Results 121 to 130 of about 16,545 (157)

Discriminant Subspace Alignment for Cross-Project Defect Prediction

2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), 2019
Cross-project defect prediction (CPDP) aims at recognizing defective software modules in a target project with the utilization of historical data from other source projects. Lately, CPDP has attracted much research interest. However, distribution discrepancy between the source and targert projects is known to have a negative effect on CPCP performance.
Zhiqiang Li 0003, Chao Qi, Li Zhang, Jie Ren 0007   +3 more
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Manifold Learning for Cross-project Software Defect Prediction

2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS), 2018
Traditional software defect prediction studies usually built models using within-project data. However, there are not enough local data repositories for us to build the software defect prediction model in practice. Recently, cross-project software defect prediction (CSDP) has been proposed.
Jing Sun, Xiaoyuan Jing, Xiwei Dong
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Ensemble Based-Cross Project Defect Prediction

2021
In Software Testing, there are typically two ways to predict defects in the software—within-project defect prediction (WPDP) and cross project defect prediction (CPDP). In this research, we are using a hybrid model for cross project defect prediction. It is a two-phase model consisting of ensemble learning (EL) and genetic algorithm (GA) phase. For our
Rajni Jindal, Adil Ahmad, Anshuman Aditya   +2 more
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Improving Prediction Robustness of VAB-SVM for Cross-Project Defect Prediction

2014 IEEE 17th International Conference on Computational Science and Engineering, 2014
Software defect prediction is important for improving software quality. Defect predictors allow software test engineers to focus on defective modules. Cross-Project Defect Prediction (CPDP) uses data from other companies to build defect predictors. However, outliers may lower prediction accuracy.
Duksan Ryu, Okjoo Choi, Jongmoon Baik
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Heterogeneous Cross Project Defect Prediction in Software

SSRN Electronic Journal, 2020
Software defect prediction is one of the software engineering's most active research fields. Most of the existing work focuses on Homogeneous Cross Project Defect Prediction (CPDP), in which the model is trained by the use of a common metric set extracted from the source and target project. Our article emphasizes the heterogeneous CPDP modeling (HCPDP)
Sonali Srivastava, Shikha Rani, Shailly Singh, Saurabh Singh, Rohit Vashisht   +4 more
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Cross Projects Defect Prediction Modeling

2019
Software defect prediction has been much studied in the field of research in Software Engineering. Within project Software defect prediction works well as there is sufficient amount of data available to train any model. But rarely local training data of the projects is available for predictions.
Lipika Goel, Sonam Gupta
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Training data selection for imbalanced cross-project defect prediction

Computers & Electrical Engineering, 2021
Abstract Machine learning methods have been applied in software engineering to effectively predict software defects. Researchers proposed cross-project defect prediction (CPDP) for cases in which few or no data are available. CPDP uses the labeled data of a source project to construct a prediction model for the target project. However, the prediction
Shang Zheng, Jinjing Gai, Hualong Yu, Haitao Zou, Shang Gao 0001   +4 more
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CrossPare: A Tool for Benchmarking Cross-Project Defect Predictions

2015 30th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW), 2015
During the last decade, many papers on defect prediction were published. One still for the most part unresolved issue are cross-project defect predictions. Here, the aim is to predict the defects of a project, with data from other projects. Many approaches were suggested and evaluated in recent years.
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A literature review on cross project defect prediction

2017 4th IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics (UPCON), 2017
In the area of defect prediction most of the literature comprises of within project defect prediction. It is always not feasible to have the historical data of the similar projects for predictions. Therefore, CPDP (Cross Project Defect Prediction) as a subset of defect prediction in general has become a popular topic in research these days.
Lipika Goel, D. Damodaran, Sunil Kumar Khatri, Mayank Sharma   +3 more
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Training data selection for cross-project defect prediction

Proceedings of the 9th International Conference on Predictive Models in Software Engineering, 2013
Software defect prediction has been a popular research topic in recent years and is considered as a means for the optimization of quality assurance activities. Defect prediction can be done in a within-project or a cross-project scenario. The within-project scenario produces results with a very high quality, but requires historic data of the project ...
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