{"title":"Predicting software stability using case-based reasoning","authors":"D. Grosser, H. Sahraoui, Petko Valtchev","doi":"10.1109/ASE.2002.1115033","DOIUrl":null,"url":null,"abstract":"Predicting stability in object-oriented (OO) software, i.e., the ease with which a software item can evolve while preserving its design, is a key feature for software maintenance. We present a novel approach which relies on the case-based reasoning (CBR) paradigm. Thus, to predict the chances of an OO software item breaking downward compatibility, our method uses knowledge of past evolution extracted from different software versions. A comparison of our similarity-based approach to a classical inductive method such as decision trees, is presented which includes various tests on large datasets from existing software.","PeriodicalId":163532,"journal":{"name":"Proceedings 17th IEEE International Conference on Automated Software Engineering,","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"40","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 17th IEEE International Conference on Automated Software Engineering,","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASE.2002.1115033","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 40
Abstract
Predicting stability in object-oriented (OO) software, i.e., the ease with which a software item can evolve while preserving its design, is a key feature for software maintenance. We present a novel approach which relies on the case-based reasoning (CBR) paradigm. Thus, to predict the chances of an OO software item breaking downward compatibility, our method uses knowledge of past evolution extracted from different software versions. A comparison of our similarity-based approach to a classical inductive method such as decision trees, is presented which includes various tests on large datasets from existing software.