Adithya Raghuraman, Truong Ho-Quang, M. Chaudron, A. Serebrenik, Bogdan Vasilescu
{"title":"Does UML Modeling Associate with Lower Defect Proneness?: A Preliminary Empirical Investigation","authors":"Adithya Raghuraman, Truong Ho-Quang, M. Chaudron, A. Serebrenik, Bogdan Vasilescu","doi":"10.1109/MSR.2019.00024","DOIUrl":null,"url":null,"abstract":"The benefits of modeling the design to improve the quality and maintainability of software systems have long been advocated and recognized. Yet, the empirical evidence on this remains scarce. In this paper, we fill this gap by reporting on an empirical study of the relationship between UML modeling and software defect proneness in a large sample of open-source GitHub projects. Using statistical modeling, and controlling for confounding variables, we show that projects containing traces of UML models in their repositories experience, on average, a statistically minorly different number of software defects (as mined from their issue trackers) than projects without traces of UML models.","PeriodicalId":6706,"journal":{"name":"2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR)","volume":"58 1","pages":"101-104"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MSR.2019.00024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
The benefits of modeling the design to improve the quality and maintainability of software systems have long been advocated and recognized. Yet, the empirical evidence on this remains scarce. In this paper, we fill this gap by reporting on an empirical study of the relationship between UML modeling and software defect proneness in a large sample of open-source GitHub projects. Using statistical modeling, and controlling for confounding variables, we show that projects containing traces of UML models in their repositories experience, on average, a statistically minorly different number of software defects (as mined from their issue trackers) than projects without traces of UML models.