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An investigation on the feasibility of cross-project defect prediction
Automated Software Engineering, 2011Software defect prediction helps to optimize testing resources allocation by identifying defect-prone modules prior to testing. Most existing models build their prediction capability based on a set of historical data, presumably from the same or similar project settings as those under prediction. However, such historical data is not always available in
Ye Yang, Mingshu Li, Qing Wang
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Cross-project smell-based defect prediction
Soft Computing, 2021Defect prediction is a technique introduced to optimize the testing phase of the software development pipeline by predicting which components in the software may contain defects. Its methodology trains a classifier with data regarding a set of features measured on each component from the target software project to predict whether the component may be ...
Bruno Sotto-Mayor, Meir Kalech
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A Framework for Homogeneous Cross-Project Defect Prediction
International Journal of Software Innovation, 2021Often, the prior defect data of the same project is unavailable; researchers thought whether the defect data of the other projects can be used for prediction. This made cross project defect prediction an open research issue. In this approach, the training data often suffers from class imbalance problem.
Lipika Goel +3 more
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Local modeling approach for cross-project defect prediction
Intelligent Decision Technologies, 2022Prediction approaches used for cross-project defect prediction (CPDP) are usually impractical because of high false alarms, or low detection rate. Instance based data filter techniques that improve the CPDP performance are time-consuming and each time a new test set arrives for prediction the entire filter procedure is repeated. We propose to use local
Nayeem Ahmad Bhat, Sheikh Umar Farooq
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Multi-objective Cross-Project Defect Prediction
2013 IEEE Sixth International Conference on Software Testing, Verification and Validation, 2013Cross-project defect prediction is very appealing because (i) it allows predicting defects in projects for which the availability of data is limited, and (ii) it allows producing generalizable prediction models. However, existing research suggests that cross-project prediction is particularly challenging and, due to heterogeneity of projects ...
Gerardo Canfora +5 more
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A Three-Stage Defect Prediction Model for Cross-Project Defect Prediction
2017 International Conference on Dependable Systems and Their Applications (DSA), 2017Aiming at dealing with the problems of the data deficiency, data high dimensionality in software defect prediction (SDP), this paper proposes a novel three-stage defect prediction model. First we introduced the information flow algorithm (IFA) to do the causality analysis to choose the most representative feature subset.
Song Huang +3 more
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Data Transformation in Cross-project Defect Prediction
Empirical Software Engineering, 2017Software metrics rarely follow a normal distribution. Therefore, software metrics are usually transformed prior to building a defect prediction model. To the best of our knowledge, the impact that the transformation has on cross-project defect prediction models has not been thoroughly explored.
Feng Zhang 0001 +2 more
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Recalling the "imprecision" of cross-project defect prediction
Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering, 2012There has been a great deal of interest in defect prediction: using prediction models trained on historical data to help focus quality-control resources in ongoing development. Since most new projects don't have historical data, there is interest in cross-project prediction: using data from one project to predict defects in another.
Foyzur Rahman +2 more
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