Roberta Arcoverde, Isela Macia Bertran, Alessandro F. Garcia, Arndt von Staa
{"title":"自动检测与架构相关的代码异常","authors":"Roberta Arcoverde, Isela Macia Bertran, Alessandro F. Garcia, Arndt von Staa","doi":"10.1109/RSSE.2012.6233419","DOIUrl":null,"url":null,"abstract":"Software architecture degradation is a longstanding problem in software engineering. Previous studies have shown that certain code anomalies - or patterns of code anomalies - are likely to be harmful to architecture design, although their identification is far from trivial. This study presents a system for not only detecting architecturally-relevant code anomalies, but also helping developers to prioritize their removal by ranking them. We detect code anomaly patterns based on static analysis that also exploit architecture information.","PeriodicalId":193223,"journal":{"name":"2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":"{\"title\":\"Automatically detecting architecturally-relevant code anomalies\",\"authors\":\"Roberta Arcoverde, Isela Macia Bertran, Alessandro F. Garcia, Arndt von Staa\",\"doi\":\"10.1109/RSSE.2012.6233419\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Software architecture degradation is a longstanding problem in software engineering. Previous studies have shown that certain code anomalies - or patterns of code anomalies - are likely to be harmful to architecture design, although their identification is far from trivial. This study presents a system for not only detecting architecturally-relevant code anomalies, but also helping developers to prioritize their removal by ranking them. We detect code anomaly patterns based on static analysis that also exploit architecture information.\",\"PeriodicalId\":193223,\"journal\":{\"name\":\"2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"23\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RSSE.2012.6233419\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Third International Workshop on Recommendation Systems for Software Engineering (RSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RSSE.2012.6233419","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Software architecture degradation is a longstanding problem in software engineering. Previous studies have shown that certain code anomalies - or patterns of code anomalies - are likely to be harmful to architecture design, although their identification is far from trivial. This study presents a system for not only detecting architecturally-relevant code anomalies, but also helping developers to prioritize their removal by ranking them. We detect code anomaly patterns based on static analysis that also exploit architecture information.