Selecting Open Source Projects for Traceability Case Studies

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Abstract

[Context & Motivation] Once research questions and initial theories have shaped, empirical research typically requires to select cases to study subsumed ideas. Issue trackers of todays open source systems (OSS) are a gold mine for empirical research, not least to study trace links among the included issue artifacts. [Question / problem] The huge amount of available OSS projects complicates the process of finding suitable cases to support the research goals. Further, simply picking a large number of projects on a random basis does not imply generalizability. Therefore the selection process should be carefully designed. [Principle ideas / results] In this paper we propose a method to choose OSS projects to study trace links found in issue tracking systems. Builds upon purposive sampling and cluster analysis, relevant project characteristics are identified whereas irrelevant information is filtered. Every step of the method is demonstrated on a live example. [Contributions] The proposed strategy selects an information-rich, representative and diverse sample of OSS to perform a traceability case study. Our work may be used as practical guide for other researchers to perform project selection tasks.

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APA

Rath, M., Tomova, M. T., & Mäder, P. (2019). Selecting Open Source Projects for Traceability Case Studies. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11412 LNCS, pp. 229–242). Springer Verlag. https://doi.org/10.1007/978-3-030-15538-4_17

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