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<h1 class="title">constexpr reflexpr</h1>
<p class="subtitle"><ul>
<li>Document number: <strong>P0953R1</strong>, ISO/IEC JTC1 SC22 WG21</li>
<li>Date: 2018-10-07</li>
<li>Authors: Matúš Chochlík &lt;chochlik@gmail.com&gt;, Axel Naumann &lt;axel@cern.ch&gt;, David Sankel &lt;dsankel@bloomberg.net&gt;, and Andrew Sutton &lt;asutton@uakron.edu&gt;</li>
<li>Audience: SG7 Reflection</li>
</ul>
<h2 id="contents">Contents</h2></p>
</header>
<nav id="TOC">
<ul>
<li><a href="#abstract">Abstract</a></li>
<li><a href="#changes">Changes</a></li>
<li><a href="#introduction">Introduction</a><ul>
<li><a href="#from-tmp-reflexpr-to-cxp-reflexpr">From TMP-reflexpr to CXP-reflexpr</a></li>
<li><a href="#mix-compile-time-reflection-with-runtime-values">Mix compile-time reflection with runtime values</a></li>
</ul></li>
<li><a href="#supporting-language-constructs">Supporting language constructs</a><ul>
<li><a href="#constexpr-for"><code>constexpr for</code></a></li>
<li><a href="#constexpr-time-allocators">constexpr-time allocators</a></li>
<li><a href="#unreflexpr"><code>unreflexpr</code></a></li>
</ul></li>
<li><a href="#library-considerations">Library considerations</a><ul>
<li><a href="#typeful-reflection">Typeful reflection</a></li>
<li><a href="#references-vs.pointers">References vs. pointers</a></li>
<li><a href="#downcasting">Downcasting</a></li>
<li><a href="#type_traits">type_traits</a></li>
</ul></li>
<li><a href="#library-design-alternative">Library Design Alternative</a></li>
<li><a href="#datatypes-and-operations">Datatypes and Operations</a><ul>
<li><a href="#classes">Classes</a></li>
<li><a href="#reflexpr"><code>reflexpr</code></a></li>
<li><a href="#unreflexpr-1"><code>unreflexpr</code></a></li>
</ul></li>
<li><a href="#conclusion">Conclusion</a></li>
<li><a href="#acknowledgments">Acknowledgments</a></li>
</ul>
</nav>
<h2 id="abstract">Abstract</h2>
<table>
<tr>
<td>
<strong>Before</strong>
</td>
<td>
<strong>After</strong>
</td>
</tr>
<tr>
<td>
<div class="sourceCode" id="cb1"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="kw">template</span> &lt;<span class="kw">typename</span> T&gt;</a>
<a class="sourceLine" id="cb1-2" data-line-number="2">T min(<span class="at">const</span> T&amp; a, <span class="at">const</span> T&amp; b) {</a>
<a class="sourceLine" id="cb1-3" data-line-number="3">  <span class="kw">using</span> MetaT = reflexpr(T);</a>
<a class="sourceLine" id="cb1-4" data-line-number="4">  log() &lt;&lt; <span class="st">&quot;min&lt;&quot;</span></a>
<a class="sourceLine" id="cb1-5" data-line-number="5">        &lt;&lt; get_display_name_v&lt;MetaT&gt;</a>
<a class="sourceLine" id="cb1-6" data-line-number="6">        &lt;&lt; <span class="st">&quot;&gt;(&quot;</span> &lt;&lt; a &lt;&lt; <span class="st">&quot;, &quot;</span> &lt;&lt; b &lt;&lt; <span class="st">&quot;) = &quot;</span>;</a>
<a class="sourceLine" id="cb1-7" data-line-number="7">  T result = a &lt; b ? a : b;</a>
<a class="sourceLine" id="cb1-8" data-line-number="8">  log() &lt;&lt; result &lt;&lt; <span class="bu">std::</span>endl;</a>
<a class="sourceLine" id="cb1-9" data-line-number="9">  <span class="cf">return</span> result;</a>
<a class="sourceLine" id="cb1-10" data-line-number="10">}</a></code></pre></div>
</td>
<td>
<div class="sourceCode" id="cb2"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb2-1" data-line-number="1"><span class="kw">template</span> &lt;<span class="kw">typename</span> T&gt;</a>
<a class="sourceLine" id="cb2-2" data-line-number="2">T min(<span class="at">const</span> T&amp; a, <span class="at">const</span> T&amp; b) {</a>
<a class="sourceLine" id="cb2-3" data-line-number="3">  <span class="kw">constexpr</span> reflect::Type <span class="at">const</span> * metaT = reflexpr(T);</a>
<a class="sourceLine" id="cb2-4" data-line-number="4">  log() &lt;&lt; <span class="st">&quot;min&lt;&quot;</span></a>
<a class="sourceLine" id="cb2-5" data-line-number="5">        &lt;&lt; metaT-&gt;get_display_name()</a>
<a class="sourceLine" id="cb2-6" data-line-number="6">        &lt;&lt; <span class="st">&quot;&gt;(&quot;</span> &lt;&lt; a &lt;&lt; <span class="st">&quot;, &quot;</span> &lt;&lt; b &lt;&lt; <span class="st">&quot;) = &quot;</span>;</a>
<a class="sourceLine" id="cb2-7" data-line-number="7">  T result = a &lt; b ? a : b;</a>
<a class="sourceLine" id="cb2-8" data-line-number="8">  log() &lt;&lt; result &lt;&lt; <span class="bu">std::</span>endl;</a>
<a class="sourceLine" id="cb2-9" data-line-number="9">  <span class="cf">return</span> result;</a>
<a class="sourceLine" id="cb2-10" data-line-number="10">}</a></code></pre></div>
</td>
</tr>
</table>
<p>The reflection TS working draft (<a href="http://wg21.link/N4766">N4766</a>) provide facilities for static reflection that are based on the template metaprogramming paradigm. Recently, however, language features have been proposed that would enable a more natural syntax for metaprogramming through use of <code>constexpr</code> facilities (See: <a href="http://wg21.link/p0598">P0598</a>, <a href="http://wg21.link/p0633">P0633</a>, <a href="http://wg21.link/p0712">P0712</a>, and <a href="http://wg21.link/p0784">P0784</a>). This paper explores the impact of these language facilities on reflexpr and considers what a natural-syntax-based reflection library would look like.</p>
<h2 id="changes">Changes</h2>
<ul>
<li>P0953R1 introduces a new section, <a href="#library-design-alternative">Library Design Alternative</a>, which, based on feedback from SG7, presents an approach using type-erased, by-value objects. Second, <code>typename</code> was introduced a disambiguator for <code>unreflexpr</code> to address ambiguity in some contexts. Third, a discussion was added to explain the motivation of using pointers instead of references. Finally, the reflect namespace is suggested for placement of type_traits functions.</li>
</ul>
<h2 id="introduction">Introduction</h2>
<h3 id="from-tmp-reflexpr-to-cxp-reflexpr">From TMP-reflexpr to CXP-reflexpr</h3>
<p>Template-metaprogramming-based reflexpr (TMP-reflexpr), which is succinctly described in <a href="http://wg21.link/p0578">P0578</a>, includes a <code>reflexpr</code> operator that, when applied to C++ syntax, produces a <em>type</em> that encodes “meta” information about that syntax. For example, when <code>reflexpr</code> is applied to a type, the result can be used to query that type’s name and, in the case of a class, list its member variables.</p>
<p>Consider the following implementation of a function <code>dump</code> which outputs the name and public data members of an arbitrary type. Note that iteration of the data members involves use of an auxiliary function and variadic templates.</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb3-1" data-line-number="1"><span class="kw">template</span> &lt;<span class="kw">typename</span> T&gt;</a>
<a class="sourceLine" id="cb3-2" data-line-number="2"><span class="dt">void</span> dumpDataMembers(); <span class="co">// implemented below</span></a>
<a class="sourceLine" id="cb3-3" data-line-number="3"></a>
<a class="sourceLine" id="cb3-4" data-line-number="4"><span class="kw">template</span> &lt;<span class="kw">typename</span> T&gt;</a>
