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Mining Source Code Improvement Patterns from Similar Code Review Works

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dc.contributor.author Ueda, Yuki en
dc.contributor.author Ishio, Takashi en
dc.contributor.author Ihara, Akinori en
dc.contributor.author Matsumoto, Kenichi en
dc.date.accessioned 2019-04-02T00:43:53Z en
dc.date.available 2019-04-02T00:43:53Z en
dc.date.issued 2019 en
dc.identifier.isbn 9781728118055 en
dc.identifier.issn 2572-6587 en
dc.identifier.uri http://hdl.handle.net/10061/13125 en
dc.description IWSC 2019 : 2019 IEEE 13th International Workshop on Software Clones, 24-24 Feb. 2019, Hangzhou, China en
dc.description.abstract Code review is key to ensuring the absence of potential issues in source code. Code reviewers spend a large amount of time to manually check submitted patches based on their knowledge. Since a number of patches sometimes have similar potential issues, code reviewers need to suggest similar source code changes to patch authors. If patch authors notice similar code improvement patterns by themselves before submitting to code review, reviewers’ cost would be reduced. In order to detect similar code changes patterns, this study employs a sequential pattern mining to detect source code improvement patterns that frequently appear in code review history. In a case study using a code review dataset of the OpenStack project, we found that the detected patterns by our proposed approach included effective examples to improve patches without reviewers’ manual check. We also found that the patterns have been changed in time series; our pattern mining approach timely achieves to track the effective code improvement patterns. ja
dc.language.iso en en
dc.publisher IEEE en
dc.rights c Copyright IEEE 2019 en
dc.subject Encoding en
dc.subject Guidelines en
dc.subject Software en
dc.subject Training en
dc.subject History en
dc.subject Manuals en
dc.subject Time series analysis en
dc.subject code review en
dc.subject source code changes en
dc.subject sequential pattern mining en
dc.title Mining Source Code Improvement Patterns from Similar Code Review Works en
dc.type.nii Conference Paper en
dc.textversion author en
dc.identifier.spage 13 en
dc.identifier.epage 19 en
dc.relation.doi 10.1109/IWSC.2019.8665852 en
dc.identifier.NAIST-ID 74653577 en
dc.identifier.NAIST-ID 73292310 en


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