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Detection and Analysis of Behavioral T-patterns in Debugging Activities

Abstract : A growing body of research in empirical software engineering applies recurrent patterns analysis in order to make sense of the developers' behavior during their interactions with IDEs. However, the exploration of hidden real-time structures of programming behavior remains a challenging task. In this paper, we investigate the presence of temporal be-havioral patterns (T-patterns) in debugging activities using the THEME software. Our preliminary exploratory results show that debugging activities are strongly correlated with code editing, file handling, window interactions and other general types of programming activities. The validation of our T-patterns detection approach demonstrates that debug-ging activities are performed on the basis of repetitive and well-organized behavioral events. Furthermore, we identify a large set of T-patterns that associate debugging activities with build success, which corroborates the positive impact of debugging practices on software development.
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Submitted on : Wednesday, April 11, 2018 - 8:28:31 AM
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César Soto-Valero, Johann Bourcier, Benoit Baudry. Detection and Analysis of Behavioral T-patterns in Debugging Activities. MSR 2018 - Mining Software Repositories, May 2018, Gothenburg, Sweden. pp.1-4, ⟨10.1145/3196398.3196452⟩. ⟨hal-01763369⟩



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