A survey on machine learning techniques for source code analysis
The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …
these techniques to a myriad of software engineering tasks that use source code analysis …
Software defect prediction analysis using machine learning techniques
There is always a desire for defect-free software in order to maintain software quality for
customer satisfaction and to save testing expenses. As a result, we examined various known …
customer satisfaction and to save testing expenses. As a result, we examined various known …
Software defect-based prediction using logistic regression: Review and challenges
J Goyal, R Ranjan Sinha - Second International Conference on …, 2022 - Springer
Software analysis and prediction system development is the significant and much-needed
field of software testing in software engineering. The automatic software predictors analyze …
field of software testing in software engineering. The automatic software predictors analyze …
Cross Project Software Defect Prediction Using Machine Learning: A Review
MS Saeed, M Saleem - … Journal of Computational and Innovative Sciences, 2023 - ijcis.com
Software defect prediction is a crucial area of study focused on enhancing software quality
and cutting down on software upkeep expenses. Cross Project Defect Prediction (CPDP) is …
and cutting down on software upkeep expenses. Cross Project Defect Prediction (CPDP) is …
[HTML][HTML] A survey on machine learning techniques applied to source code
The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …
these techniques to a myriad of software engineering tasks that use source code analysis …
Cloud-based bug tracking software defects analysis using deep learning
Cloud technology is not immune to bugs and issue tracking. A dedicated system is required
that will extremely error prone and less cumbersome and must command a high degree of …
that will extremely error prone and less cumbersome and must command a high degree of …
Enhancing software defect prediction: a framework with improved feature selection and ensemble machine learning
M Ali, T Mazhar, A Al-Rasheed, T Shahzad… - PeerJ Computer …, 2024 - peerj.com
Effective software defect prediction is a crucial aspect of software quality assurance,
enabling the identification of defective modules before the testing phase. This study aims to …
enabling the identification of defective modules before the testing phase. This study aims to …
Software defect prediction using an intelligent ensemble-based model
M Ali, T Mazhar, Y Arif, S Al-Otaibi, YY Ghadi… - IEEE …, 2024 - ieeexplore.ieee.org
Software defect prediction plays a crucial role in enhancing software quality while achieving
cost savings in testing. Its primary objective is to identify and send only defective modules to …
cost savings in testing. Its primary objective is to identify and send only defective modules to …
Evaluating the effectiveness of decomposed Halstead Metrics in software fault prediction
The occurrence of faults in software systems represents an inevitable predicament. Testing
is the most common means to detect such faults; however, exhaustive testing is not feasible …
is the most common means to detect such faults; however, exhaustive testing is not feasible …
A robust tuned K-nearest neighbours classifier for software defect prediction
If the software fails to perform its function, serious consequences may result. Software defect
prediction is one of the most useful tasks in the Software Development Life Cycle (SDLC) …
prediction is one of the most useful tasks in the Software Development Life Cycle (SDLC) …