<span class="parenthesis">)</span> <span class="operator">+</span> size_­, n<span class="parenthesis">)</span></span>.
</del>
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<div class="marginalizedparent">
<a class='marginalized' href='buffer.dynamic.string.html#13'>13</a>
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<del>
<span class="textit">Remarks:</span><span class="texttt">length_­error</span> if <span class="texttt">size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">+</span> n</span> exceeds <span class="texttt">max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>.
</del>
</div>
</div>
<span class="indexparent"><a class='index' id='lib:commit,dynamic_string_buffer'></a></span><span class="indexparent"><a class='index' id='lib:dynamic_string_buffer,commit'></a></span>
<div id="buffer.dynamic.string-itemdecl:9" class="itemdecl">
<div class="marginalizedparent">
<a class='itemDeclLink' href='#buffer.dynamic.string-itemdecl:9'>🔗</a>
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<pre class='itemdeclcode'><del ><span class='texttt'><span class='keyword'>void</span> commit<span class='parenthesis'>(</span>size_&shy;t n<span class='parenthesis'>)</span> <span class='keyword'>noexcept</span>;</span></del>
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<del>
<span class="textit">Effects:</span>Performs:
</del>
<pre class='codeblock'>
<del ><span class='tcode_in_codeblock'>size_&shy; <span class='operator'>+</span><span class='operator'>=</span> min<span class='parenthesis'>(</span>n, str_&shy;<span class='operator'>.</span>size<span class='parenthesis'>(</span><span class='parenthesis'>)</span> <span class='operator'>-</span> size_&shy;<span class='parenthesis'>)</span>;</span></del>
<del ><span class='tcode_in_codeblock'>str_&shy;<span class='operator'>.</span>resize<span class='parenthesis'>(</span>size_&shy;<span class='parenthesis'>)</span>;</span></del>
</pre>
</div>
</div>
<span class="indexparent"><a class='index' id='lib:grow,dynamic_string_buffer'></a></span><span class="indexparent"><a class='index' id='lib:dynamic_string_buffer,grow'></a></span>
<div id="buffer.dynamic.string-itemdecl:10" class="itemdecl">
<div class="marginalizedparent">
<a class='itemDeclLink' href='#buffer.dynamic.string-itemdecl:10'>🔗</a>
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<pre class='itemdeclcode'><ins ><span class='texttt'><span class='keyword'>void</span> grow<span class='parenthesis'>(</span>size_&shy;t n<span class='parenthesis'>)</span>;</span></ins>
</pre>
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<div class="itemdescr">

</div>
<div class="itemdescr">
<ins>
<span class="textit">Effects:</span>Performs <ins ><span class="texttt">str_­<span class="operator">.</span>resize<span class="parenthesis">(</span>size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">+</span> n<span class="parenthesis">)</span>;</span>
</ins>
.</ins>
</div>
<div class="itemdescr">
<ins>
<span class="textit">Throws:</span><span class="texttt">length_­error</span> if <ins ><span class="texttt">size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="anglebracket">&gt;</span> max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">|</span><span class="operator">|</span> max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">-</span> size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="anglebracket">&lt;</span> n</span>
</ins>
.</ins>
</div>
<span class="indexparent"><a class='index' id='lib:shrink,dynamic_string_buffer'></a></span><span class="indexparent"><a class='index' id='lib:dynamic_string_buffer,shrink'></a></span>
<div id="buffer.dynamic.string-itemdecl:11" class="itemdecl">
<div class="marginalizedparent">
<a class='itemDeclLink' href='#buffer.dynamic.string-itemdecl:11'>🔗</a>
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<pre class='itemdeclcode'><ins ><span class='texttt'><span class='keyword'>void</span> shrink<span class='parenthesis'>(</span>size_&shy;t n<span class='parenthesis'>)</span>;</span></ins>
</pre>
</div>
<div class="itemdescr">

</div>
<div class="itemdescr">
<ins>
<span class="textit">Effects:</span>Performs <ins ><span class="texttt">str_­<span class="operator">.</span>resize<span class="parenthesis">(</span>n <span class="anglebracket">&gt;</span> size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">?</span> <span class="literal">0</span> <span class="operator">:</span> size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">-</span> n<span class="parenthesis">)</span>;</span>
</ins>
.</ins>
</div>
<span class="indexparent"><a class='index' id='lib:consume,dynamic_string_buffer'></a></span><span class="indexparent"><a class='index' id='lib:dynamic_string_buffer,consume'></a></span>
<div id="buffer.dynamic.string-itemdecl:12" class="itemdecl">
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<pre class='itemdeclcode'><span class='keyword'>void</span> consume<span class='parenthesis'>(</span>size_t n<span class='parenthesis'>)</span>;
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<span class="textit">Effects:</span>Performs:
<pre class='codeblock'>
<del ><span class='tcode_in_codeblock'>size_&shy;t m <span class='operator'>=</span> min<span class='parenthesis'>(</span>n, size_&shy;<span class='parenthesis'>)</span>;</span></del>
