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Experiences on Developer Participation and Effort Estimation
Software Engineering and Advanced Applications, Euromicro Conference
By Ekrem Kocaguneli,Ayse T. Misirli,Bora Caglayan,Ayse Bener
Issue Date:September 2011
Software effort estimation is critical for resource allocation and planning. Accurate estimates enable managers to distribute the workload among resources in a balanced manner. The actual workload of developers may be different from the values observed in ...
Merits of using repository metrics in defect prediction for open source projects
Emerging Trends in FLOSS Research and Development, International Workshop on
By Bora Caglayan, Ayse Bener, Stefan Koch
Issue Date:May 2009
Many corporate code developers are the beta testers of open source software.They continue testing until they are sure that they have a stable version to build their code on. In this respect defect predictors play a critical role to identify defective parts...
Dione: an integrated measurement and defect prediction solution
Found in: Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering (FSE '12)
By Ayse Bener, Ayse Tosun Misirli, Bora Caglayan, Burak Turhan, Gul Calikli, Turgay Aytac
Issue Date:November 2012
We present an integrated measurement and defect prediction tool: Dione. Our tool enables organizations to measure, monitor, and control product quality through learning based defect prediction. Similar existing tools either provide data collection and anal...
Factors characterizing reopened issues: a case study
Found in: Proceedings of the 8th International Conference on Predictive Models in Software Engineering (PROMISE '12)
By Andriy Miranskyy, Ayse Bener, Ayse Tosun Misirli, Bora Caglayan, Burak Turhan
Issue Date:September 2012
Background: Reopened issues may cause problems in managing software maintenance effort. In order to take actions that will reduce the likelihood of issue reopening the possible causes of bug reopens should be analysed. Aims: In this paper, we investigate p...
Usage of multiple prediction models based on defect categories
Found in: Proceedings of the 6th International Conference on Predictive Models in Software Engineering (PROMISE '10)
By Andriy Miranskyy, Ayse Bener, Ayse Tosun, Bora Caglayan, Nuzio Ruffolo
Issue Date:September 2010
Background: Most of the defect prediction models are built for two purposes: 1) to detect defective and defect-free modules (binary classification), and 2) to estimate the number of defects (regression analysis). It would also be useful to give more inform...
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