{"title":"哪种重构能降低Bug率?","authors":"Idan Amit, D. Feitelson","doi":"10.1145/3345629.3345631","DOIUrl":null,"url":null,"abstract":"We present a methodology to identify refactoring operations that reduce the bug rate in the code. The methodology is based on comparing the bug fixing rate in certain time windows before and after the refactoring. We analyzed 61,331 refactor commits from 1,531 large active GitHub projects. When comparing three-month windows, the bug rate is substantially reduced in 17% of the files of analyzed refactors, compared to 12% of the files in random commits. Within this group, implementing 'todo's provides the most benefits. Certain operations like reuse, upgrade, and using enum and namespaces are also especially beneficial.","PeriodicalId":424201,"journal":{"name":"Proceedings of the Fifteenth International Conference on Predictive Models and Data Analytics in Software Engineering","volume":"177 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Which Refactoring Reduces Bug Rate?\",\"authors\":\"Idan Amit, D. Feitelson\",\"doi\":\"10.1145/3345629.3345631\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a methodology to identify refactoring operations that reduce the bug rate in the code. The methodology is based on comparing the bug fixing rate in certain time windows before and after the refactoring. We analyzed 61,331 refactor commits from 1,531 large active GitHub projects. When comparing three-month windows, the bug rate is substantially reduced in 17% of the files of analyzed refactors, compared to 12% of the files in random commits. Within this group, implementing 'todo's provides the most benefits. Certain operations like reuse, upgrade, and using enum and namespaces are also especially beneficial.\",\"PeriodicalId\":424201,\"journal\":{\"name\":\"Proceedings of the Fifteenth International Conference on Predictive Models and Data Analytics in Software Engineering\",\"volume\":\"177 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Fifteenth International Conference on Predictive Models and Data Analytics in Software Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3345629.3345631\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Fifteenth International Conference on Predictive Models and Data Analytics in Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3345629.3345631","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We present a methodology to identify refactoring operations that reduce the bug rate in the code. The methodology is based on comparing the bug fixing rate in certain time windows before and after the refactoring. We analyzed 61,331 refactor commits from 1,531 large active GitHub projects. When comparing three-month windows, the bug rate is substantially reduced in 17% of the files of analyzed refactors, compared to 12% of the files in random commits. Within this group, implementing 'todo's provides the most benefits. Certain operations like reuse, upgrade, and using enum and namespaces are also especially beneficial.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
