{"title":"Mining micro-practices from operational data","authors":"Minghui Zhou, A. Mockus","doi":"10.1145/2635868.2666611","DOIUrl":null,"url":null,"abstract":"Micro-practices are actual (and usually undocumented or incorrectly documented) activity patterns used by individuals or projects to accomplish basic software development tasks, such as writing code, testing, triaging bugs, or mentoring newcomers. The operational data in software repositories presents the tantalizing possibility to discover such fine-scale behaviors and use them to understand and improve software development. We propose a large-scale evidence-based approach to accomplish this by first creating a mirror of the projects in the open source universe. The next step would involve the inductive generalization from in-depth studies of specific projects from one side and the categorization of micro-practices in the entire universe from the other side.","PeriodicalId":250543,"journal":{"name":"Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2635868.2666611","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Micro-practices are actual (and usually undocumented or incorrectly documented) activity patterns used by individuals or projects to accomplish basic software development tasks, such as writing code, testing, triaging bugs, or mentoring newcomers. The operational data in software repositories presents the tantalizing possibility to discover such fine-scale behaviors and use them to understand and improve software development. We propose a large-scale evidence-based approach to accomplish this by first creating a mirror of the projects in the open source universe. The next step would involve the inductive generalization from in-depth studies of specific projects from one side and the categorization of micro-practices in the entire universe from the other side.