Results 11 to 20 of about 16,545 (157)

A Survey on Transfer Learning for Cross-Project Defect Prediction

IEEE Access
Software defect prediction involves predicting which components in a software program, like classes or functions, are likely to have defects, based on metrics that describe those components.
Bruno Sotto-Mayor, Meir Kalech
doaj   +4 more sources

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, Heng Dai, Weiqiang Peng, Wenhua Hu, Fuyang Li   +4 more
doaj   +2 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

Improving Cross-Project Software Defect Prediction Method Through Transformation and Feature Selection Approach

IEEE Access, 2023
In the traditional software defect prediction methodology, the historical record (dataset) of the same project is partitioned into training and testing data.
Yahaya Zakariyau Bala, Pathiah Abdul Samat, Khaironi Yatim Sharif, Noridayu Manshor   +3 more
doaj   +3 more sources

Within-project and cross-project defect prediction based on model averaging [PDF]

Scientific Reports
Software 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   +2 more sources

Cross-Project Defect Prediction Method Based on Manifold Feature Transformation

Future Internet, 2021
Traditional research methods in software defect prediction use part of the data in the same project to train the defect prediction model and predict the defect label of the remaining part of the data.
Yu Zhao, Yi Zhu, Qiao Yu, Xiaoying Chen
doaj   +3 more sources

Heterogeneous Cross-Project Defect Prediction via Optimal Transport

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, Guiyu Li, Shang Zheng, Haitao Zou, Hualong Yu, Shang Gao   +5 more
doaj   +2 more sources

DeepCPDP: Deep Learning Based Cross-Project Defect Prediction [PDF]

IEEE Access, 2019
Cross-project defect prediction (CPDP) is an active research topic in the domain of software defect prediction, since CPDP can be applied to the following scenarios: the target project for software defect prediction is a new project or the target project
Deyu Chen, Xiang Chen, Hao Li, Junfeng Xie, Yanzhou Mu   +4 more
doaj   +2 more sources

Cross-Project Defect Prediction with Metrics Selection and Balancing Approach

Applied Computer Systems, 2022
In software development, defects influence the quality and cost in an undesirable way. Software defect prediction (SDP) is one of the techniques which improves the software quality and testing efficiency by early identification of defects(bug/fault/error)
Nevendra Meetesh, Singh Pradeep
doaj   +2 more sources

Balanced Adversarial Tight Matching for Cross-Project Defect Prediction

IET Software
Cross-project defect prediction (CPDP) is an attractive research area in software testing. It identifies defects in projects with limited labeled data (target projects) by utilizing predictive models from data-rich projects (source projects).
Siyu Jiang, Jiapeng Zhang, Feng Guo, Teng Ouyang, Jing Li   +4 more
doaj   +2 more sources