An Empirical Study of Training Data Selection Methods for Ranking-Oriented Cross-Project Defect Prediction [PDF]
Sensors, 2021 Ranking-oriented cross-project defect prediction (ROCPDP), which ranks software modules of a new target industrial project based on the predicted defect number or density, has been suggested in the literature.
Haoyu Luo +4 more
doaj +4 more sources
Heterogeneous Cross-Project Defect Prediction via Optimal Transport [PDF]
IEEE Access, 2023 Heterogeneous cross-project defect prediction (HCPDP) aims to learn a prediction model from a heterogeneous source project and then apply the model to a target project.
Xing Zong +5 more
doaj +3 more sources
Within-project and cross-project defect prediction based on model averaging [PDF]
Scientific ReportsSoftware defect prediction has an important impact on the national economy and financial service industry. Discovering defective modules in the early stage of software development has great significance.
Tong Li, Zhong Wang, Peibei Shi
doaj +4 more sources
Too trivial to test? An inverse view on defect prediction to identify methods with low fault risk [PDF]
PeerJ Computer Science, 2019 Background Test resources are usually limited and therefore it is often not possible to completely test an application before a release. To cope with the problem of scarce resources, development teams can apply defect prediction to identify fault-prone ...
Rainer Niedermayr +2 more
doaj +5 more sources
Cross-Project Defect Prediction: A Literature Review
IEEE Access, 2022 Background: Software defect prediction models aim at identifying the potential faulty modules of a software project based on historical data collected from previous versions of the same project.
Sourabh Pal, Alberto Sillitti
doaj +2 more sources
Cross‐project defect prediction method based on genetic algorithm feature selection [PDF]
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
doaj +2 more sources
Improving Transfer Learning for Cross Project Defect Prediction
, 2022 —Cross-project defect prediction (CPDP) makes use of cross-project (CP) data to overcome the lack of data necessary to train well-performing software defect prediction (SDP) classifiers in the early stage of new software projects. Since the CP data (known as the source) may be different from the new project’s data (known as the target), this makes it ...
Osayande Pascal Omondiagbe +2 more
openalex +2 more sources
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 +4 more
openalex +2 more sources
Cross-Project Software Defect Prediction Based on Domain Adaptation and Feature Fusion [PDF]
AlgorithmsWith the advancement of computer science, software has become increasingly prevalent across all facets of society, making software quality issues a focal point of industry concern.
Guanhua Guo, Yinglei Song, Peng Zhang
doaj +2 more sources
Adversarial Learning for Cross-Project Semi-Supervised Defect Prediction
IEEE Access, 2020 Cross-project defect prediction (CPDP) aims to build a prediction model on existing source projects and predict the labels of target project. The data distribution difference between different projects makes CPDP very challenging.
Ying Sun +6 more
doaj +2 more sources