Results 1 to 10 of about 377 (66)
An Empirical Study on Software Defect Prediction Using CodeBERT Model
Applied Sciences, 2021 Deep learning-based software defect prediction has been popular these days. Recently, the publishing of the CodeBERT model has made it possible to perform many software engineering tasks.
Cong Pan, Minyan Lu, Biao Xu
doaj +3 more sources
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
doaj +3 more sources
A Framework for Software Defect Prediction and Metric Selection
IEEE Access, 2018 Automated software defect prediction is an important and fundamental activity in the domain of software development. However, modern software systems are inherently large and complex with numerous correlated metrics that capture different aspects of the ...
Shamsul Huda +6 more
doaj +3 more sources
Integrated Approach to Software Defect Prediction
IEEE Access, 2017 Software defect prediction provides actionable outputs to software teams while contributing to industrial success. Empirical studies have been conducted on software defect prediction for both cross-project and within-project defect prediction.
Ebubeogu Amarachukwu Felix, Sai Peck Lee
doaj +3 more sources
SOFTWARE DEFECT PREDICTION APPROACHES REVISITED [PDF]
International Journal of Intelligent Computing and Information Sciences, 2023 A crucial field in software development and testing is Software Defect Prediction (SDP) because the quality, dependability, efficiency, and cost of the software are all improved by forecasting software defects at an earlier stage.
Khaled Shebl, Yasmine Afify, Nagwa Badr
doaj +1 more source
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 +1 more source
Multi-view learning for software defect prediction [PDF]
e-Informatica Software Engineering Journal, 2021 Background: Traditionally, machine learning algorithms have been simply applied for software defect prediction by considering single-view data, meaning the input data contains a single feature vector.
Elife Ozturk Kiyak +2 more
doaj +1 more source
Software Defect Prediction Framework Using Hybrid Software Metric
JOIV: International Journal on Informatics Visualization, 2022 Software fault prediction is widely used in the software development industry. Moreover, software development has accelerated significantly during this epidemic.
Amirul Zaim +4 more
doaj +1 more source
Software fault prediction based on change metrics using hybrid algorithms: An empirical study
Journal of King Saud University: Computer and Information Sciences, 2020 Quality of the developed software depends on its bug free operation. Although bugs can be introduced in any phase of the software development life-cycle but their identification in earlier phase can lead to reduce the allocation cost of testing and ...
Wasiur Rhmann +3 more
doaj +1 more source
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 +3 more
doaj +1 more source