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- W2894876581 abstract "Background: Researchers oftentimes measure quality metrics only in the changed files when analyzing software evolution over commit-history. This approach is not suitable for compilation and using program analysis techniques that require byte-code. At the same time, compiling the whole software not only is costly but may also leave us with many uncompilable and unanalyzed revisions. Aims: We intend to demonstrate if analyzing changes in a module results in achieving a high compilation ratio and a better understanding of software quality evolution. Method: We conduct a large-scale multi-perspective empirical study on 37838 distinct revisions of the core module of 68 systems across Apache, Google, and Netflix to assess their compilability and identify when the software is uncompilable as a result of a developer's fault. We study the characteristics of uncompilable revisions and analyze compilable ones to understand the impact of developers on software quality. Results: We achieve high compilation ratios: 98.4% for Apache, 99.0% for Google, and 94.3% for Netflix. We identify 303 sequences of uncompile commits and create a model to predict uncompilability based on commit metadata with an F1-score of 0.89 and an AUC of 0.96. We identify statistical differences between the impact of affiliated and external developers of organizations. Conclusions: Focusing on a module results in a more complete and accurate software evolution analysis, reduces the cost and complexity, and facilitates manual inspection." @default.
- W2894876581 created "2018-10-12" @default.
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- W2894876581 date "2018-10-11" @default.
- W2894876581 modified "2023-09-28" @default.
- W2894876581 title "A scalable and efficient approach for compiling and analyzing commit history" @default.
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- W2894876581 doi "https://doi.org/10.1145/3239235.3239237" @default.
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