Software Cost Estimation with Cocomo II with Cdrom
Software Cost Estimation with Cocomo II with Cdrom
Requirements Volatility and Defect Density
ISSRE '99 Proceedings of the 10th International Symposium on Software Reliability Engineering
Building Defect Prediction Models in Practice
IEEE Software
A Novel Method for Early Software Quality Prediction Based on Support Vector Machine
ISSRE '05 Proceedings of the 16th IEEE International Symposium on Software Reliability Engineering
Data Mining Static Code Attributes to Learn Defect Predictors
IEEE Transactions on Software Engineering
Predicting defect-prone software modules using support vector machines
Journal of Systems and Software
On the effectiveness of early life cycle defect prediction with Bayesian Nets
Empirical Software Engineering
Quantitatively managing defects for iterative projects: an industrial experience report in China
ICSP'08 Proceedings of the Software process, 2008 international conference on Making globally distributed software development a success story
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In upgrade project development, Enhancement Requirements (ER, e.g. requirement additions and modifications) introduce new defects to the project. We need to evaluate this impact to help plan later project schedule and resources. Typically, many of the existing prediction technologies estimate defects based on software size or process performance baselines. However, they are limited in estimating the impact of ER on product quality. This paper proposes a novel ER-based defect prediction method using information retrieval (IR) technique and support vector machines (SVM). We analyze the historical data of defects and requirement specifications of actual upgrade projects to establish multiple prediction models to estimate new defects introduced by ER. Then we design two experiments to validate the method and report some preliminary results. The results indicate that our method can provide useful support for impact analysis of requirement evolution in upgrade projects.