{"title":"A model for estimating efforts required to make changes in a software development project","authors":"K. Jeet, R. Dhir","doi":"10.1145/2007052.2007088","DOIUrl":null,"url":null,"abstract":"Research on software quality is as old as software project management. As in other engineering and science disciplines, one approach to understand and control this issue is the use of models. These, quality models have become a well-accepted means to describe and manage software quality. Statistical techniques like Bayesians Networks are used to access and predict software quality by using these quality models. But they are not very accurate. These models lack clarity and operation. In this paper, we propose to develop software model that uses a fuzzy inference approach to access and predict software quality. This model indicates the impact of implementation, quality assurance and analysis on maintenance (an important factor for measuring quality) and the result is studied by the impact on indicator like average efforts required to maintain a project.","PeriodicalId":348804,"journal":{"name":"International Conference on Advances in Computing and Artificial Intelligence","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Advances in Computing and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2007052.2007088","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Research on software quality is as old as software project management. As in other engineering and science disciplines, one approach to understand and control this issue is the use of models. These, quality models have become a well-accepted means to describe and manage software quality. Statistical techniques like Bayesians Networks are used to access and predict software quality by using these quality models. But they are not very accurate. These models lack clarity and operation. In this paper, we propose to develop software model that uses a fuzzy inference approach to access and predict software quality. This model indicates the impact of implementation, quality assurance and analysis on maintenance (an important factor for measuring quality) and the result is studied by the impact on indicator like average efforts required to maintain a project.