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Travis CI (pmd-bot) 121aa1e8e2 Update documentation 
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<h1 class="post-title-main">Adding support for metrics to a language</h1>
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<div class="summary">PMD's Java module has an extensive framework for the calculation of metrics, which allows rule developers to implement and use new code metrics very simply. Most of the functionality of this framework is abstracted in such a way that any PMD supported language can implement such a framework without too much trouble. Here's how.</div>
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<a target="_blank" href="https://github.com/pmd/pmd/blob/master/docs/pages/pmd/devdocs/major_contributions/adding_new_metrics_framework.md" class="btn btn-default githubEditButton" role="button"><i class="fa fa-github fa-lg"></i> Edit me</a>
<h2 id="internal-architecture-of-the-metrics-framework">Internal architecture of the metrics framework</h2>
<h3 id="overview-of-the-java-framework">Overview of the Java framework</h3>
<p>The framework has several subsystems, the two most easily identifiable being:</p>
<ul>
<li>
<p>A <strong>project memoizer</strong> (<code class="highlighter-rouge">ProjectMemoizer</code>). When a metric is computed, it’s stored back in this structure and can be
reused later. This
reduces the overhead on the calculation of e.g. aggregate results (<code class="highlighter-rouge">ResultOption</code> calculations). The contents of
this data structure are indexed with fully qualified names (<code class="highlighter-rouge">JavaQualifiedName</code>), which must identify unambiguously
classes and methods.</p>
</li>
<li>
<p>The <strong>façade</strong>. The static end-user façade (<code class="highlighter-rouge">JavaMetrics</code>) is backed by an instance of a <code class="highlighter-rouge">JavaMetricsFaçade</code>. This
allows us to abstract the functionality of the façade into <code class="highlighter-rouge">pmd-core</code> for other frameworks to use. The façade
instance contains a project memoizer for the analysed project, and a metrics computer
(<code class="highlighter-rouge">JavaMetricsComputer</code>). It’s this last object which really computes the metric and stores back its result in the
project mirror, while the façade only handles parameters.</p>
</li>
</ul>
<p>Metrics (<code class="highlighter-rouge">Metric&lt;N&gt;</code>) plug in to this static system and only provide behaviour that’s executed by the metrics computer.
Internally, metric keys (<code class="highlighter-rouge">MetricKey&lt;N&gt;</code>) are parameterized with their version (<code class="highlighter-rouge">MetricVersion</code>) to index memoisation
maps (see <code class="highlighter-rouge">ParameterizedMetricKey&lt;N&gt;</code>). This allows us to memoise several versions of the same metric without conflict.</p>
<p>At the very least, a metrics framework has those two components and is just a convenient way to compute and memoize
metrics on a single file. The expressive power of metrics can be improved by implementing <em>signature matching</em> capabilities,
which allows a metric to count signatures matching a specific pattern (a mask) over a whole class. This was originally
designed to work across files, given a working usage resolution. However, making that work with incremental analysis is
harder than it looks, and has been rescheduled to another project.</p>
<h3 id="abstraction-layer">Abstraction layer</h3>
<p>As you may have seen, most of the functionality of the first two components are abstracted into <code class="highlighter-rouge">pmd-core</code>. This
allows us to implement new metrics frameworks quite quickly. These abstract components are parameterized by the
node types of the class and operation AST nodes. Moreover, it makes the external behaviour of the framework very
stable across languages, yet each component can easily be customized by adding methods or overriding existing ones.</p>
<p>The signature matching aspect is framed by generic interfaces, but it can’t really be abstracted more
than that. The info given in the signatures is usually very language specific, as it includes info about e.g.
visibility modifiers. So more work is required to implement that, but it can already be used to implement
sophisticated metrics, that already give access to detection strategies.</p>
<h2 id="implementation-of-a-new-framework">Implementation of a new framework</h2>
<h3 id="1-groundwork">1. Groundwork</h3>
<ul>
<li>Create a class implementing <code class="highlighter-rouge">QualifiedName</code>. This implementation must be tailored to the target language so
that it can indentify unambiguously any class and operation in the analysed project. You
must implement <code class="highlighter-rouge">equals</code>, <code class="highlighter-rouge">hashCode</code> and <code class="highlighter-rouge">toString</code>.
<a href="https://github.com/pmd/pmd/blob/master/pmd-java/src/main/java/net/sourceforge/pmd/lang/java/ast/JavaQualifiedName.java">Example</a></li>
<li>Determine the AST nodes that correspond to class and method declaration in your language. These types are
referred hereafter as <code class="highlighter-rouge">T</code> and <code class="highlighter-rouge">O</code>, respectively. Both these types must implement the interface <code class="highlighter-rouge">QualifiableNode</code>,
which means they must expose a <code class="highlighter-rouge">getQualifiedName</code> method to give access to their qualified name.</li>
</ul>
<h3 id="2-implement-the-façade">2. Implement the façade</h3>
<ul>
<li>Create a class extending <code class="highlighter-rouge">AbstractMetricsComputer&lt;T, O&gt;</code>. This object will be responsible for calculating metrics
given a memoizer, a node and info about the metric. Typically, this object is stateless so you might as well make it
a singleton.</li>
<li>Create a class extending <code class="highlighter-rouge">BasicProjectMemoizer&lt;T, O&gt;</code>. There’s no abstract functionality to implement.
