{"title":"Predicting component failures at design time","authors":"Adrian Schröter, Thomas Zimmermann, A. Zeller","doi":"10.1145/1159733.1159739","DOIUrl":null,"url":null,"abstract":"How do design decisions impact the quality of the resulting software? In an empirical study of 52 ECLIPSE plug-ins, we found that the software design as well as past failure history, can be used to build models which accurately predict failure-prone components in new programs. Our prediction only requires usage relationships between components, which are typically defined in the design phase; thus, designers can easily explore and assess design alternatives in terms of predicted quality. In the ECLIPSE study, 90% of the 5% most failure-prone components, as predicted by our model from design data, turned out to actually produce failures later; a random guess would have predicted only 33%.","PeriodicalId":201305,"journal":{"name":"International Symposium on Empirical Software Engineering","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"186","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on Empirical Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1159733.1159739","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 186
Abstract
How do design decisions impact the quality of the resulting software? In an empirical study of 52 ECLIPSE plug-ins, we found that the software design as well as past failure history, can be used to build models which accurately predict failure-prone components in new programs. Our prediction only requires usage relationships between components, which are typically defined in the design phase; thus, designers can easily explore and assess design alternatives in terms of predicted quality. In the ECLIPSE study, 90% of the 5% most failure-prone components, as predicted by our model from design data, turned out to actually produce failures later; a random guess would have predicted only 33%.