{"title":"Prediction of project problem effects on software risk factors","authors":"M. Ozgur Cingiz, Ahmet Unudulmaz, O. Kalipsiz","doi":"10.1109/SoMeT.2013.6645641","DOIUrl":null,"url":null,"abstract":"Software risks can be defined as uncertainty and loss in project process. Software risk management consists of risk identification, estimation, refinement, mitigation, monitoring and maintenance steps. In our study we focus on prediction of project problem effects that can cause loss in software project in terms of their values on risk factors and also we want to rank our risk factors to observe how they can give detail about project problem effects separately. For these purpose five classification methods for prediction of problem impact and two filter feature selection methods for ranking importance of risk factors are used in this study.","PeriodicalId":447065,"journal":{"name":"2013 IEEE 12th International Conference on Intelligent Software Methodologies, Tools and Techniques (SoMeT)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 12th International Conference on Intelligent Software Methodologies, Tools and Techniques (SoMeT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SoMeT.2013.6645641","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Software risks can be defined as uncertainty and loss in project process. Software risk management consists of risk identification, estimation, refinement, mitigation, monitoring and maintenance steps. In our study we focus on prediction of project problem effects that can cause loss in software project in terms of their values on risk factors and also we want to rank our risk factors to observe how they can give detail about project problem effects separately. For these purpose five classification methods for prediction of problem impact and two filter feature selection methods for ranking importance of risk factors are used in this study.