<a class="sourceLine" id="cb3-5" data-line-number="5"><span class="dt">void</span> dump()</a>
<a class="sourceLine" id="cb3-6" data-line-number="6">    <span class="co">// Output the name and data members of a record (class, struct, union).</span></a>
<a class="sourceLine" id="cb3-7" data-line-number="7">    <span class="co">// For example:</span></a>
<a class="sourceLine" id="cb3-8" data-line-number="8">    <span class="co">//..</span></a>
<a class="sourceLine" id="cb3-9" data-line-number="9">    <span class="co">// struct S {</span></a>
<a class="sourceLine" id="cb3-10" data-line-number="10">    <span class="co">//     std::string m_s;</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11">    <span class="co">//     int m_i;</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12">    <span class="co">// };</span></a>
<a class="sourceLine" id="cb3-13" data-line-number="13">    <span class="co">// </span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14">    <span class="co">// int main {</span></a>
<a class="sourceLine" id="cb3-15" data-line-number="15">    <span class="co">//     dump&lt;S&gt;(); // name: S</span></a>
<a class="sourceLine" id="cb3-16" data-line-number="16">    <span class="co">//                // members:</span></a>
<a class="sourceLine" id="cb3-17" data-line-number="17">    <span class="co">//                //   std::string m_s</span></a>
<a class="sourceLine" id="cb3-18" data-line-number="18">    <span class="co">//                //   int m_i</span></a>
<a class="sourceLine" id="cb3-19" data-line-number="19">    <span class="co">// }</span></a>
<a class="sourceLine" id="cb3-20" data-line-number="20">    <span class="co">//..</span></a>
<a class="sourceLine" id="cb3-21" data-line-number="21"></a>
<a class="sourceLine" id="cb3-22" data-line-number="22">{</a>
<a class="sourceLine" id="cb3-23" data-line-number="23">    <span class="kw">using</span> MetaT = reflexpr(T);</a>
<a class="sourceLine" id="cb3-24" data-line-number="24">    <span class="bu">std::</span>cout &lt;&lt; <span class="st">&quot;name: &quot;</span> &lt;&lt; get_display_name_v&lt;MetaT&gt; &lt;&lt; <span class="bu">std::</span>endl;</a>
<a class="sourceLine" id="cb3-25" data-line-number="25">    <span class="bu">std::</span>cout &lt;&lt; <span class="st">&quot;members:&quot;</span> &lt;&lt; <span class="bu">std::</span>endl;</a>
<a class="sourceLine" id="cb3-26" data-line-number="26"></a>
<a class="sourceLine" id="cb3-27" data-line-number="27">    <span class="kw">using</span> DataMemberObjectSequence = <span class="dt">get_public_data_members_t</span>&lt;MetaT&gt;;</a>
<a class="sourceLine" id="cb3-28" data-line-number="28">    dumpDataMembers&lt;unpack_sequence&lt;<span class="bu">std::</span>tuple, DataMemberObjectSequence&gt;&gt;();</a>
<a class="sourceLine" id="cb3-29" data-line-number="29">}</a>
<a class="sourceLine" id="cb3-30" data-line-number="30"></a>
<a class="sourceLine" id="cb3-31" data-line-number="31"><span class="kw">template</span> &lt;&gt;</a>
<a class="sourceLine" id="cb3-32" data-line-number="32"><span class="dt">void</span> dumpDataMembers&lt;<span class="bu">std::</span>tuple&lt;&gt;&gt;() { }</a>
<a class="sourceLine" id="cb3-33" data-line-number="33">    <span class="co">// base case does nothing</span></a>
<a class="sourceLine" id="cb3-34" data-line-number="34"></a>
<a class="sourceLine" id="cb3-35" data-line-number="35"><span class="kw">template</span> &lt;<span class="kw">typename</span> DataMember, <span class="kw">typename</span>... DataMembers&gt;</a>
<a class="sourceLine" id="cb3-36" data-line-number="36"><span class="dt">void</span> dumpDataMembers&lt;<span class="bu">std::</span>tuple&lt;DataMember, DataMembers...&gt;&gt;()</a>
<a class="sourceLine" id="cb3-37" data-line-number="37">{</a>
<a class="sourceLine" id="cb3-38" data-line-number="38">    <span class="co">// Output information about the first data member and recurse for the</span></a>
<a class="sourceLine" id="cb3-39" data-line-number="39">    <span class="co">// subsequent data members.</span></a>
<a class="sourceLine" id="cb3-40" data-line-number="40">    <span class="bu">std::</span>cout</a>
<a class="sourceLine" id="cb3-41" data-line-number="41">        &lt;&lt; <span class="st">&quot;  &quot;</span> &lt;&lt; get_display_name_v&lt;<span class="dt">get_type_t</span>&lt;DataMember&gt;&gt;</a>
<a class="sourceLine" id="cb3-42" data-line-number="42">        &lt;&lt; <span class="st">&quot; &quot;</span> &lt;&lt; get_display_name_v&lt;DataMember&gt;</a>
<a class="sourceLine" id="cb3-43" data-line-number="43">        &lt;&lt; <span class="bu">std::</span>endl;</a>
<a class="sourceLine" id="cb3-44" data-line-number="44">    dumpDataMembers&lt;<span class="bu">std::</span>tuple&lt;DataMembers...&gt;&gt;();</a>
<a class="sourceLine" id="cb3-45" data-line-number="45">}</a></code></pre></div>
<p>While the above code can be simplified somewhat by use of a template metaprogramming library such as Boost.MPL, this snippet is fairly representative of the complexity and, for most C++ developers, unfamiliarity of the required constructs.</p>
<p>Louis Dionne’s Boost.Hana library provides an alternative approach whereby values with specially designed types allow one to write code that has much of the appearance of normal C++ code, but actually accomplishes metaprogramming (See <a href="http://wg21.link/p0425">P0425</a>). Instead of having to write a separate function to accomplish iteration, one could use <code>hana::for_each</code> from within the <code>dump</code> function.</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb4-1" data-line-number="1"><span class="kw">template</span> &lt;<span class="kw">typename</span> T&gt;</a>
<a class="sourceLine" id="cb4-2" data-line-number="2"><span class="dt">void</span> dump() {</a>
<a class="sourceLine" id="cb4-3" data-line-number="3">    <span class="kw">constexpr</span> <span class="kw">auto</span> metaT = reflexpr(T);</a>
<a class="sourceLine" id="cb4-4" data-line-number="4">    <span class="bu">std::</span>cout &lt;&lt; <span class="st">&quot;name: &quot;</span> &lt;&lt; metaT-&gt;get_display_name() &lt;&lt; <span class="bu">std::</span>endl;</a>
<a class="sourceLine" id="cb4-5" data-line-number="5">    <span class="bu">std::</span>cout &lt;&lt; <span class="st">&quot;members:&quot;</span> &lt;&lt; <span class="bu">std::</span>endl;</a>
<a class="sourceLine" id="cb4-6" data-line-number="6">    hana::for_each(metaT.get_public_data_members(), [&amp;](<span class="kw">auto</span> dataMember) {</a>
<a class="sourceLine" id="cb4-7" data-line-number="7">        <span class="bu">std::</span>cout</a>
<a class="sourceLine" id="cb4-8" data-line-number="8">            &lt;&lt; <span class="st">&quot;  &quot;</span> &lt;&lt; dataMember.getType().get_display_name()</a>
<a class="sourceLine" id="cb4-9" data-line-number="9">            &lt;&lt; <span class="st">&quot; &quot;</span> &lt;&lt; dataMember.get_display_name()</a>
<a class="sourceLine" id="cb4-10" data-line-number="10">            &lt;&lt; <span class="bu">std::</span>endl;</a>
<a class="sourceLine" id="cb4-11" data-line-number="11">    });</a>