<del ><span class='tcode_in_codeblock'>str_&shy;<span class='operator'>.</span>erase<span class='parenthesis'>(</span><span class='literal'>0</span>, m<span class='parenthesis'>)</span>;</span></del>
<del ><span class='tcode_in_codeblock'>size_&shy; <span class='operator'>-</span><span class='operator'>=</span> m;</span></del>
<ins ><span class='tcode_in_codeblock'>str_&shy;<span class='operator'>.</span>erase<span class='parenthesis'>(</span><span class='literal'>0</span>, min<span class='parenthesis'>(</span>n, size<span class='parenthesis'>(</span><span class='parenthesis'>)</span><span class='parenthesis'>)</span><span class='parenthesis'>)</span>;</span></ins>
</pre>
</div>
</div>
</div>
<p><em>Modify the <code>read</code> function [buffer.read] as follows:</em></p>
<div class="wording">
<h2>
<a class='secnum' style='min-width:88pt'>17.5</a> Synchronous read operations <a class='abbr_ref' href='#'>[buffer.read]</a>
</h2>
</div>
<em>[…]</em>
<div class="wording">
<div id="buffer.read-itemdecl:2" class="itemdecl">
<div class="marginalizedparent">
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<pre class='itemdeclcode'><span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncReadStream, <span class='keyword'>class</span> DynamicBuffer<span class='anglebracket'>&gt;</span>
  size_t read<span class='parenthesis'>(</span>SyncReadStream<span class='operator'>&amp;</span> stream, DynamicBuffer<del ><span class='texttt'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b<span class='parenthesis'>)</span>;
<span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncReadStream, <span class='keyword'>class</span> DynamicBuffer<span class='anglebracket'>&gt;</span>
  size_t read<span class='parenthesis'>(</span>SyncReadStream<span class='operator'>&amp;</span> stream, DynamicBuffer<del ><span class='texttt'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b, error_code<span class='operator'>&amp;</span> ec<span class='parenthesis'>)</span>;
<span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncReadStream, <span class='keyword'>class</span> DynamicBuffer,
  <span class='keyword'>class</span> CompletionCondition<span class='anglebracket'>&gt;</span>
    size_t read<span class='parenthesis'>(</span>SyncReadStream<span class='operator'>&amp;</span> stream, DynamicBuffer<del ><span class='texttt'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b,
                CompletionCondition completion_condition<span class='parenthesis'>)</span>;
<span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncReadStream, <span class='keyword'>class</span> DynamicBuffer,
  <span class='keyword'>class</span> CompletionCondition<span class='anglebracket'>&gt;</span>
    size_t read<span class='parenthesis'>(</span>SyncReadStream<span class='operator'>&amp;</span> stream, DynamicBuffer<del ><span class='texttt'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b,
                CompletionCondition completion_condition,
                error_code<span class='operator'>&amp;</span> ec<span class='parenthesis'>)</span>;
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<a class='marginalized' href='buffer.read.html#8'>8</a>
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<span class="textit">Effects:</span>Clears <span class="texttt">ec</span>, then reads data from the synchronous read stream (<a href='#buffer.stream.reqmts.syncreadstream'>[buffer.stream.reqmts.syncreadstream]</a>) object <span class="texttt">stream</span> by performing zero or more calls to the stream’s <span class="texttt">read_­some</span> member function.
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<div class="para">
<div class="marginalizedparent">
<a class='marginalized' href='buffer.read.html#9'>9</a>
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Data is placed into the dynamic buffer (<a href='#buffer.reqmts.dynamicbuffer'>[buffer.reqmts.dynamicbuffer]</a>) object <span class="texttt">b</span>. A mutable buffer sequence (<a href='#buffer.reqmts.mutablebuffersequence'>[buffer.reqmts.mutablebuffersequence]</a>) <ins ><span class="texttt">x</span> </ins>is obtained prior to each <span class="texttt">read_­some</span> call <del >using <span class="texttt">b<span class="operator">.</span>prepare<span class="parenthesis">(</span>N<span class="parenthesis">)</span></span>,</del><ins >by performing:</ins>
<pre class='codeblock'>
<ins ><span class='tcode_in_codeblock'><span class='keyword'>auto</span> orig_&shy;size <span class='operator'>=</span> b<span class='operator'>.</span>size<span class='parenthesis'>(</span><span class='parenthesis'>)</span>;</span></ins>
<ins ><span class='tcode_in_codeblock'>b<span class='operator'>.</span>grow<span class='parenthesis'>(</span>N<span class='parenthesis'>)</span>;</span></ins>
<ins ><span class='tcode_in_codeblock'><span class='keyword'>auto</span> x <span class='operator'>=</span> b<span class='operator'>.</span>data<span class='parenthesis'>(</span>orig_&shy;size, N<span class='parenthesis'>)</span>;</span></ins>
</pre>
where <span class="texttt">N</span> is an unspecified value less than or equal to <span class="texttt">b<span class="operator">.</span>max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">-</span> b<span class="operator">.</span>size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>.
