{"title":"在设计时预测组件故障","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":"{\"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}","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}
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%.