Results 31 to 40 of about 16,545 (157)
Multi-Source Heterogeneous Kernel Mapping in Software Defect Prediction
Applied Sciences, 2023 Heterogeneous defect prediction (HDP) is a significant research topic in cross-project defect prediction (CPDP), due to the inconsistency of metrics used between source and target projects.
Jingxiu Yao, Bin Liu, Yumei Wu, Zhibo Li
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Cross‐project defect prediction method based on genetic algorithm feature selection
Engineering Reports, 2023 With the continuous development of Internet technology, the role of software in life is increasing, and software defect prediction (SDP) is a key means to ensure software reliability.
Zhixi Hu, Yi Zhu
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Revisiting ‘revisiting supervised methods for effort‐aware cross‐project defect prediction’
IET Software, 2023 Effort‐aware cross‐project defect prediction (EACPDP), which uses cross‐project software modules to build a model to rank within‐project software modules based on the defect density, has been suggested to allocate limited testing resource efficiently ...
Fuyang Li +5 more
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Cross-Project Software Defect Prediction Based on Class Code Similarity
IEEE Access, 2022 Software defect prediction techniques can help software developers find software defects as soon as possible. It can also reduce the cost of software development.
Wanzhi Wen +6 more
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IEEE Access, 2023 Recent reviews of the literature indicate the need for empirical studies on cross-project defect prediction (CPDP) that would allow aggregation of the evidence and improve predictive performance.
Touseef Tahir +6 more
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Evaluating Data Filter on Cross-Project Defect Prediction: Comparison and Improvements
IEEE Access, 2017 Cross-project defect prediction (CPDP) is a field of study where a software project lacking enough local data can use data from other projects to build defect predictors.
Yong Li +3 more
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MSCPDPLab: A MATLAB toolbox for transfer learning based multi-source cross-project defect prediction
SoftwareX, 2023 Software defect prediction (SDP) plays an important role in allocating testing resources and improving testing efficiency. Multi-source cross-project defect prediction (MSCPDP) based on transfer learning refers to transferring defect knowledge from ...
Jiaqi Zou +3 more
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CoRR, 2021 Software defect prediction heavily relies on the metrics collected from software projects. Earlier studies often used machine learning techniques to build, validate, and improve bug prediction models using either a set of metrics collected within a project or across different projects. However, techniques applied and conclusions derived by those models
Hadi Jahanshahi +2 more
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Applied Sciences, 2022 Using artificial intelligence (AI) based software defect prediction (SDP) techniques in the software development process helps isolate defective software modules, count the number of software defects, and identify risky code changes.
Mahesha Pandit +7 more
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Simplification of Training Data for Cross-Project Defect Prediction
CoRR, 2014 Cross-project defect prediction (CPDP) plays an important role in estimating the most likely defect-prone software components, especially for new or inactive projects. To the best of our knowledge, few prior studies provide explicit guidelines on how to select suitable training data of quality from a large number of public software repositories.
Peng He +3 more
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