Semantic web enabled software analysis

  • Authors:

  • Jonas Tappolet;Christoph Kiefer;Abraham Bernstein

  • Affiliations:

  • Dynamic and Distributed Information Systems, University of Zurich, Switzerland;Dynamic and Distributed Information Systems, University of Zurich, Switzerland;Dynamic and Distributed Information Systems, University of Zurich, Switzerland

  • Venue:
  • Web Semantics: Science, Services and Agents on the World Wide Web
  • Year:
  • 2010

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Abstract

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 formats based on OWL. EvoOnt models software design, release history information, and bug-tracking meta-data. Since OWL describes the semantics of the data, EvoOnt (1) is easily extendible, (2) can be processed with many existing tools, and (3) allows to derive assertions through its inherent Description Logic reasoning capabilities. The contribution of this paper is that it introduces a novel software evolution ontology that vastly simplifies typical software evolution analysis tasks. In detail, we show the usefulness of EvoOnt by repeating selected software evolution and analysis experiments from the 2004-2007 Mining Software Repositories Workshops (MSR). We demonstrate that if the data used for analysis were available in EvoOnt then the analyses in 75% of the papers at MSR could be reduced to one or at most two simple queries within off-the-shelf SPARQL tools. In addition, we present how the inherent capabilities of the Semantic Web have the potential of enabling new tasks that have not yet been addressed by software evolution researchers, e.g., due to the complexities of the data integration.