<div id="buffer.read-9.note-1" class="note">
[ <a class='note_link' href='#buffer.read-9.note-1'><span class="textit">Note</span></a>
<div class="noteBody">
<span class="textit">:</span> Implementations can use <span class="texttt">b<span class="operator">.</span>capacity<span class="parenthesis">(</span><span class="parenthesis">)</span></span> when determining <span class="texttt">N</span>, to minimize the number of <span class="texttt">read_­some</span> calls performed on the stream. — <i>end note</i>
</div>
 ]
</div>
After each <span class="texttt">read_­some</span> call, the implementation performs <del ><span class="texttt">b<span class="operator">.</span>commit<span class="parenthesis">(</span>n<span class="parenthesis">)</span></span></del><ins ><span class="texttt">b<span class="operator">.</span>shrink<span class="parenthesis">(</span>N <span class="operator">-</span> n<span class="parenthesis">)</span></span></ins>, where <span class="texttt">n</span> is the return value from <span class="texttt">read_­some</span>.
</div>
</div>
</div>
<p><em>Modify the <code>async_read</code> function [buffer.async.read] as follows:</em></p>
<div class="wording">
<h2>
<a class='secnum' style='min-width:88pt'>17.6</a> Asynchronous read operations <a class='abbr_ref' href='#'>[buffer.async.read]</a>
</h2>
</div>
<em>[…]</em>
<div class="wording">
<div id="buffer.async.read-itemdecl:2" class="itemdecl">
<div class="marginalizedparent">
<a class='itemDeclLink' href='#buffer.async.read-itemdecl:2'>🔗</a>
</div>
<pre class='itemdeclcode'><span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> AsyncReadStream, <span class='keyword'>class</span> DynamicBuffer, <span class='keyword'>class</span> CompletionToken<span class='anglebracket'>&gt;</span>
    <span class='textit'><span class='texttt'>DEDUCED</span></span> async_read<span class='parenthesis'>(</span>AsyncReadStream<span class='operator'>&amp;</span> stream,
                       DynamicBuffer<del ><span class='texttt'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b, CompletionToken<span class='operator'>&amp;</span><span class='operator'>&amp;</span> token<span class='parenthesis'>)</span>;
<span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> AsyncReadStream, <span class='keyword'>class</span> DynamicBuffer, <span class='keyword'>class</span> CompletionCondition,
         <span class='keyword'>class</span> CompletionToken<span class='anglebracket'>&gt;</span>
    <span class='textit'><span class='texttt'>DEDUCED</span></span> async_read<span class='parenthesis'>(</span>AsyncReadStream<span class='operator'>&amp;</span> stream,
                       DynamicBuffer<del ><span class='texttt'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b,
                       CompletionCondition completion_condition,
                       CompletionToken<span class='operator'>&amp;</span><span class='operator'>&amp;</span> token<span class='parenthesis'>)</span>;
</pre>
</div>
<div class="itemdescr">

</div>
<div class="para">
<div class="marginalizedparent">
<a class='marginalized' href='buffer.async.read.html#9'>9</a>
</div>
<div class="itemdescr">
<div class="sourceLinkParent">
<a class='sourceLink' href='#'>#</a>
</div>
<span class="textit">Completion signature:</span><span class="texttt"><span class="keyword">void</span><span class="parenthesis">(</span>error_­code ec, size_­t n<span class="parenthesis">)</span></span>.
</div>
</div>
<div class="para">
<div class="marginalizedparent">
<a class='marginalized' href='buffer.async.read.html#10'>10</a>
</div>
<div class="itemdescr">
<div class="sourceLinkParent">
<a class='sourceLink' href='#'>#</a>
</div>
<span class="textit">Effects:</span>Initiates an asynchronous operation to read data from the buffer-oriented asynchronous read stream (<a href='#buffer.stream.reqmts.asyncreadstream'>[buffer.stream.reqmts.asyncreadstream]</a>) object <span class="texttt">stream</span> by performing one or more asynchronous read_some operations on the stream.