<a class="sourceLine" id="cb4-12" data-line-number="12">}</a></code></pre></div>
<p>While this mitigates much of the syntactic complexity of template metaprogramming, the types involved are opaque (they cannot be named) and special library features are required to accomplish tasks such as iteration.</p>
<p>Constexpr-based reflexpr (CXP-reflexpr), the subject of this paper, operates in the Hana-style: instead of <code>reflexpr</code> producing a <em>type</em>, it produces a <em>value</em> that encodes meta information. Unlike Hana-style, however, this value has a non-opaque type and we normally do not need special library features to work with it.</p>
<p>The following snippet illustrates our original example using CXP-reflexpr.</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb5-1" data-line-number="1"><span class="kw">template</span> &lt;<span class="kw">typename</span> T&gt;</a>
<a class="sourceLine" id="cb5-2" data-line-number="2"><span class="dt">void</span> dump() {</a>
<a class="sourceLine" id="cb5-3" data-line-number="3">    <span class="kw">constexpr</span> reflect::Record <span class="at">const</span> * metaT = reflexpr(T);</a>
<a class="sourceLine" id="cb5-4" data-line-number="4">    <span class="bu">std::</span>cout &lt;&lt; <span class="st">&quot;name: &quot;</span> &lt;&lt; metaT-&gt;get_display_name() &lt;&lt; <span class="bu">std::</span>endl;</a>
<a class="sourceLine" id="cb5-5" data-line-number="5">    <span class="bu">std::</span>cout &lt;&lt; <span class="st">&quot;members:&quot;</span> &lt;&lt; <span class="bu">std::</span>endl;</a>
<a class="sourceLine" id="cb5-6" data-line-number="6">    <span class="cf">for</span>(RecordMember <span class="at">const</span> * member : metaT-&gt;get_public_data_members())</a>
<a class="sourceLine" id="cb5-7" data-line-number="7">        <span class="bu">std::</span>cout</a>
<a class="sourceLine" id="cb5-8" data-line-number="8">            &lt;&lt; <span class="st">&quot;  &quot;</span> &lt;&lt; member-&gt;get_type()-&gt;get_display_name()</a>
<a class="sourceLine" id="cb5-9" data-line-number="9">            &lt;&lt; <span class="st">&quot; &quot;</span> &lt;&lt; member-&gt;get_name() &lt;&lt; <span class="bu">std::</span>endl;</a>
<a class="sourceLine" id="cb5-10" data-line-number="10">}</a></code></pre></div>
<h3 id="mix-compile-time-reflection-with-runtime-values">Mix compile-time reflection with runtime values</h3>
<p>In the above example, we didn’t have a need to mix a runtime value with compile-time meta-information. While this is doable with TMP-reflexpr, additional language facilities are required to accomplish this with CXP-reflexpr.</p>
<p>Consider a function <code>dumpJson</code> that outputs an arbitrary <code>class</code> or <code>struct</code> as a JSON string. Note the use of two new language constructs: <code>constexpr for</code>, and <code>unreflexpr</code>.</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb6-1" data-line-number="1"><span class="dt">void</span> dumpJson(<span class="at">const</span> <span class="bu">std::</span>string &amp;s);</a>
<a class="sourceLine" id="cb6-2" data-line-number="2">    <span class="co">// Output &#39;s&#39; with double-quotes and escaped special characters.</span></a>
<a class="sourceLine" id="cb6-3" data-line-number="3"></a>
<a class="sourceLine" id="cb6-4" data-line-number="4"><span class="dt">void</span> dumpJson(<span class="at">const</span> <span class="dt">int</span> &amp;i);</a>
<a class="sourceLine" id="cb6-5" data-line-number="5">    <span class="co">// Output &#39;i&#39; as an int.</span></a>
<a class="sourceLine" id="cb6-6" data-line-number="6"></a>
<a class="sourceLine" id="cb6-7" data-line-number="7"><span class="kw">template</span> &lt;<span class="kw">typename</span> T&gt;</a>
<a class="sourceLine" id="cb6-8" data-line-number="8"><span class="dt">void</span> dumpJson(<span class="at">const</span> T &amp;t) {</a>
<a class="sourceLine" id="cb6-9" data-line-number="9">    <span class="bu">std::</span>cout &lt;&lt; <span class="st">&quot;{ &quot;</span>;</a>
<a class="sourceLine" id="cb6-10" data-line-number="10">    <span class="kw">constexpr</span> reflect::Class <span class="at">const</span> * metaT = reflexpr(T);</a>
<a class="sourceLine" id="cb6-11" data-line-number="11">    <span class="dt">bool</span> saw_prev = <span class="kw">false</span>;</a>
<a class="sourceLine" id="cb6-12" data-line-number="12">    <span class="kw">constexpr</span> <span class="cf">for</span>(RecordMember <span class="at">const</span> * member : metaT-&gt;get_public_data_members())</a>
<a class="sourceLine" id="cb6-13" data-line-number="13">    {</a>
<a class="sourceLine" id="cb6-14" data-line-number="14">        <span class="cf">if</span>(saw_prev) {</a>
<a class="sourceLine" id="cb6-15" data-line-number="15">            <span class="bu">std::</span>cout &lt;&lt; <span class="st">&quot;, &quot;</span>;</a>
<a class="sourceLine" id="cb6-16" data-line-number="16">        }</a>
<a class="sourceLine" id="cb6-17" data-line-number="17"></a>
<a class="sourceLine" id="cb6-18" data-line-number="18">        <span class="bu">std::</span>cout &lt;&lt; member-&gt;get_name() &lt;&lt; <span class="st">&quot;=&quot;</span>;</a>
<a class="sourceLine" id="cb6-19" data-line-number="19"></a>
<a class="sourceLine" id="cb6-20" data-line-number="20">        <span class="kw">constexpr</span> reflect::Constant <span class="at">const</span> * pointerToMember = member-&gt;get_pointer();</a>
<a class="sourceLine" id="cb6-21" data-line-number="21">        dumpJson(t.*unreflexpr(pointerToMember));</a>
<a class="sourceLine" id="cb6-22" data-line-number="22"></a>
<a class="sourceLine" id="cb6-23" data-line-number="23">        saw_prev = <span class="kw">true</span>;</a>
<a class="sourceLine" id="cb6-24" data-line-number="24">    }</a>
<a class="sourceLine" id="cb6-25" data-line-number="25">    <span class="bu">std::</span>cout &lt;&lt; <span class="st">&quot; }&quot;</span>;</a>
<a class="sourceLine" id="cb6-26" data-line-number="26">}</a>
<a class="sourceLine" id="cb6-27" data-line-number="27"></a>
<a class="sourceLine" id="cb6-28" data-line-number="28"><span class="kw">struct</span> S {</a>
<a class="sourceLine" id="cb6-29" data-line-number="29">    <span class="bu">std::</span>string <span class="va">m_s</span>;</a>
<a class="sourceLine" id="cb6-30" data-line-number="30">    <span class="dt">int</span> <span class="va">m_i</span>;</a>
<a class="sourceLine" id="cb6-31" data-line-number="31">};</a>
<a class="sourceLine" id="cb6-32" data-line-number="32"></a>
<a class="sourceLine" id="cb6-33" data-line-number="33"><span class="dt">int</span> main {</a>
<a class="sourceLine" id="cb6-34" data-line-number="34">    dumpJson( S{<span class="st">&quot;hello&quot;</span>, <span class="dv">33</span>} ); <span class="co">// outputs: { m_s=&quot;hello&quot;, m_i=33 }</span></a>
<a class="sourceLine" id="cb6-35" data-line-number="35">}</a></code></pre></div>
<p>The recursive call warrants some additional explanation</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb7-1" data-line-number="1">dumpJson(t.*unreflexpr(pointerToMember));</a></code></pre></div>
<ul>
