{"title":"结合软件工件的文本和结构分析，以实现可追溯性链接恢复","authors":"Collin McMillan, D. Poshyvanyk, Meghan Revelle","doi":"10.1109/TEFSE.2009.5069582","DOIUrl":null,"url":null,"abstract":"Existing methods for recovering traceability links among software documentation artifacts analyze textual similarities among these artifacts. It may be the case, however, that related documentation elements share little terminology or phrasing. This paper presents a technique for indirectly recovering these traceability links in requirements documentation by combining textual with structural information as we conjecture that related requirements share related source code elements. A preliminary case study indicates that our combined approach improves the precision and recall of recovering relevant links among documents as compared to stand-alone methods based solely on analyzing textual similarities.","PeriodicalId":150917,"journal":{"name":"2009 ICSE Workshop on Traceability in Emerging Forms of Software Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"104","resultStr":"{\"title\":\"Combining textual and structural analysis of software artifacts for traceability link recovery\",\"authors\":\"Collin McMillan, D. Poshyvanyk, Meghan Revelle\",\"doi\":\"10.1109/TEFSE.2009.5069582\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Existing methods for recovering traceability links among software documentation artifacts analyze textual similarities among these artifacts. It may be the case, however, that related documentation elements share little terminology or phrasing. This paper presents a technique for indirectly recovering these traceability links in requirements documentation by combining textual with structural information as we conjecture that related requirements share related source code elements. A preliminary case study indicates that our combined approach improves the precision and recall of recovering relevant links among documents as compared to stand-alone methods based solely on analyzing textual similarities.\",\"PeriodicalId\":150917,\"journal\":{\"name\":\"2009 ICSE Workshop on Traceability in Emerging Forms of Software Engineering\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"104\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 ICSE Workshop on Traceability in Emerging Forms of Software Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TEFSE.2009.5069582\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 ICSE Workshop on Traceability in Emerging Forms of Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TEFSE.2009.5069582","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Combining textual and structural analysis of software artifacts for traceability link recovery
Existing methods for recovering traceability links among software documentation artifacts analyze textual similarities among these artifacts. It may be the case, however, that related documentation elements share little terminology or phrasing. This paper presents a technique for indirectly recovering these traceability links in requirements documentation by combining textual with structural information as we conjecture that related requirements share related source code elements. A preliminary case study indicates that our combined approach improves the precision and recall of recovering relevant links among documents as compared to stand-alone methods based solely on analyzing textual similarities.
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