Proceedings of the 2006 International Workshop on Mining Software Repositories 2006
DOI: 10.1145/1137983.1138011
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Are refactorings less error-prone than other changes?

Abstract: Refactorings are program transformations which should preserve the program behavior. Consequently, we expect that during phases when there are mostly refactorings in the change history of a system, only few new bugs are introduced. For our case study we analyzed the version histories of several open source systems and reconstructed the refactorings performed. Furthermore, we obtained bug reports from various sources depending on the system. Based on this data we identify phases when the above hypothesis holds … Show more

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Cited by 69 publications
(65 citation statements)
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References 9 publications
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“…Weißergerber and Diehl [93] presented a technique for identifying changes that are refactorings. The line-based differences of files in a CVS commit were mapped to the differences in syntactic entities (e.g., class and method names).…”
Section: Identification Of Refactorings In Changesmentioning
confidence: 99%
“…Weißergerber and Diehl [93] presented a technique for identifying changes that are refactorings. The line-based differences of files in a CVS commit were mapped to the differences in syntactic entities (e.g., class and method names).…”
Section: Identification Of Refactorings In Changesmentioning
confidence: 99%
“…Refactoring leads to change in the code which may increase the bugs if the software is not properly designed according to design pattern rules. Weißgerber and Diehl (2006) concluded that the number of bug report increases after refactoring. Researchers have identified the approaches for refactoring for given code smell but still determining which code needs to be refactored on priority is still matter of research.…”
Section: Frame Work For Ranking the Components As Per The Refactoringmentioning
confidence: 99%
“…Recording dynamic information of a program can provide us with sufficient knowledge about message exchanges and modular interactions during the program execution period [40][41] [19]. However, this technique faces two major issues: (i) the overwhelming volume of tracing data [29][36] and (ii) incomplete coverage of the code [25] [13]. In order to have a full coverage of the target code during each experimental session, this approach focuses on a specific set of observable system functionalities and behaviors.…”
Section: Architecture Decomposition Partitionmentioning
confidence: 99%