<li><code>pointerToMember</code> is “meta” information about a pointer to a member. In the above example, it refers to <code>&amp;S::m_s</code> in the first iteration of the loop and <code>&amp;S::m_i</code> in the second iteration.</li>
<li>The <code>unreflexpr</code> operator converts this “meta” information about the pointer to member to the pointer to member itself.</li>
<li><code>t.*</code> is the syntax for accessing a pointer to member.</li>
<li><code>dumpJson</code> is the recursive call.</li>
</ul>
<p>The first iteration is decomposed like this:</p>
<div class="sourceCode" id="cb8"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb8-1" data-line-number="1">dumpJson(t.*unreflexpr(pointerToMember));</a>
<a class="sourceLine" id="cb8-2" data-line-number="2">              ↓</a>
<a class="sourceLine" id="cb8-3" data-line-number="3">dumpJson(t.*&amp;S::<span class="va">m_s</span>);</a>
<a class="sourceLine" id="cb8-4" data-line-number="4">              ↓</a>
<a class="sourceLine" id="cb8-5" data-line-number="5">dumpJson(t.<span class="va">m_s</span>);</a></code></pre></div>
<p>The second iteration is similar:</p>
<div class="sourceCode" id="cb9"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb9-1" data-line-number="1">dumpJson(t.*unreflexpr(pointerToMember));</a>
<a class="sourceLine" id="cb9-2" data-line-number="2">              ↓</a>
<a class="sourceLine" id="cb9-3" data-line-number="3">dumpJson(t.*&amp;S::<span class="va">m_i</span>);</a>
<a class="sourceLine" id="cb9-4" data-line-number="4">              ↓</a>
<a class="sourceLine" id="cb9-5" data-line-number="5">dumpJson(t.<span class="va">m_i</span>);</a></code></pre></div>
<h2 id="supporting-language-constructs">Supporting language constructs</h2>
<h3 id="constexpr-for"><code>constexpr for</code></h3>
<p>This construct essentially unrolls a for loop at compile-time, allowing for the body of the loop to manifest different types at different iterations. This was originally proposed by Andrew Sutton in <a href="http://wg21.link/p0589">P0589</a> for Hana-style programming, but the unrolling semantics work for our purposes as well.</p>
<p>While this language construct isn’t strictly necessary for CXP-reflexpr, we think it greatly simplifies code that would otherwise require complex library facilities.</p>
<h3 id="constexpr-time-allocators">constexpr-time allocators</h3>
<p>constexpr-time allocators as described in <a href="http://wg21.link/p0784">P0784</a> (also seen in a more preliminary form in <a href="http://wg21.link/p0784">P0597</a>) allow us to make use of <code>std::vector</code>, among other data types, at compile time. While these constructs aren’t strictly necessary (resizable arrays based on fixed buffer sizes has been demonstrated by Ben Deane and Jason Turner in <a href="http://wg21.link/p0810">P0810</a>), they make the data structures used at compile time more uniform with those at runtime.</p>
<h3 id="unreflexpr"><code>unreflexpr</code></h3>
<p>With TMP-reflexpr, types are easily extracted because we are already in a type context.</p>
<div class="sourceCode" id="cb10"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb10-1" data-line-number="1"><span class="co">// &#39;foo&#39; has a type that is the same as the first field of &#39;S&#39;.</span></a>
<a class="sourceLine" id="cb10-2" data-line-number="2"><span class="dt">get_reflected_type_t</span>&lt;</a>
<a class="sourceLine" id="cb10-3" data-line-number="3">  <span class="dt">get_type_t</span>&lt;</a>
<a class="sourceLine" id="cb10-4" data-line-number="4">    <span class="dt">get_element_t</span>&lt;</a>
<a class="sourceLine" id="cb10-5" data-line-number="5">        <span class="dv">0</span>,</a>
<a class="sourceLine" id="cb10-6" data-line-number="6">        <span class="dt">get_public_data_members_t</span>&lt;reflexpr(S)&gt;&gt;&gt;&gt; foo;</a></code></pre></div>
<p>With CXP-reflexpr, on the other hand, once we have a <code>Type</code> object, there isn’t a sufficient language facility for going back into type processing</p>
<div class="sourceCode" id="cb11"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb11-1" data-line-number="1"><span class="kw">constexpr</span> Type <span class="at">const</span> * t = reflexpr(S)-&gt;get_public_data_members()[<span class="dv">0</span>]-&gt;get_type();</a>
<a class="sourceLine" id="cb11-2" data-line-number="2"></a>
<a class="sourceLine" id="cb11-3" data-line-number="3"><span class="co">// unreflexpr is required to create &#39;foo&#39; with the type that &#39;t&#39; refers to.</span></a>
<a class="sourceLine" id="cb11-4" data-line-number="4">unreflexpr(t) foo;</a></code></pre></div>
<p>One might think <code>decltype</code> would work, but the <code>Type</code> returned by reflexpr(X) is generic, and has no specialized member types for <code>X</code>; there is nothing <code>X</code>-specific to <code>decltype()</code> on.</p>
<p>Therefore, the one language-level feature that is critical for feature parity with TMP-reflexpr is <code>unreflexpr</code> support. It is required for both types and compile-time values.</p>
<h2 id="library-considerations">Library considerations</h2>
<p>A <code>constexpr reflexpr</code> facility has several library-level implications and design questions. These are addressed in this section.</p>
<h3 id="typeful-reflection">Typeful reflection</h3>
<p>Some of the initial sketches for constexpr-based reflection had the <code>reflexpr</code> operation produce values that are always of the same type. While this has some advantages for implementers and is certainly simpler that each value having its own unique type, we feel that making some use of types will encourage programming that is easier to read and reason about.</p>
<ul>
<li><p>Typeful reflection enables the use of overloading in library development. Consider the simplicity of the following overloaded function when compared to a single function implemented with <code>constexpr if</code>.</p>
<div class="sourceCode" id="cb12"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb12-1" data-line-number="1"><span class="dt">void</span> outputMetaInformation(reflect::Union <span class="at">const</span> *);</a>
<a class="sourceLine" id="cb12-2" data-line-number="2"><span class="dt">void</span> outputMetaInformation(reflect::Class <span class="at">const</span> *);</a>
<a class="sourceLine" id="cb12-3" data-line-number="3"><span class="dt">void</span> outputMetaInformation(reflect::Enum <span class="at">const</span> *);</a>
<a class="sourceLine" id="cb12-4" data-line-number="4"><span class="dt">void</span> outputMetaInformation(reflect::Type <span class="at">const</span> *);</a>
<a class="sourceLine" id="cb12-5" data-line-number="5"><span class="dt">void</span> outputMetaInformation(reflect::TypeAlias <span class="at">const</span> *);</a>
<a class="sourceLine" id="cb12-6" data-line-number="6"><span class="dt">void</span> outputMetaInformation(reflect::Namespace <span class="at">const</span> *);</a>
<a class="sourceLine" id="cb12-7" data-line-number="7"><span class="dt">void</span> outputMetaInformation(reflect::NamespaceAlias <span class="at">const</span> *);</a>
<a class="sourceLine" id="cb12-8" data-line-number="8"><span class="dt">void</span> outputMetaInformation(reflect::RecordMember <span class="at">const</span> *);</a>
