Metrics As Scores Dataset: Metrics and Domains From the Qualitas.class Corpus

<p>This dataset was created by extracting software metrics data from the Qualitas.class corpus (Terra et al. 2013; Tempero et al. 2010). Therefore, the principal quantity type is Metric, and the context is given by a system&rsquo;s Domain (e.g., &quot;Game&quot;, &quot;Middleware&quot;, etc.). Some metrics were obtained on program-level, while others are package- or method-level metrics. Most of the metrics in the corpus are of discrete/integral nature. The corpus holds 23 types of pre-computed software metrics for a total of 111 systems which are spread across eleven different domains.</p> <p>This dataset has the following discrete <strong>Features</strong> (Metrics):</p> <ul> <li>CA: Afferent Coupling</li> <li>CE: Efferent Coupling</li> <li>DIT: Depth of Inheritance Tree</li> <li>MLOC: Method Lines of Code</li> <li>NBD: Nested Block Depth</li> <li>NOC: Number of Classes</li> <li>NOF: Number of Attributes</li> <li>NOI: Number of Interfaces</li> <li>NOM: Number of Methods</li> <li>NOP: Number of Packages</li> <li>NORM: Number of Overridden Methods</li> <li>NSC: Number of Children</li> <li>NSF: Number of Static Attributes</li> <li>NSM: Number of Static Methods</li> <li>PAR: Number of Parameters</li> <li>TLOC: Total Lines of Code</li> <li>VG: McCabe Cyclomatic Complexity</li> <li>WMC: Weighted Methods per Class</li> </ul> <p>The following features are continuous:</p> <ul> <li>LCOM: Lack of Cohesion in Methods</li> <li>RMA: Abstractness</li> <li>RMD: Normalized Distance</li> <li>RMI: Instability</li> <li>SIX: Specialization Index</li> </ul> <p>It has a total of 11 <strong>Groups</strong>&nbsp;(Domains): 3D; Graphics; Media, Databases, Diagrams; Visualiz., Games, IDE, Middleware, Parsers; Generators, Progr. Language, SDK, Testing, and Tool.</p>