{"title":"关于提交的性质","authors":"Lile Hattori, Michele Lanza","doi":"10.1109/ASEW.2008.4686322","DOIUrl":null,"url":null,"abstract":"Information contained in versioning system commits has been frequently used to support software evolution research. Concomitantly, some researchers have tried to relate commits to certain activities, e.g., large commits are more likely to be originated from code management activities, while small ones are related to development activities. However, these characterizations are vague, because there is no consistent definition of what is a small or a large commit. In this paper, we study the nature of commits in two dimensions. First, we define the size of commits in terms of number of files, and then we classify commits based on the content of their comments. To perform this study, we use the history log of nine large open source projects.","PeriodicalId":215885,"journal":{"name":"2008 23rd IEEE/ACM International Conference on Automated Software Engineering - Workshops","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"129","resultStr":"{\"title\":\"On the nature of commits\",\"authors\":\"Lile Hattori, Michele Lanza\",\"doi\":\"10.1109/ASEW.2008.4686322\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Information contained in versioning system commits has been frequently used to support software evolution research. Concomitantly, some researchers have tried to relate commits to certain activities, e.g., large commits are more likely to be originated from code management activities, while small ones are related to development activities. However, these characterizations are vague, because there is no consistent definition of what is a small or a large commit. In this paper, we study the nature of commits in two dimensions. First, we define the size of commits in terms of number of files, and then we classify commits based on the content of their comments. To perform this study, we use the history log of nine large open source projects.\",\"PeriodicalId\":215885,\"journal\":{\"name\":\"2008 23rd IEEE/ACM International Conference on Automated Software Engineering - Workshops\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"129\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 23rd IEEE/ACM International Conference on Automated Software Engineering - Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASEW.2008.4686322\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 23rd IEEE/ACM International Conference on Automated Software Engineering - Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASEW.2008.4686322","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Information contained in versioning system commits has been frequently used to support software evolution research. Concomitantly, some researchers have tried to relate commits to certain activities, e.g., large commits are more likely to be originated from code management activities, while small ones are related to development activities. However, these characterizations are vague, because there is no consistent definition of what is a small or a large commit. In this paper, we study the nature of commits in two dimensions. First, we define the size of commits in terms of number of files, and then we classify commits based on the content of their comments. To perform this study, we use the history log of nine large open source projects.