<a class="sourceLine" id="cb12-9" data-line-number="9"><span class="dt">void</span> outputMetaInformation(reflect::Variable <span class="at">const</span> *);</a>
<a class="sourceLine" id="cb12-10" data-line-number="10"><span class="dt">void</span> outputMetaInformation(reflect::Enumerator <span class="at">const</span> *);</a></code></pre></div></li>
<li><p>Typeful reflection is similar to the already accepted and sufficiently motivated concepts-based TMP reflexpr. Types to values is what’s concepts are to types.</p></li>
<li><p>Using untyped reflection has many of the same problem as treating all memory as <code>void*</code>. Reasonably-strong types help with organization and the long-term maintenance of programs.</p></li>
</ul>
<p>We also considered using <code>std::variant</code> or variant-like classes as an alternative to reference semantics. Due to the complexity of visitation, the resulting code ended up complex looking, especially for those newer to the language. If a language-level variant with pattern matching support were to be incorporated into C++, then this might be worth revisiting.</p>
<h3 id="references-vs.pointers">References vs. pointers</h3>
<p>We were initially tempted to use references instead of pointers to provide a more value-semantic experience. Unfortunately, the inability to put a reference directly in a <code>std::vector</code> hinders usability. This design choice would require use of the often confusing <code>std::reference_wrapper</code> template in several places.</p>
<h3 id="downcasting">Downcasting</h3>
<p>While reflecting syntax will produce the most-specific type available, the need to go from a general type to a specific type remains. For example, the return type of <code>Record::get_public_member_types</code> is <code>std::vector&lt;Type const*&gt;</code>. A user may want to “downcast” one of these types into a <code>Class</code>, for example.</p>
<p>For this, we provide two cast-related operations in our <code>Object</code> class:</p>
<div class="sourceCode" id="cb13"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb13-1" data-line-number="1"><span class="kw">class</span> Object {</a>
<a class="sourceLine" id="cb13-2" data-line-number="2"><span class="kw">public</span>:</a>
<a class="sourceLine" id="cb13-3" data-line-number="3">    <span class="co">// ...</span></a>
<a class="sourceLine" id="cb13-4" data-line-number="4"></a>
<a class="sourceLine" id="cb13-5" data-line-number="5">    <span class="kw">template</span>&lt;<span class="kw">typename</span> T&gt;</a>
<a class="sourceLine" id="cb13-6" data-line-number="6">    <span class="kw">constexpr</span> T <span class="at">const</span> * get_as() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb13-7" data-line-number="7">        <span class="co">// Return the specified view, but constexpr-throw (aka diagnose) in</span></a>
<a class="sourceLine" id="cb13-8" data-line-number="8">        <span class="co">// case of invalid accesses.</span></a>
<a class="sourceLine" id="cb13-9" data-line-number="9"></a>
<a class="sourceLine" id="cb13-10" data-line-number="10">    <span class="kw">template</span>&lt;<span class="kw">typename</span> T&gt;</a>
<a class="sourceLine" id="cb13-11" data-line-number="11">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_a() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb13-12" data-line-number="12">        <span class="co">// Returns whether or not this object can be viewed as the specified</span></a>
<a class="sourceLine" id="cb13-13" data-line-number="13">        <span class="co">// &#39;T&#39;.</span></a>
<a class="sourceLine" id="cb13-14" data-line-number="14">};</a></code></pre></div>
<p>These functions allow a user to check if the object can be downcast and to actually perform the operation.</p>
<h3 id="type_traits">type_traits</h3>
<p>The C++ standard library includes several metafunctions that aid in metaprogramming in the <code>&lt;type_traits&gt;</code> header. <code>std::add_const_t</code> is one such example. While these facilities can be used in the CXP-reflexpr paradigm, it is awkward:</p>
<div class="sourceCode" id="cb14"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb14-1" data-line-number="1">Type <span class="at">const</span> * p = <span class="co">/*...*/</span>;</a>
<a class="sourceLine" id="cb14-2" data-line-number="2">Type <span class="at">const</span> * constP = reflexpr(<span class="bu">std::</span>add_const_t&lt;unreflexpr(p)&gt;);</a></code></pre></div>
<p>We propose that each of these existing metaprogramming functions get a CXP-reflexpr-styled equivalent in the <code>reflect</code> namespace.</p>
<div class="sourceCode" id="cb15"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb15-1" data-line-number="1"><span class="kw">namespace</span> <span class="bu">std::</span>reflect {</a>
<a class="sourceLine" id="cb15-2" data-line-number="2">  <span class="kw">constexpr</span> reflect::Type <span class="at">const</span> * add_const(reflect::Type <span class="at">const</span> * t)</a>
<a class="sourceLine" id="cb15-3" data-line-number="3">  {</a>
<a class="sourceLine" id="cb15-4" data-line-number="4">    <span class="co">// Not necessarily implemented in this way.</span></a>
<a class="sourceLine" id="cb15-5" data-line-number="5">    <span class="cf">return</span> reflexpr(<span class="bu">std::</span>add_const_t&lt;unreflexpr(t)&gt;);</a>
<a class="sourceLine" id="cb15-6" data-line-number="6">  }</a>
<a class="sourceLine" id="cb15-7" data-line-number="7">}</a></code></pre></div>
<h2 id="library-design-alternative">Library Design Alternative</h2>
<p>While the use of pointers and an inheritance hierarchy for user syntax has benefits, there are two principle problems with this approach. First, as hinted at in <a href="http://wg21.link/P0993r0">P0993r0</a>, the storage and linkage of the pointed-to value raises some implementability concerns that, while likely possible to mitigate, significantly increase the complexity of the approach. Second, we have observed a preference from the committee to use value semantics instead of pointer semantics whenever possible.</p>
<p><a href="http://wg21.link/P0993r0">P0993r0</a> advocated for an approach where <code>reflexpr</code> would always return values of type <code>meta::object</code>. This forces use of concepts in the case of overloading. The following snippet shows the changed signatures of <code>outputMetaInformation</code> as described in <a href="#typeful-reflection">Typeful reflection</a>:</p>
<div class="sourceCode" id="cb16"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb16-1" data-line-number="1"><span class="kw">template</span>&lt;reflect::Union u&gt;</a>
<a class="sourceLine" id="cb16-2" data-line-number="2"><span class="dt">void</span> outputMetaInformation();</a>
<a class="sourceLine" id="cb16-3" data-line-number="3"><span class="kw">template</span>&lt;reflect::Class c&gt;</a>
<a class="sourceLine" id="cb16-4" data-line-number="4"><span class="dt">void</span> outputMetaInformation();</a></code></pre></div>
<p>Note that <code>reflect::Union</code> and <code>reflect::Class</code> are concepts and not types. <code>u</code> and <code>c</code>, in this approach, both have type <code>reflect::object</code>.</p>
