Software fault prediction using data mining, machine learning and deep learning techniques: A systematic literature review
Software fault/defect prediction assists software developers to identify faulty constructs, such
as modules or classes, early in the software development life cycle. There are data mining …
as modules or classes, early in the software development life cycle. There are data mining …
A literature review of using machine learning in software development life cycle stages
The software engineering community is rapidly adopting machine learning for transitioning
modern-day software towards highly intelligent and self-learning systems. However, the …
modern-day software towards highly intelligent and self-learning systems. However, the …
[HTML][HTML] On the use of deep learning in software defect prediction
Context: Automated software defect prediction (SDP) methods are increasingly applied,
often with the use of machine learning (ML) techniques. Yet, the existing ML-based …
often with the use of machine learning (ML) techniques. Yet, the existing ML-based …
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 …
Survey of supervised learning for medical image processing
A Aljuaid, M Anwar - SN Computer Science, 2022 - Springer
Medical image interpretation is an essential task for the correct diagnosis of many diseases.
Pathologists, radiologists, physicians, and researchers rely heavily on medical images to …
Pathologists, radiologists, physicians, and researchers rely heavily on medical images to …
Prediction of software fault-prone classes using ensemble random forest with adaptive synthetic sampling algorithm
A Balaram, S Vasundra - Automated Software Engineering, 2022 - Springer
The process of predicting fault module in software is known as Software Fault Prediction
(SFP) which is important for releasing software versions that are dependent on the …
(SFP) which is important for releasing software versions that are dependent on the …
Diversity based imbalance learning approach for software fault prediction using machine learning models
P Manchala, M Bisi - Applied Soft Computing, 2022 - Elsevier
The Software fault prediction (SFP) target is to distinguish between faulty and non-faulty
modules. The prediction model's performance is vulnerable to the class imbalance issue in …
modules. The prediction model's performance is vulnerable to the class imbalance issue in …
An efficient hybrid mine blast algorithm for tackling software fault prediction problem
An inherent problem in software engineering is that competing prediction systems have
been found to produce conflicting results. Yet accurate prediction is crucial because the …
been found to produce conflicting results. Yet accurate prediction is crucial because the …
[HTML][HTML] Salp swarm optimizer for modeling the software fault prediction problem
S Kassaymeh, S Abdullah, MA Al-Betar… - Journal of King Saud …, 2022 - Elsevier
This paper proposes the salp swarm algorithm (SSA) combined with a backpropagation
neural network (BPNN) to solve the software fault prediction (SFP) problem. The SFP …
neural network (BPNN) to solve the software fault prediction (SFP) problem. The SFP …
Service-oriented model-based fault prediction and localization for service compositions testing using deep learning techniques
As service-oriented computing systems become more buoyant and complex, the occurrence
of faults dramatically increases. Fault prediction plays a crucial role in the service-oriented …
of faults dramatically increases. Fault prediction plays a crucial role in the service-oriented …