</div>
</div>
<div class="para">
<div class="marginalizedparent">
<a class='marginalized' href='buffer.async.read.html#11'>11</a>
</div>
<div class="itemdescr">
<div class="sourceLinkParent">
<a class='sourceLink' href='#'>#</a>
</div>
Data is placed into the dynamic buffer (<a href='#buffer.reqmts.dynamicbuffer'>[buffer.reqmts.dynamicbuffer]</a>) object <span class="texttt">b</span>. A mutable buffer sequence (<a href='#buffer.reqmts.mutablebuffersequence'>[buffer.reqmts.mutablebuffersequence]</a>) <ins ><span class="texttt">x</span> </ins>is obtained prior to each <span class="texttt">async_­read_­some</span> call <del >using <span class="texttt">b<span class="operator">.</span>prepare<span class="parenthesis">(</span>N<span class="parenthesis">)</span></span>,</del><ins >by performing:</ins>
<pre class='codeblock'>
<ins ><span class='tcode_in_codeblock'><span class='keyword'>auto</span> orig_&shy;size <span class='operator'>=</span> b<span class='operator'>.</span>size<span class='parenthesis'>(</span><span class='parenthesis'>)</span>;</span></ins>
<ins ><span class='tcode_in_codeblock'>b<span class='operator'>.</span>grow<span class='parenthesis'>(</span>N<span class='parenthesis'>)</span>;</span></ins>
<ins ><span class='tcode_in_codeblock'><span class='keyword'>auto</span> x <span class='operator'>=</span> b<span class='operator'>.</span>data<span class='parenthesis'>(</span>orig_&shy;size, N<span class='parenthesis'>)</span>;</span></ins>
</pre>
where <span class="texttt">N</span> is an unspecified value such that <span class="texttt">N</span> is less than or equal to <span class="texttt">b<span class="operator">.</span>max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">-</span> b<span class="operator">.</span>size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>.
<div id="buffer.async.read-11.note-1" class="note">
[ <a class='note_link' href='#buffer.async.read-11.note-1'><span class="textit">Note</span></a>
<div class="noteBody">
<span class="textit">:</span> Implementations can use <span class="texttt">b<span class="operator">.</span>capacity<span class="parenthesis">(</span><span class="parenthesis">)</span></span> when determining <span class="texttt">N</span>, to minimize the number of asynchronous read_some operations performed on the stream. — <i>end note</i>
</div>
 ]
</div>
After the completion of each asynchronous read_some operation, the implementation performs <del ><span class="texttt">b<span class="operator">.</span>commit<span class="parenthesis">(</span>n<span class="parenthesis">)</span></span></del><ins ><span class="texttt">b<span class="operator">.</span>shrink<span class="parenthesis">(</span>N <span class="operator">-</span> n<span class="parenthesis">)</span></span></ins>, where <span class="texttt">n</span> is the value passed to the asynchronous read_some operation’s completion handler.
</div>
</div>
</div>
<p><em>Modify the <code>write</code> function [buffer.write] as follows:</em></p>
<div class="wording">
<h2>
<a class='secnum' style='min-width:88pt'>17.7</a> Synchronous write operations <a class='abbr_ref' href='#'>[buffer.write]</a>
</h2>
</div>
<em>[…]</em>
<div class="wording">
<div id="buffer.write-itemdecl:2" class="itemdecl">
<div class="marginalizedparent">
<a class='itemDeclLink' href='#buffer.write-itemdecl:2'>🔗</a>
</div>
<pre class='itemdeclcode'><span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncWriteStream, <span class='keyword'>class</span> DynamicBuffer<span class='anglebracket'>&gt;</span>
  size_t write<span class='parenthesis'>(</span>SyncWriteStream<span class='operator'>&amp;</span> stream, DynamicBuffer<del ><span class='texttt'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b<span class='parenthesis'>)</span>;
<span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncWriteStream, <span class='keyword'>class</span> DynamicBuffer<span class='anglebracket'>&gt;</span>
  size_t write<span class='parenthesis'>(</span>SyncWriteStream<span class='operator'>&amp;</span> stream, DynamicBuffer<del ><span class='texttt'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b, error_code<span class='operator'>&amp;</span> ec<span class='parenthesis'>)</span>;
<span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncWriteStream, <span class='keyword'>class</span> DynamicBuffer, <span class='keyword'>class</span> CompletionCondition<span class='anglebracket'>&gt;</span>
  size_t write<span class='parenthesis'>(</span>SyncWriteStream<span class='operator'>&amp;</span> stream, DynamicBuffer<del ><span class='texttt'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b,
               CompletionCondition completion_condition<span class='parenthesis'>)</span>;
<span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncWriteStream, <span class='keyword'>class</span> DynamicBuffer, <span class='keyword'>class</span> CompletionCondition<span class='anglebracket'>&gt;</span>
  size_t write<span class='parenthesis'>(</span>SyncWriteStream<span class='operator'>&amp;</span> stream, DynamicBuffer<del ><span class='texttt'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b,
               CompletionCondition completion_condition,