<p>There are three principle drawbacks of this approach. First overloading must always use values passed by a template parameter, even when it would not otherwise be necessary. This may substantially discourage creation and maintenance of reflection code by the large number of C++ developers that would not consider themselves experts in the language. Second, requiring concepts to do basic things goes against the desire to make metaprogramming look just like normal programming. Third, the lack of built-in types may result in the proliferation of programs which use <code>reflect::object</code> without concepts and create a maintenance burden.</p>
<p>A third alternative is to use type-erased, by-value objects. This is like the ‘pointer’ approach in that there is a hierarchy of types, but conversion operators are used instead of casting to base classes. For example, the <code>RecordMember</code> type would be,</p>
<div class="sourceCode" id="cb17"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb17-1" data-line-number="1"><span class="kw">class</span> RecordMember : </a>
<a class="sourceLine" id="cb17-2" data-line-number="2">{</a>
<a class="sourceLine" id="cb17-3" data-line-number="3"><span class="kw">public</span>:</a>
<a class="sourceLine" id="cb17-4" data-line-number="4">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_public() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb17-5" data-line-number="5">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_protected() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb17-6" data-line-number="6">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_private() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb17-7" data-line-number="7"></a>
<a class="sourceLine" id="cb17-8" data-line-number="8">    <span class="kw">constexpr</span> Record get_type() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb17-9" data-line-number="9">    <span class="kw">operator</span> Named() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb17-10" data-line-number="10">};</a></code></pre></div>
<p>, instead of,</p>
<div class="sourceCode" id="cb18"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb18-1" data-line-number="1"><span class="kw">class</span> RecordMember : <span class="kw">public</span> Named</a>
<a class="sourceLine" id="cb18-2" data-line-number="2">{</a>
<a class="sourceLine" id="cb18-3" data-line-number="3"><span class="kw">public</span>:</a>
<a class="sourceLine" id="cb18-4" data-line-number="4">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_public() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb18-5" data-line-number="5">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_protected() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb18-6" data-line-number="6">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_private() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb18-7" data-line-number="7"></a>
<a class="sourceLine" id="cb18-8" data-line-number="8">    <span class="kw">constexpr</span> Record <span class="at">const</span> * get_type() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb18-9" data-line-number="9">};</a></code></pre></div>
<p>. This approach provides the benefits of typeful programming and those of the monotype approach.</p>
<p>Consider the difference between the <code>get_public_data_members</code> function of <code>Record</code> with the monotype style,</p>
<div class="sourceCode" id="cb19"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb19-1" data-line-number="1"><span class="kw">class</span> Record : <span class="kw">public</span> Type</a>
<a class="sourceLine" id="cb19-2" data-line-number="2">{</a>
<a class="sourceLine" id="cb19-3" data-line-number="3">    <span class="co">//...</span></a>
<a class="sourceLine" id="cb19-4" data-line-number="4">    <span class="kw">constexpr</span> <span class="bu">std::</span>vector&lt;meta::object&gt; get_public_data_members() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb19-5" data-line-number="5">};</a>
<a class="sourceLine" id="cb19-6" data-line-number="6"></a>
<a class="sourceLine" id="cb19-7" data-line-number="7"><span class="co">// Type provides little information here</span></a>
<a class="sourceLine" id="cb19-8" data-line-number="8"><span class="bu">std::</span>vector&lt;meta::object&gt; members</a>
<a class="sourceLine" id="cb19-9" data-line-number="9">  = reflexpr(SomeType).get_public_data_members();</a>
<a class="sourceLine" id="cb19-10" data-line-number="10"></a>
<a class="sourceLine" id="cb19-11" data-line-number="11"><span class="co">// Alternatively, we assume some kind of terse concepts syntax.</span></a>
<a class="sourceLine" id="cb19-12" data-line-number="12"><span class="bu">std::</span>vector&lt;meta::RecordMember {}&gt; members</a>
<a class="sourceLine" id="cb19-13" data-line-number="13">  = reflexpr(SomeType).get_public_data_members();</a></code></pre></div>
<p>, and the type-erased, by-value style,</p>
<div class="sourceCode" id="cb20"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb20-1" data-line-number="1"><span class="kw">class</span> Record : <span class="kw">public</span> Type</a>
<a class="sourceLine" id="cb20-2" data-line-number="2">{</a>
<a class="sourceLine" id="cb20-3" data-line-number="3">    <span class="co">//...</span></a>
<a class="sourceLine" id="cb20-4" data-line-number="4">    <span class="kw">constexpr</span> <span class="bu">std::</span>vector&lt;RecordMember&gt; get_public_data_members() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb20-5" data-line-number="5">};</a>
<a class="sourceLine" id="cb20-6" data-line-number="6"></a>
<a class="sourceLine" id="cb20-7" data-line-number="7"><span class="bu">std::</span>vector&lt;RecordMember&gt; members</a>
<a class="sourceLine" id="cb20-8" data-line-number="8">  = reflexpr(SomeType).get_public_data_members();</a></code></pre></div>
<p>. The latter appears at a glance to be typical C++ code.</p>
<h2 id="datatypes-and-operations">Datatypes and Operations</h2>
<p>CXP-reflexpr provides a rich class hierarchy representing the various attributes that can be reflected. The following diagram illustrates this hierarchy.</p>
<p><img src="data:image/png;base64,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" id="id" class="class" style="width:100.0%" /></p>
<p>Arrows go from derived classes to base classes. The blue classes are those that <code>reflexpr</code> directly produces values of. The green classes are those that are intermediate or indirectly available from the other classes.</p>
<h3 id="classes">Classes</h3>
<p>What follows is a short synopsis of the class hierarchy described above.</p>
<div class="sourceCode" id="cb21"><pre class="sourceCode cpp"><code class="sourceCode cpp"><a class="sourceLine" id="cb21-1" data-line-number="1"><span class="kw">namespace</span> reflect {</a>
<a class="sourceLine" id="cb21-2" data-line-number="2"></a>
<a class="sourceLine" id="cb21-3" data-line-number="3"><span class="kw">class</span> Object {</a>
<a class="sourceLine" id="cb21-4" data-line-number="4"><span class="kw">public</span>:</a>
