{"title":"Predicting Software Field Reliability","authors":"Pete Rotella, S. Chulani, Devesh Goyal","doi":"10.1109/SERIP.2015.20","DOIUrl":null,"url":null,"abstract":"The objective of the work described is to accurately predict, as early as possible in the software lifecycle, how reliably a new software release will behave in the field. The initiative is based on a set of innovative mathematical models that have consistently shown a high correlation between key in-process metrics and our primary customer experience metric, SWDPMH (Software Defects per Million Hours [usage] per Month). We have focused on the three primary dimensions of testing -- incoming, fixed, and backlog bugs. All of the key predictive metrics described here are empirically-derived, and in specific quantitative terms have not previously been documented in the software engineering/quality literature.","PeriodicalId":293394,"journal":{"name":"2015 IEEE/ACM 2nd International Workshop on Software Engineering Research and Industrial Practice","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE/ACM 2nd International Workshop on Software Engineering Research and Industrial Practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SERIP.2015.20","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The objective of the work described is to accurately predict, as early as possible in the software lifecycle, how reliably a new software release will behave in the field. The initiative is based on a set of innovative mathematical models that have consistently shown a high correlation between key in-process metrics and our primary customer experience metric, SWDPMH (Software Defects per Million Hours [usage] per Month). We have focused on the three primary dimensions of testing -- incoming, fixed, and backlog bugs. All of the key predictive metrics described here are empirically-derived, and in specific quantitative terms have not previously been documented in the software engineering/quality literature.
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