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Displaying 1-4 out of 4 total
Learning from Open-Source Projects: An Empirical Study on Defect Prediction
2013 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)
By Zhimin He,Fayola Peters,Tim Menzies, Ye Yang
Issue Date:October 2013
The fundamental issue in cross project defect prediction is selecting the most appropriate training data for creating quality defect predictors. Another concern is whether historical data of open-source projects can be used to create quality predictors for...
Balancing Privacy and Utility in Cross-Company Defect Prediction
IEEE Transactions on Software Engineering
By Fayola Peters,Tim Menzies,Liang Gong,Hongyu Zhang
Issue Date:August 2013
Background: Cross-company defect prediction (CCDP) is a field of study where an organization lacking enough local data can use data from other organizations for building defect predictors. To support CCDP, data must be shared. Such shared data must be priv...
Applications of Simulation and AI Search: Assessing the Relative Merits of Agile vs Traditional Software Development
Automated Software Engineering, International Conference on
By Bryan Lemon, Aaron Riesbeck, Tim Menzies, Justin Price, Joseph D'Alessandro, Rikard Carlsson, Tomi Prifiti, Fayola Peters, Hiuhua Lu, Dan Port
Issue Date:November 2009
This paper augments Boehm-Turner's model of agile and plan-based software development augmented with an AI search algorithm. The AI search finds the key factors that predict for the success of agile or traditional plan-based software developments. Accordin...
Better cross company defect prediction
2013 10th IEEE Working Conference on Mining Software Repositories (MSR 2013)
By Fayola Peters,Tim Menzies,Andrian Marcus
Issue Date:May 2013
How can we find data for quality prediction? Early in the life cycle, projects may lack the data needed to build such predictors. Prior work assumed that relevant training data was found nearest to the local project. But is this the best approach? This pap...
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