<a class="sourceLine" id="cb21-5" data-line-number="5">    <span class="kw">constexpr</span> <span class="bu">std::</span>source_location get_source_location() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-6" data-line-number="6">    <span class="kw">constexpr</span> <span class="bu">std::</span>string get_source_file_name() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-7" data-line-number="7"></a>
<a class="sourceLine" id="cb21-8" data-line-number="8">    <span class="kw">template</span>&lt;<span class="kw">typename</span> T&gt;</a>
<a class="sourceLine" id="cb21-9" data-line-number="9">    <span class="kw">constexpr</span> T <span class="at">const</span> * get_as() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-10" data-line-number="10"></a>
<a class="sourceLine" id="cb21-11" data-line-number="11">    <span class="kw">template</span>&lt;<span class="kw">typename</span> T&gt;</a>
<a class="sourceLine" id="cb21-12" data-line-number="12">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_a() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-13" data-line-number="13">};</a>
<a class="sourceLine" id="cb21-14" data-line-number="14"></a>
<a class="sourceLine" id="cb21-15" data-line-number="15"><span class="kw">class</span> Named : <span class="kw">public</span> Object {</a>
<a class="sourceLine" id="cb21-16" data-line-number="16">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_anonymous() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-17" data-line-number="17">    <span class="kw">constexpr</span> <span class="bu">std::</span>string get_name() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-18" data-line-number="18">    <span class="kw">constexpr</span> <span class="bu">std::</span>string get_display_name() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-19" data-line-number="19">};</a>
<a class="sourceLine" id="cb21-20" data-line-number="20"></a>
<a class="sourceLine" id="cb21-21" data-line-number="21"><span class="kw">class</span> Type : <span class="kw">public</span> Named { };</a>
<a class="sourceLine" id="cb21-22" data-line-number="22"></a>
<a class="sourceLine" id="cb21-23" data-line-number="23"><span class="kw">class</span> Record : <span class="kw">public</span> Type</a>
<a class="sourceLine" id="cb21-24" data-line-number="24">{</a>
<a class="sourceLine" id="cb21-25" data-line-number="25"><span class="kw">public</span>:</a>
<a class="sourceLine" id="cb21-26" data-line-number="26">    <span class="kw">constexpr</span> <span class="bu">std::</span>vector&lt;RecordMember <span class="at">const</span>*&gt; get_public_data_members() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-27" data-line-number="27">    <span class="kw">constexpr</span> <span class="bu">std::</span>vector&lt;RecordMember <span class="at">const</span>*&gt; get_accessible_data_members() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-28" data-line-number="28">    <span class="kw">constexpr</span> <span class="bu">std::</span>vector&lt;RecordMember <span class="at">const</span>*&gt; get_data_members() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-29" data-line-number="29"></a>
<a class="sourceLine" id="cb21-30" data-line-number="30">    <span class="kw">constexpr</span> <span class="bu">std::</span>vector&lt;Type <span class="at">const</span>*&gt; get_public_member_types() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-31" data-line-number="31">    <span class="kw">constexpr</span> <span class="bu">std::</span>vector&lt;Type <span class="at">const</span>*&gt; get_accessible_member_types() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-32" data-line-number="32">    <span class="kw">constexpr</span> <span class="bu">std::</span>vector&lt;Type <span class="at">const</span>*&gt; get_member_types() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-33" data-line-number="33">};</a>
<a class="sourceLine" id="cb21-34" data-line-number="34"></a>
<a class="sourceLine" id="cb21-35" data-line-number="35"><span class="kw">class</span> Union : <span class="kw">public</span> Record { };</a>
<a class="sourceLine" id="cb21-36" data-line-number="36"></a>
<a class="sourceLine" id="cb21-37" data-line-number="37"><span class="kw">class</span> Class : <span class="kw">public</span> Record</a>
<a class="sourceLine" id="cb21-38" data-line-number="38">{</a>
<a class="sourceLine" id="cb21-39" data-line-number="39"><span class="kw">public</span>:</a>
<a class="sourceLine" id="cb21-40" data-line-number="40">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_struct() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-41" data-line-number="41">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_class() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-42" data-line-number="42"></a>
<a class="sourceLine" id="cb21-43" data-line-number="43">    <span class="kw">constexpr</span> <span class="bu">std::</span>vector&lt;Base <span class="at">const</span>*&gt; get_public_bases() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-44" data-line-number="44">    <span class="kw">constexpr</span> <span class="bu">std::</span>vector&lt;Base <span class="at">const</span>*&gt; get_accessible_bases() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-45" data-line-number="45">    <span class="kw">constexpr</span> <span class="bu">std::</span>vector&lt;Base <span class="at">const</span>*&gt; get_bases() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-46" data-line-number="46"></a>
<a class="sourceLine" id="cb21-47" data-line-number="47">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_final() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-48" data-line-number="48">};</a>
<a class="sourceLine" id="cb21-49" data-line-number="49"></a>
<a class="sourceLine" id="cb21-50" data-line-number="50"><span class="kw">class</span> Enum : <span class="kw">public</span> Type</a>
<a class="sourceLine" id="cb21-51" data-line-number="51">{</a>
<a class="sourceLine" id="cb21-52" data-line-number="52">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_scoped_enum() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-53" data-line-number="53">    <span class="kw">constexpr</span> <span class="bu">std::</span>vector&lt;Enumerator <span class="at">const</span>*&gt; get_enumerators() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-54" data-line-number="54">};</a>
<a class="sourceLine" id="cb21-55" data-line-number="55"></a>
<a class="sourceLine" id="cb21-56" data-line-number="56"><span class="kw">class</span> TypeAlias : <span class="kw">public</span> Type</a>
<a class="sourceLine" id="cb21-57" data-line-number="57">{</a>
<a class="sourceLine" id="cb21-58" data-line-number="58">    <span class="kw">constexpr</span> Type <span class="at">const</span> * get_aliased() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-59" data-line-number="59">};</a>
<a class="sourceLine" id="cb21-60" data-line-number="60"></a>
<a class="sourceLine" id="cb21-61" data-line-number="61"><span class="kw">class</span> Variable : <span class="kw">public</span> Named</a>
<a class="sourceLine" id="cb21-62" data-line-number="62">{</a>