               error_code<span class='operator'>&amp;</span> ec<span class='parenthesis'>)</span>;
</pre>
</div>
</div>
<p><em>Modify the <code>async_write</code> function [buffer.async.write] as follows:</em></p>
<div class="wording">
<h2>
<a class='secnum' style='min-width:88pt'>17.8</a> Asynchronous write operations <a class='abbr_ref' href='#'>[buffer.async.write]</a>
</h2>
</div>
<em>[…]</em>
<div class="wording">
<div id="buffer.async.write-itemdecl:2" class="itemdecl">
<div class="marginalizedparent">
<a class='itemDeclLink' href='#buffer.async.write-itemdecl:2'>🔗</a>
</div>
<pre class='itemdeclcode'><span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> AsyncWriteStream, <span class='keyword'>class</span> DynamicBuffer, <span class='keyword'>class</span> CompletionToken<span class='anglebracket'>&gt;</span>
  <span class='textit'><span class='texttt'>DEDUCED</span></span> async_write<span class='parenthesis'>(</span>AsyncWriteStream<span class='operator'>&amp;</span> stream,
                      DynamicBuffer<del ><span class='texttt'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b, CompletionToken<span class='operator'>&amp;</span><span class='operator'>&amp;</span> token<span class='parenthesis'>)</span>;
<span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> AsyncWriteStream, <span class='keyword'>class</span> DynamicBuffer, <span class='keyword'>class</span> CompletionCondition,
         <span class='keyword'>class</span> CompletionToken<span class='anglebracket'>&gt;</span>
    <span class='textit'><span class='texttt'>DEDUCED</span></span> async_write<span class='parenthesis'>(</span>AsyncWriteStream<span class='operator'>&amp;</span> stream,
                        DynamicBuffer<del ><span class='texttt'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b,
                        CompletionCondition completion_condition,
                        CompletionToken<span class='operator'>&amp;</span><span class='operator'>&amp;</span> token<span class='parenthesis'>)</span>;
</pre>
</div>
</div>
<p><em>Modify the <code>read_until</code> function [buffer.read.until] as follows:</em></p>
<div class="wording">
<h2>
<a class='secnum' style='min-width:88pt'>17.9</a> Synchronous delimited read operations <a class='abbr_ref' href='#'>[buffer.read.until]</a>
</h2>
<span class="indexparent"><a class='index' id='lib:read_until'></a></span>
<div id="buffer.read.until-itemdecl:1" class="itemdecl">
<div class="marginalizedparent">
<a class='itemDeclLink' href='#buffer.read.until-itemdecl:1'>🔗</a>
</div>
<pre class='itemdeclcode'><span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncReadStream, <span class='keyword'>class</span> DynamicBuffer<span class='anglebracket'>&gt;</span>
  size_t read_until<span class='parenthesis'>(</span>SyncReadStream<span class='operator'>&amp;</span> s, DynamicBuffer<del ><span class='texttt'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b, <span class='keyword'>char</span> delim<span class='parenthesis'>)</span>;
<span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncReadStream, <span class='keyword'>class</span> DynamicBuffer<span class='anglebracket'>&gt;</span>
  size_t read_until<span class='parenthesis'>(</span>SyncReadStream<span class='operator'>&amp;</span> s, DynamicBuffer<del ><span class='texttt'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b,
                    <span class='keyword'>char</span> delim, error_code<span class='operator'>&amp;</span> ec<span class='parenthesis'>)</span>;
<span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncReadStream, <span class='keyword'>class</span> DynamicBuffer<span class='anglebracket'>&gt;</span>
  size_t read_until<span class='parenthesis'>(</span>SyncReadStream<span class='operator'>&amp;</span> s, DynamicBuffer<del ><span class='texttt'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b, string_view delim<span class='parenthesis'>)</span>;
<span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> SyncReadStream, <span class='keyword'>class</span> DynamicBuffer<span class='anglebracket'>&gt;</span>
  size_t read_until<span class='parenthesis'>(</span>SyncReadStream<span class='operator'>&amp;</span> s, DynamicBuffer<del ><span class='texttt'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b,
                    string_view delim, error_code<span class='operator'>&amp;</span> ec<span class='parenthesis'>)</span>;
</pre>
</div>
<div class="itemdescr">

</div>
<div class="para">
<div class="marginalizedparent">
<a class='marginalized' href='buffer.read.until.html#1'>1</a>
</div>
<div class="itemdescr">
<div class="sourceLinkParent">
<a class='sourceLink' href='#'>#</a>
</div>
<span class="textit">Effects:</span>Reads data from the buffer-oriented synchronous read stream (<a href='#buffer.stream.reqmts.syncreadstream'>[buffer.stream.reqmts.syncreadstream]</a>) object <span class="texttt">stream</span> by performing zero or more calls to the stream’s <span class="texttt">read_­some</span> member function, until <del >the readable bytes of </del>the dynamic buffer (<a href='#buffer.reqmts.dynamicbuffer'>[buffer.reqmts.dynamicbuffer]</a>) object <span class="texttt">b</span> contains the specified delimiter <span class="texttt">delim</span>.
