A hybrid approach to software fault prediction using genetic programming and ensemble learning methods
Software fault prediction techniques use previous software metrics and also use the fault
data to predict fault-prone modules for the next release of software. In this article we review …
data to predict fault-prone modules for the next release of software. In this article we review …
[HTML][HTML] Reliable prediction of software defects using Shapley interpretable machine learning models
Predicting defect-prone software components can play a significant role in allocating
relevant testing resources to fault-prone modules and hence increasing the business value …
relevant testing resources to fault-prone modules and hence increasing the business value …
Revisiting the class imbalance issue in software defect prediction
Software defect prediction is related to the testing area of software industry. Several methods
have been developed for the prediction of bugs in software source codes. The objective of …
have been developed for the prediction of bugs in software source codes. The objective of …
[PDF][PDF] Software Fault Prediction: A Systematic Mapping Study.
Context: Software fault prediction has been an important research topic in the software
engineering field for more than 30 years. Software defect prediction models are commonly …
engineering field for more than 30 years. Software defect prediction models are commonly …
Performance analysis of machine learning algorithms using bagging ensemble technique for software fault prediction
R Samantaray, H Das - 2023 6th International Conference on …, 2023 - ieeexplore.ieee.org
Software development comes with a lot of challenges. Developers face various issues with
performance and bugs. These issues increase with the scale of the project and if fewer …
performance and bugs. These issues increase with the scale of the project and if fewer …
A dimensionality reduction-based efficient software fault prediction using Fisher linear discriminant analysis (FLDA)
Software quality is an important factor in the success of software companies. Traditional
software quality assurance techniques face some serious limitations especially in terms of …
software quality assurance techniques face some serious limitations especially in terms of …
Efficiency of oversampling methods for enhancing software defect prediction by using imbalanced data
TR Benala, K Tantati - Innovations in Systems and Software Engineering, 2023 - Springer
Software defect prediction (SDP) is essential to analyze and identify defects present in a
software model in early stages of software development. The identification of these defects …
software model in early stages of software development. The identification of these defects …
[HTML][HTML] Software defect prediction using supervised machine learning and ensemble techniques: a comparative study
A Alsaeedi, MZ Khan - Journal of Software Engineering and Applications, 2019 - scirp.org
An essential objective of software development is to locate and fix defects ahead of
schedule that could be expected under diverse circumstances. Many software development …
schedule that could be expected under diverse circumstances. Many software development …
[HTML][HTML] Predicting defects in imbalanced data using resampling methods: an empirical investigation
R Malhotra, J Jain - PeerJ Computer Science, 2022 - peerj.com
The development of correct and effective software defect prediction (SDP) models is one of
the utmost needs of the software industry. Statistics of many defect-related open-source data …
the utmost needs of the software industry. Statistics of many defect-related open-source data …
Genetic feature selection for software defect prediction
Recently, software defect prediction is an important research topic in the software
engineering field. The accurate prediction of defect prone software modules can help the …
engineering field. The accurate prediction of defect prone software modules can help the …