<a class="sourceLine" id="cb21-63" data-line-number="63">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_constexpr() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-64" data-line-number="64">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_static() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-65" data-line-number="65"></a>
<a class="sourceLine" id="cb21-66" data-line-number="66">    <span class="kw">constexpr</span> Constant <span class="at">const</span> * get_pointer() <span class="at">const</span>; </a>
<a class="sourceLine" id="cb21-67" data-line-number="67">    <span class="kw">constexpr</span> Type <span class="at">const</span> * get_type() <span class="at">const</span>; </a>
<a class="sourceLine" id="cb21-68" data-line-number="68">};</a>
<a class="sourceLine" id="cb21-69" data-line-number="69"></a>
<a class="sourceLine" id="cb21-70" data-line-number="70"><span class="kw">class</span> Base : <span class="kw">public</span> Object</a>
<a class="sourceLine" id="cb21-71" data-line-number="71">{</a>
<a class="sourceLine" id="cb21-72" data-line-number="72">    <span class="kw">constexpr</span> Class <span class="at">const</span> * get_class() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-73" data-line-number="73">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_virtual() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-74" data-line-number="74">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_public() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-75" data-line-number="75">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_protected() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-76" data-line-number="76">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_private() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-77" data-line-number="77">};</a>
<a class="sourceLine" id="cb21-78" data-line-number="78"></a>
<a class="sourceLine" id="cb21-79" data-line-number="79"><span class="kw">class</span> Namespace : <span class="kw">public</span> Named</a>
<a class="sourceLine" id="cb21-80" data-line-number="80">{</a>
<a class="sourceLine" id="cb21-81" data-line-number="81">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_global() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-82" data-line-number="82">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_inline() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-83" data-line-number="83">};</a>
<a class="sourceLine" id="cb21-84" data-line-number="84"></a>
<a class="sourceLine" id="cb21-85" data-line-number="85"><span class="kw">class</span> NamespaceAlias : <span class="kw">public</span> Namespace</a>
<a class="sourceLine" id="cb21-86" data-line-number="86">{</a>
<a class="sourceLine" id="cb21-87" data-line-number="87">    <span class="kw">constexpr</span> Namespace <span class="at">const</span> * get_aliased() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-88" data-line-number="88">};</a>
<a class="sourceLine" id="cb21-89" data-line-number="89"></a>
<a class="sourceLine" id="cb21-90" data-line-number="90"><span class="kw">class</span> RecordMember : <span class="kw">public</span> Named</a>
<a class="sourceLine" id="cb21-91" data-line-number="91">{</a>
<a class="sourceLine" id="cb21-92" data-line-number="92">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_public() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-93" data-line-number="93">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_protected() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-94" data-line-number="94">    <span class="kw">constexpr</span> <span class="dt">bool</span> is_private() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-95" data-line-number="95"></a>
<a class="sourceLine" id="cb21-96" data-line-number="96">    <span class="kw">constexpr</span> Record <span class="at">const</span> * get_type() <span class="at">const</span>;</a>
<a class="sourceLine" id="cb21-97" data-line-number="97">};</a>
<a class="sourceLine" id="cb21-98" data-line-number="98"></a>
<a class="sourceLine" id="cb21-99" data-line-number="99"><span class="kw">class</span> Constant : <span class="kw">public</span> Variable { };</a>
<a class="sourceLine" id="cb21-100" data-line-number="100"></a>
<a class="sourceLine" id="cb21-101" data-line-number="101"><span class="kw">class</span> Enumerator : <span class="kw">public</span> Constant { };</a>
<a class="sourceLine" id="cb21-102" data-line-number="102"></a>
<a class="sourceLine" id="cb21-103" data-line-number="103">} <span class="co">// namespace reflect</span></a></code></pre></div>
<!-- TBD: Enumerator can't implement the 'get_pointer' method of 'Variable' unfortunately. I think this should probably be fixed in the language rather than us working around it here. -->
<h3 id="reflexpr"><code>reflexpr</code></h3>
<p><code>reflexpr( texp )</code> returns values of types according to the first rule that applies:</p>
<ul>
<li>If <code>texp</code> is a type alias, a <code>TypeAlias const *</code> is returned.</li>
<li>If <code>texp</code> is an enum, a <code>Enum const *</code> is returned.</li>
<li>If <code>texp</code> is a class, a <code>Class const *</code> is returned.</li>
<li>If <code>texp</code> is a union, a <code>Union const *</code> is returned.</li>
<li>If <code>texp</code> is any other type, a <code>Type const *</code> is returned.</li>
<li>If <code>texp</code> is a namespace alias, a <code>NamespaceAlias const *</code> is returned.</li>
<li>If <code>texp</code> is a namespace, a <code>Namespace const *</code> is returned.</li>
<li>If <code>texp</code> is an enumerator, a <code>Enumerator const *</code> is returned.</li>
<li>If <code>texp</code> is a compile-time constant, a <code>Constant const *</code> is returned.</li>
<li>If <code>texp</code> is a variable, a <code>Variable const *</code> is returned.</li>
</ul>
<h3 id="unreflexpr-1"><code>unreflexpr</code></h3>
<p><code>unreflexpr(meta)</code> produces the entities according to the following rules:</p>
<ul>
<li>If <code>meta</code> has type <code>Type const*</code>, the result is the type that <code>meta</code> reflects.</li>
<li>If <code>meta</code> has type <code>Constant const*</code>, the result is the value that <code>meta</code> reflects. In an otherwise ambiguous context, <code>meta</code> must have type <code>Constant const*</code>.</li>
</ul>
<p><code>unreflexpr typename(meta)</code> produces the entities according to the following rules:</p>
<ul>
<li><code>meta</code> must have type <code>Type const*</code>, the result is the type that <code>meta</code> reflects.</li>
</ul>
<h2 id="conclusion">Conclusion</h2>
<p>This paper introduces a facility that allows for compile-time reflection using a natural, constexpr-styled programming by taking advantages of new constexpr language features on the horizon. The result is a much simplified interface that makes both reflection and metaprogramming more accessible and maintainable.</p>
<h2 id="acknowledgments">Acknowledgments</h2>
<p>None of this would be possible without the continued, pioneering work of Daveed Vandevoorde, Louis Dionne, and Andrew Sutton in improving the experience of constexpr programming.</p>
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