</div>
</div>
<div class="para">
<div class="marginalizedparent">
<a class='marginalized' href='buffer.read.until.html#2'>2</a>
</div>
<div class="itemdescr">
<div class="sourceLinkParent">
<a class='sourceLink' href='#'>#</a>
</div>
Data is placed into the dynamic buffer object <span class="texttt">b</span>. A mutable buffer sequence (<a href='#buffer.reqmts.mutablebuffersequence'>[buffer.reqmts.mutablebuffersequence]</a>) <ins ><span class="texttt">x</span> </ins>is obtained prior to each <span class="texttt">read_­some</span> call <del >using <span class="texttt">b<span class="operator">.</span>prepare<span class="parenthesis">(</span>N<span class="parenthesis">)</span></span>,</del><ins >by performing:</ins>
<pre class='codeblock'>
<ins ><span class='tcode_in_codeblock'><span class='keyword'>auto</span> orig_&shy;size <span class='operator'>=</span> b<span class='operator'>.</span>size<span class='parenthesis'>(</span><span class='parenthesis'>)</span>;</span></ins>
<ins ><span class='tcode_in_codeblock'>b<span class='operator'>.</span>grow<span class='parenthesis'>(</span>N<span class='parenthesis'>)</span>;</span></ins>
<ins ><span class='tcode_in_codeblock'><span class='keyword'>auto</span> x <span class='operator'>=</span> b<span class='operator'>.</span>data<span class='parenthesis'>(</span>orig_&shy;size, N<span class='parenthesis'>)</span>;</span></ins>
</pre>
where <span class="texttt">N</span> is an unspecified value such that <span class="texttt">N <span class="anglebracket">&lt;</span><span class="operator">=</span> max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">-</span> size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>.
<div id="buffer.read.until-2.note-1" class="note">
[ <a class='note_link' href='#buffer.read.until-2.note-1'><span class="textit">Note</span></a>
<div class="noteBody">
<span class="textit">:</span> Implementations can use <span class="texttt">b<span class="operator">.</span>capacity<span class="parenthesis">(</span><span class="parenthesis">)</span></span> when determining <span class="texttt">N</span>, to minimize the number of <span class="texttt">read_­some</span> calls performed on the stream. — <i>end note</i>
</div>
 ]
</div>
After each <span class="texttt">read_­some</span> call, the implementation performs <del ><span class="texttt">b<span class="operator">.</span>commit<span class="parenthesis">(</span>n<span class="parenthesis">)</span></span></del><ins ><span class="texttt">b<span class="operator">.</span>shrink<span class="parenthesis">(</span>N <span class="operator">-</span> n<span class="parenthesis">)</span></span></ins>, where <span class="texttt">n</span> is the return value from <span class="texttt">read_­some</span>.
</div>
</div>
<div class="para">
<div class="marginalizedparent">
<a class='marginalized' href='buffer.read.until.html#3'>3</a>
</div>
<div class="itemdescr">
<div class="sourceLinkParent">
<a class='sourceLink' href='#'>#</a>
</div>
The synchronous read_until operation continues until:
<ul class="itemize">
<li id="buffer.read.until-3.1">
<div class="marginalizedparent" style="left:-10em">
<a class='marginalized' href='#buffer.read.until-3.1'>(3.1)</a>
</div>
<del>
the readable bytes of
</del>
<span class="texttt">b</span> contains the delimiter <span class="texttt">delim</span>; or
</li>
<li id="buffer.read.until-3.2">
<div class="marginalizedparent" style="left:-10em">
<a class='marginalized' href='#buffer.read.until-3.2'>(3.2)</a>
</div>
<span class="texttt">b<span class="operator">.</span>size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">=</span><span class="operator">=</span> b<span class="operator">.</span>max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>; or
</li>
<li id="buffer.read.until-3.3">
<div class="marginalizedparent" style="left:-10em">
<a class='marginalized' href='#buffer.read.until-3.3'>(3.3)</a>
</div>
an asynchronous read_some operation fails.
</li>
</ul>
</div>
</div>
<div class="para">
<div class="marginalizedparent">
<a class='marginalized' href='buffer.read.until.html#4'>4</a>
</div>
<div class="itemdescr">
<div class="sourceLinkParent">
<a class='sourceLink' href='#'>#</a>
</div>
On exit, if <del >the readable bytes of </del>tcodeb contains the delimiter, <span class="texttt">ec</span> is set such that <span class="texttt"><span class="operator">!</span>ec</span> is <span class="texttt"><span class="literal">true</span></span>. Otherwise, if <span class="texttt">b<span class="operator">.</span>size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">=</span><span class="operator">=</span> b<span class="operator">.</span>max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>, <span class="texttt">ec</span> is set such that <span class="texttt">ec <span class="operator">=</span><span class="operator">=</span> stream_­errc<span class="operator">​::​</span>not_­found</span>. If <span class="texttt">b<span class="operator">.</span>size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="anglebracket">&lt;</span> b<span class="operator">.</span>max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>, <span class="texttt">ec</span> contains the <span class="texttt">error_­code</span> from the most recent <span class="texttt">read_­some</span> call.
</div>
</div>
<div class="para">
<div class="marginalizedparent">
<a class='marginalized' href='buffer.read.until.html#5'>5</a>
</div>
<div class="itemdescr">
<div class="sourceLinkParent">
<a class='sourceLink' href='#'>#</a>
</div>
<span class="textit">Returns:</span>The number of bytes in <del >the readable bytes of </del><span class="texttt">b</span> up to and including the delimiter, if present.
