Software reusability dataset based on static analysis metrics and reuse rate information

The widely adopted component-based development paradigm considers the reuse of proper software components as a primary criterion for successful software development. As a result, various research efforts are directed towards evaluating the extent to which a software component is reusable. Prior effo...

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Veröffentlicht in:Data in brief 2019-12, Vol.27, p.104687-104687, Article 104687
Hauptverfasser: Papamichail, Michail D., Diamantopoulos, Themistoklis, Symeonidis, Andreas L.
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Sprache:eng
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Zusammenfassung:The widely adopted component-based development paradigm considers the reuse of proper software components as a primary criterion for successful software development. As a result, various research efforts are directed towards evaluating the extent to which a software component is reusable. Prior efforts follow expert-based approaches, however the continuously increasing open-source software initiative allows the introduction of data-driven alternatives. In this context we have generated a dataset that harnesses information residing in online code hosting facilities and introduces the actual reuse rate of software components as a measure of their reusability. To do so, we have analyzed the most popular projects included in the maven registry and have computed a large number of static analysis metrics at both class and package levels using SourceMeter tool [2] that quantify six major source code properties: complexity, cohesion, coupling, inheritance, documentation and size. For these projects we additionally computed their reuse rate using our self-developed code search engine, AGORA [5]. The generated dataset contains analysis information regarding more than 24,000 classes and 2000 packages, and can, thus, be used as the information basis towards the design and development of data-driven reusability evaluation methodologies. The dataset is related to the research article entitled “Measuring the Reusability of Software Components using Static Analysis Metrics and Reuse Rate Information” [1].
ISSN:2352-3409
2352-3409
DOI:10.1016/j.dib.2019.104687