{"title":"通过软件工件总结改进可追溯性链接恢复方法","authors":"Jairo Aponte, Andrian Marcus","doi":"10.1145/1987856.1987867","DOIUrl":null,"url":null,"abstract":"Analyzing candidate traceability links is a difficult, time consuming and error prone task, as it usually requires a detailed study of a long list of software artifacts of various kinds. One option to alleviate this problem is to select the most important features of the software artifacts that the developers would investigate. We discuss in this position paper how text summarization techniques could be used to address this problem. The potential gains in using summaries are both in terms of time and correctness of the traceability link recovery process.","PeriodicalId":116816,"journal":{"name":"TEFSE '11","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Improving traceability link recovery methods through software artifact summarization\",\"authors\":\"Jairo Aponte, Andrian Marcus\",\"doi\":\"10.1145/1987856.1987867\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Analyzing candidate traceability links is a difficult, time consuming and error prone task, as it usually requires a detailed study of a long list of software artifacts of various kinds. One option to alleviate this problem is to select the most important features of the software artifacts that the developers would investigate. We discuss in this position paper how text summarization techniques could be used to address this problem. The potential gains in using summaries are both in terms of time and correctness of the traceability link recovery process.\",\"PeriodicalId\":116816,\"journal\":{\"name\":\"TEFSE '11\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"TEFSE '11\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1987856.1987867\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"TEFSE '11","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1987856.1987867","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improving traceability link recovery methods through software artifact summarization
Analyzing candidate traceability links is a difficult, time consuming and error prone task, as it usually requires a detailed study of a long list of software artifacts of various kinds. One option to alleviate this problem is to select the most important features of the software artifacts that the developers would investigate. We discuss in this position paper how text summarization techniques could be used to address this problem. The potential gains in using summaries are both in terms of time and correctness of the traceability link recovery process.
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