<a href="https://github.com/pmd/pmd/blob/master/pmd-java/src/main/java/net/sourceforge/pmd/lang/java/metrics/JavaProjectMemoizer.java">Example</a>
<a href="https://github.com/pmd/pmd/blob/master/pmd-java/src/main/java/net/sourceforge/pmd/lang/java/metrics/JavaMetricsComputer.java">Example</a></li>
<li>Create a class extending <code class="highlighter-rouge">AbstractMetricsFacade&lt;T, O&gt;</code>. This class needs a reference to your <code class="highlighter-rouge">ProjectMemoizer</code> and
your <code class="highlighter-rouge">MetricsComputer</code>. It backs the real end user façade, and handles user provided parameters before delegating to
your <code class="highlighter-rouge">MetricsComputer</code>.
<a href="https://github.com/pmd/pmd/blob/master/pmd-java/src/main/java/net/sourceforge/pmd/lang/java/metrics/JavaMetricsFacade.java">Example</a></li>
<li>Create the static façade of your framework. This one has an instance of your <code class="highlighter-rouge">MetricsFaçade</code> object and delegates
static methods to that instance.
<a href="https://github.com/pmd/pmd/blob/master/pmd-java/src/main/java/net/sourceforge/pmd/lang/java/metrics/JavaMetrics.java">Example</a></li>
<li>Create classes <code class="highlighter-rouge">AbstractOperationMetric</code> and <code class="highlighter-rouge">AbstractClassMetric</code>. These must implement <code class="highlighter-rouge">Metric&lt;T&gt;</code> and
<code class="highlighter-rouge">Metric&lt;O&gt;</code>, respectively. They typically provide defaults for the <code class="highlighter-rouge">supports</code> method of each metric.
<a href="https://github.com/pmd/pmd/blob/master/pmd-java/src/main/java/net/sourceforge/pmd/lang/java/metrics/impl/AbstractJavaOperationMetric.java">Example</a></li>
<li>Create enums <code class="highlighter-rouge">ClassMetricKey</code> and <code class="highlighter-rouge">OperationMetricKey</code>. These must implement <code class="highlighter-rouge">MetricKey&lt;T&gt;</code> and <code class="highlighter-rouge">MetricKey&lt;O&gt;</code>. The
enums list all available metric keys for your language.
<a href="https://github.com/pmd/pmd/blob/master/pmd-java/src/main/java/net/sourceforge/pmd/lang/java/metrics/api/JavaOperationMetricKey.java">Example</a></li>
<li>Create metrics by extending your base classes, reference them in your enums, and you can start using them with your
façade!</li>
</ul>
<h3 id="optional-signature-matching">Optional: Signature matching</h3>
<p>You can match the signature of anything: method, field, class, package… It depends on what’s useful for you.
Suppose you want to be able to match signatures for nodes of type <code class="highlighter-rouge">N</code>. What you have to do then is the following:</p>
<ul>
<li>Create a class implementing the interface <code class="highlighter-rouge">Signature&lt;N&gt;</code>. Signatures describe basic information about the node,
which typically includes most of the modifiers they declare (eg visibility, abstract or virtual, etc.).
It’s up to you to define the right level of detail, depending on the accuracy of the pattern matching required.</li>
<li>Make type <code class="highlighter-rouge">N</code> implement <code class="highlighter-rouge">SignedNode&lt;N&gt;</code>. This makes the node capable of giving its signature. Factory methods to
build a <code class="highlighter-rouge">Signature&lt;N&gt;</code> from a <code class="highlighter-rouge">N</code> are a good idea.</li>
<li>Create signature masks. A mask is an object that matches some signatures based on their features. For example, with
the Java framework, you can build a <code class="highlighter-rouge">JavaOperationSigMask</code> that matches all method signatures with visibility
<code class="highlighter-rouge">public</code>. A sigmask implements <code class="highlighter-rouge">SigMask&lt;S&gt;</code>, where <code class="highlighter-rouge">S</code> is the type of signature your mask handles.</li>
<li>Create utility methods in your abstract class metric class to count signatures matching a specific mask.
<a href="https://github.com/pmd/pmd/blob/master/pmd-java/src/main/java/net/sourceforge/pmd/lang/java/metrics/AbstractJavaClassMetric.java#L50">Example</a></li>
</ul>
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