Analyzing Software with iSPARQL

One of the most important decisions researchers face when analyzing software systems is the choice of a proper data analysis/exchange format. In this paper, we present EvoOnt, a set of software ontologies and data exchange format based on OWL. EvoOnt models software design, release history information, and bug-tracking meta-data. Since OWL describes the semantics of the data, EvoOnt is (1) easily extendible, (2) comes with many existing tools, and (3) allows to derive assertions through its inherent Description Logic reasoning capabilities. We show the usefulness of EvoOnt in combination with iSPARQL – our SPARQL-based Semantic Web query engine containing similarity joins. Together, EvoOnt and iSPARQL can accomplish a sizable number of tasks sought in software analyzing, such as an assessment of the amount of change between releases, the computation of software design metrics, or the detection of code smells. In a series of experiments with a realworld Java project, we show that a number of software analysis tasks can be reduced to a simple iSPARQL query on an EvoOnt dataset.