<div id="buffer.read.until-5.note-1" class="note">
[ <a class='note_link' href='#buffer.read.until-5.note-1'><span class="textit">Note</span></a>
<div class="noteBody">
<span class="textit">:</span> On completion, the buffer can contain additional bytes following the delimiter. — <i>end note</i>
</div>
 ]
</div>
Otherwise returns <span class="texttt"><span class="literal">0</span></span>.
</div>
</div>
</div>
<p><em>Modify the <code>async_read_until</code> function [buffer.async.read.until] as follows:</em></p>
<div class="wording">
<h2>
<a class='secnum' style='min-width:88pt'>17.10</a> Asynchronous delimited read operations <a class='abbr_ref' href='#'>[buffer.async.read.until]</a>
</h2>
<span class="indexparent"><a class='index' id='lib:async_read_until'></a></span>
<div id="buffer.async.read.until-itemdecl:1" class="itemdecl">
<div class="marginalizedparent">
<a class='itemDeclLink' href='#buffer.async.read.until-itemdecl:1'>🔗</a>
</div>
<pre class='itemdeclcode'><span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> AsyncReadStream, <span class='keyword'>class</span> DynamicBuffer, <span class='keyword'>class</span> CompletionToken<span class='anglebracket'>&gt;</span>
  <span class='textit'><span class='texttt'>DEDUCED</span></span> async_read_until<span class='parenthesis'>(</span>AsyncReadStream<span class='operator'>&amp;</span> s,
                           DynamicBuffer<del ><span class='texttt'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b, <span class='keyword'>char</span> delim,
                           CompletionToken<span class='operator'>&amp;</span><span class='operator'>&amp;</span> token<span class='parenthesis'>)</span>;
<span class='keyword'>template</span><span class='anglebracket'>&lt;</span><span class='keyword'>class</span> AsyncReadStream, <span class='keyword'>class</span> DynamicBuffer, <span class='keyword'>class</span> CompletionToken<span class='anglebracket'>&gt;</span>
  <span class='textit'><span class='texttt'>DEDUCED</span></span> async_read_until<span class='parenthesis'>(</span>AsyncReadStream<span class='operator'>&amp;</span> s,
                           DynamicBuffer<del ><span class='texttt'><span class='operator'>&amp;</span><span class='operator'>&amp;</span></span></del> b, string_view delim,
                           CompletionToken<span class='operator'>&amp;</span><span class='operator'>&amp;</span> token<span class='parenthesis'>)</span>;
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<a class='marginalized' href='buffer.async.read.until.html#1'>1</a>
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A composed asynchronous operation (<a href='#async.reqmts.async.composed'>[async.reqmts.async.composed]</a>).
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<a class='marginalized' href='buffer.async.read.until.html#2'>2</a>
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<span class="textit">Completion signature:</span><span class="texttt"><span class="keyword">void</span><span class="parenthesis">(</span>error_­code ec, size_­t n<span class="parenthesis">)</span></span>.
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<a class='marginalized' href='buffer.async.read.until.html#3'>3</a>
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<span class="textit">Effects:</span>Initiates an asynchronous operation to read data from the buffer-oriented asynchronous read stream (<a href='#buffer.stream.reqmts.asyncreadstream'>[buffer.stream.reqmts.asyncreadstream]</a>) object <span class="texttt">stream</span> by performing zero or more asynchronous read_some operations on the stream, until <del >the readable bytes of </del>the dynamic buffer (<a href='#buffer.reqmts.dynamicbuffer'>[buffer.reqmts.dynamicbuffer]</a>) object <span class="texttt">b</span> contain<ins >s</ins> the specified delimiter <span class="texttt">delim</span>.
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<a class='marginalized' href='buffer.async.read.until.html#4'>4</a>
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Data is placed into the dynamic buffer object <span class="texttt">b</span>. A mutable buffer sequence (<a href='#buffer.reqmts.mutablebuffersequence'>[buffer.reqmts.mutablebuffersequence]</a>) <ins ><span class="texttt">x</span> </ins>is obtained prior to each <span class="texttt">async_­read_­some</span> call <del >using <span class="texttt">b<span class="operator">.</span>prepare<span class="parenthesis">(</span>N<span class="parenthesis">)</span></span>,</del><ins >by performing:</ins>
<pre class='codeblock'>
<ins ><span class='tcode_in_codeblock'><span class='keyword'>auto</span> orig_&shy;size <span class='operator'>=</span> b<span class='operator'>.</span>size<span class='parenthesis'>(</span><span class='parenthesis'>)</span>;</span></ins>
<ins ><span class='tcode_in_codeblock'>b<span class='operator'>.</span>grow<span class='parenthesis'>(</span>N<span class='parenthesis'>)</span>;</span></ins>
<ins ><span class='tcode_in_codeblock'><span class='keyword'>auto</span> x <span class='operator'>=</span> b<span class='operator'>.</span>data<span class='parenthesis'>(</span>orig_&shy;size, N<span class='parenthesis'>)</span>;</span></ins>
</pre>
where <span class="texttt">N</span> is an unspecified value such that <span class="texttt">N <span class="anglebracket">&lt;</span><span class="operator">=</span> max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">-</span> size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>.
