Results 61 to 70 of about 16,545 (157)

CDS: A Cross–Version Software Defect Prediction Model With Data Selection

IEEE Access, 2020
Over the past decade, a large number of software defect prediction approaches have been proposed to identify the defect-prone modules by mining software repositories. Recently, a novel scenario called Cross-Version Defect Prediction (CVDP) begins to draw
Jie Zhang, Jiajing Wu, Chuan Chen, Zibin Zheng, Michael R. Lyu   +4 more
doaj   +1 more source

An Empirical Study of Classifier Combination for Cross-Project Defect Prediction

2015 IEEE 39th Annual Computer Software and Applications Conference, 2015
To help developers better allocate testing and debugging efforts, many software defect prediction techniques have been proposed in the literature. These techniques can be used to predict classes that are more likely to be buggy based on past history of buggy classes.
Yun Zhang 0011, David Lo 0001, Xin Xia 0001, Jianling Sun   +3 more
openaire   +3 more sources

Cross-Project Defect Prediction Based on Two-Phase Feature Importance Amplification. [PDF]

Comput Intell Neurosci, 2022
Xing Y, Lin W, Lin X, Yang B, Tan Z.
europepmc   +1 more source

An Abstract Syntax Tree Encoding Method for Cross-Project Defect Prediction

IEEE Access, 2019
In the last few years, with the development of deep learning theory, researchers have tried to introduce the method of artificial intelligence into the field of software defect prediction (SDP) to improve its prediction effect.
Ziyi Cai, Lu Lu, Shaojian Qiu
doaj   +1 more source

Towards Cross-Project Defect Prediction with Imbalanced Feature Sets

CoRR, 2014
10 pages, 8 figures, 7 ...
Peng He, Bing Li 0010, Yutao Ma
openaire   +2 more sources

Feature Subset Selection and Instance Filtering for Cross-project Defect Prediction - Classification and Ranking

CLEI Electronic Journal, 2016
The defect prediction models can be a good tool on organizing the project´s test resources. The models can be constructed with two main goals: 1) to classify the software parts - defective or not; or 2) to rank the most defective parts in a decreasing ...
Faimison Porto, Adenilso da Silva Simao
doaj   +1 more source

A Systematic Study of Cross-Project Defect Prediction With Meta-Learning

CoRR, 2018
The prediction of defects in a target project based on data from external projects is called Cross-Project Defect Prediction (CPDP). Several methods have been proposed to improve the predictive performance of CPDP models. However, there is a lack of comparison among state-of-the-art methods.
Faimison Rodrigues Porto, Leandro L. Minku, Emilia Mendes, Adenilso Simão   +3 more
openaire   +2 more sources

Heterogeneous Cross-Project Defect Prediction Using Encoder Networks and Transfer Learning

IEEE Access
Heterogeneous cross-project defect prediction (HCPDP) aims to predict defects in new software projects using defect data from previous software projects where the source and target projects have some different metrics.
Radowanul Haque, Aftab Ali, Sally McClean, Ian Cleland, Joost Noppen   +4 more
doaj   +1 more source

Benchmarking cross-project defect prediction approaches with costs metrics

CoRR, 2018
Rejected at ICSE Technical Track, will be presented as a poster and hopefully appear in an extended version in a journal at some point in ...
openaire   +2 more sources

Improving transfer learning for software cross-project defect prediction

Applied Intelligence
AbstractSoftware 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),
Osayande P. Omondiagbe, Sherlock A. Licorish, Stephen G. MacDonell   +2 more
openaire   +2 more sources