Huzefa H. Kagdi, Jonathan I. Maletic, Bonita Sharif
{"title":"挖掘软件存储库的可追溯性链接","authors":"Huzefa H. Kagdi, Jonathan I. Maletic, Bonita Sharif","doi":"10.1109/ICPC.2007.28","DOIUrl":null,"url":null,"abstract":"An approach to recover/discover traceability links between software artifacts via the examination of a software system's version history is presented. A heuristic-based approach that uses sequential-pattern mining is applied to the commits in software repositories for uncovering highly frequent co-changing sets of artifacts (e.g., source code and documentation). If different types of files are committed together with high frequency then there is a high probability that they have a traceability link between them. The approach is evaluated on a number of versions of the open source system KDE. As a validation step, the discovered links are used to predict similar changes in the newer versions of the same system. The results show highly precision predictions of certain types of traceability links.","PeriodicalId":135871,"journal":{"name":"15th IEEE International Conference on Program Comprehension (ICPC '07)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"103","resultStr":"{\"title\":\"Mining software repositories for traceability links\",\"authors\":\"Huzefa H. Kagdi, Jonathan I. Maletic, Bonita Sharif\",\"doi\":\"10.1109/ICPC.2007.28\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An approach to recover/discover traceability links between software artifacts via the examination of a software system's version history is presented. A heuristic-based approach that uses sequential-pattern mining is applied to the commits in software repositories for uncovering highly frequent co-changing sets of artifacts (e.g., source code and documentation). If different types of files are committed together with high frequency then there is a high probability that they have a traceability link between them. The approach is evaluated on a number of versions of the open source system KDE. As a validation step, the discovered links are used to predict similar changes in the newer versions of the same system. The results show highly precision predictions of certain types of traceability links.\",\"PeriodicalId\":135871,\"journal\":{\"name\":\"15th IEEE International Conference on Program Comprehension (ICPC '07)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"103\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"15th IEEE International Conference on Program Comprehension (ICPC '07)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPC.2007.28\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"15th IEEE International Conference on Program Comprehension (ICPC '07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPC.2007.28","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mining software repositories for traceability links
An approach to recover/discover traceability links between software artifacts via the examination of a software system's version history is presented. A heuristic-based approach that uses sequential-pattern mining is applied to the commits in software repositories for uncovering highly frequent co-changing sets of artifacts (e.g., source code and documentation). If different types of files are committed together with high frequency then there is a high probability that they have a traceability link between them. The approach is evaluated on a number of versions of the open source system KDE. As a validation step, the discovered links are used to predict similar changes in the newer versions of the same system. The results show highly precision predictions of certain types of traceability links.