{"title":"文本搜索是一种有效的故障定位方法吗","authors":"Vibha Sinha, Senthil Mani, Debdoot Mukherjee","doi":"10.1145/2384716.2384770","DOIUrl":null,"url":null,"abstract":"There has been widespread interest in both academia and industry around techniques to help in fault localization. Much of this work leverages static or dynamic code analysis and hence is constrained by the programming language used or presence of test cases. In order to provide more generically applicable techniques, recent work has focused on devising text search based approaches that recommend source files which a developer can modify to fix a bug. Text search may be used for fault localization in either of the following ways. We can search a repository of past bugs with the bug description to find similar bugs and recommend the source files that were modified to fix those bugs. Alternately, we can directly search the code repository to find source files that share words with the bug report text. Few interesting questions come to mind when we consider applying these text-based search techniques in real projects. For example, would searching on past fixed bugs yield better results than searching on code? What is the accuracy one can expect? Would giving preference to code words in the bug report better the search results? In this paper, we apply variants of text-search on four open source projects and compare the impact of different design considerations on search efficacy.","PeriodicalId":194590,"journal":{"name":"ACM SIGPLAN International Conference on Systems, Programming, Languages and Applications: Software for Humanity","volume":"74 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Is text search an effective approach for fault localization: a practitioners perspective\",\"authors\":\"Vibha Sinha, Senthil Mani, Debdoot Mukherjee\",\"doi\":\"10.1145/2384716.2384770\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There has been widespread interest in both academia and industry around techniques to help in fault localization. Much of this work leverages static or dynamic code analysis and hence is constrained by the programming language used or presence of test cases. In order to provide more generically applicable techniques, recent work has focused on devising text search based approaches that recommend source files which a developer can modify to fix a bug. Text search may be used for fault localization in either of the following ways. We can search a repository of past bugs with the bug description to find similar bugs and recommend the source files that were modified to fix those bugs. Alternately, we can directly search the code repository to find source files that share words with the bug report text. Few interesting questions come to mind when we consider applying these text-based search techniques in real projects. For example, would searching on past fixed bugs yield better results than searching on code? What is the accuracy one can expect? Would giving preference to code words in the bug report better the search results? In this paper, we apply variants of text-search on four open source projects and compare the impact of different design considerations on search efficacy.\",\"PeriodicalId\":194590,\"journal\":{\"name\":\"ACM SIGPLAN International Conference on Systems, Programming, Languages and Applications: Software for Humanity\",\"volume\":\"74 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM SIGPLAN International Conference on Systems, Programming, Languages and Applications: Software for Humanity\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2384716.2384770\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM SIGPLAN International Conference on Systems, Programming, Languages and Applications: Software for Humanity","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2384716.2384770","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Is text search an effective approach for fault localization: a practitioners perspective
There has been widespread interest in both academia and industry around techniques to help in fault localization. Much of this work leverages static or dynamic code analysis and hence is constrained by the programming language used or presence of test cases. In order to provide more generically applicable techniques, recent work has focused on devising text search based approaches that recommend source files which a developer can modify to fix a bug. Text search may be used for fault localization in either of the following ways. We can search a repository of past bugs with the bug description to find similar bugs and recommend the source files that were modified to fix those bugs. Alternately, we can directly search the code repository to find source files that share words with the bug report text. Few interesting questions come to mind when we consider applying these text-based search techniques in real projects. For example, would searching on past fixed bugs yield better results than searching on code? What is the accuracy one can expect? Would giving preference to code words in the bug report better the search results? In this paper, we apply variants of text-search on four open source projects and compare the impact of different design considerations on search efficacy.