<div id="buffer.async.read.until-4.note-1" class="note">
[ <a class='note_link' href='#buffer.async.read.until-4.note-1'><span class="textit">Note</span></a>
<div class="noteBody">
<span class="textit">:</span> Implementations can use <span class="texttt">b<span class="operator">.</span>capacity<span class="parenthesis">(</span><span class="parenthesis">)</span></span> when determining <span class="texttt">N</span>, to minimize the number of asynchronous read_some operations performed on the stream. — <i>end note</i>
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 ]
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After the completion of each asynchronous read_some operation, the implementation performs <del ><span class="texttt">b<span class="operator">.</span>commit<span class="parenthesis">(</span>n<span class="parenthesis">)</span></span></del><ins ><span class="texttt">b<span class="operator">.</span>shrink<span class="parenthesis">(</span>N <span class="operator">-</span> n<span class="parenthesis">)</span></span></ins>, where <span class="texttt">n</span> is the value passed to the asynchronous read_some operation’s completion handler.
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<a class='marginalized' href='buffer.async.read.until.html#5'>5</a>
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The asynchronous read_until operation continues until:
<ul class="itemize">
<li id="buffer.async.read.until-5.1">
<div class="marginalizedparent" style="left:-10em">
<a class='marginalized' href='#buffer.async.read.until-5.1'>(5.1)</a>
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<del>
the readable bytes of
</del>
<span class="texttt">b</span> contain<ins >s</ins> the delimiter <span class="texttt">delim</span>; or
</li>
<li id="buffer.async.read.until-5.2">
<div class="marginalizedparent" style="left:-10em">
<a class='marginalized' href='#buffer.async.read.until-5.2'>(5.2)</a>
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<span class="texttt">b<span class="operator">.</span>size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">=</span><span class="operator">=</span> b<span class="operator">.</span>max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>; or
</li>
<li id="buffer.async.read.until-5.3">
<div class="marginalizedparent" style="left:-10em">
<a class='marginalized' href='#buffer.async.read.until-5.3'>(5.3)</a>
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an asynchronous read_some operation fails.
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<a class='marginalized' href='buffer.async.read.until.html#6'>6</a>
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The program shall ensure the <span class="texttt">AsyncReadStream</span> object <span class="texttt">stream</span> is valid until the completion handler for the asynchronous operation is invoked.
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<a class='marginalized' href='buffer.async.read.until.html#7'>7</a>
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If <span class="texttt">delim</span> is of type <span class="texttt">string_­view</span>, the implementation copies the underlying sequence of characters prior to initiating an asynchronous read_some operation on the stream.
<div id="buffer.async.read.until-7.note-1" class="note">
[ <a class='note_link' href='#buffer.async.read.until-7.note-1'><span class="textit">Note</span></a>
<div class="noteBody">
<span class="textit">:</span> This means that the caller is not required to guarantee the validity of the delimiter string after the call to <span class="texttt">async_­read_­until</span> returns. — <i>end note</i>
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<a class='marginalized' href='buffer.async.read.until.html#8'>8</a>
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On completion of the asynchronous operation, if <del >the readable bytes of </del><span class="texttt">b</span> contain<ins >s</ins> the delimiter, <span class="texttt">ec</span> is set such that <span class="texttt"><span class="operator">!</span>ec</span> is <span class="texttt"><span class="literal">true</span></span>. Otherwise, if <span class="texttt">b<span class="operator">.</span>size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="operator">=</span><span class="operator">=</span> b<span class="operator">.</span>max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>, <span class="texttt">ec</span> is set such that <span class="texttt">ec <span class="operator">=</span><span class="operator">=</span> stream_­errc<span class="operator">​::​</span>not_­found</span>. If <span class="texttt">b<span class="operator">.</span>size<span class="parenthesis">(</span><span class="parenthesis">)</span> <span class="anglebracket">&lt;</span> b<span class="operator">.</span>max_­size<span class="parenthesis">(</span><span class="parenthesis">)</span></span>, <span class="texttt">ec</span> is the <span class="texttt">error_­code</span> from the most recent asynchronous read_some operation. <span class="texttt">n</span> is the number of readable bytes in <span class="texttt">b</span> up to and including the delimiter, if present, otherwise <span class="texttt"><span class="literal">0</span></span>.
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<h2 id="history">History</h2>
<ul>
<li>2020-01-13: R1: Added detailed wording.</li>
<li>Belfast 2019-11, SG4: Consensus to forward a revision with wording to LEWG.</li>
<li>Cologne 2019-07, LEWGI: Consensus to forward to LEWG.</li>
<li>2019-09-16, R0: Initial revision.</li>
</ul>
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