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 …
Researcher bias: The use of machine learning in software defect prediction
Background. The ability to predict defect-prone software components would be valuable.
Consequently, there have been many empirical studies to evaluate the performance of …
Consequently, there have been many empirical studies to evaluate the performance of …
A survey on machine learning techniques for source code analysis
T Sharma, M Kechagia, S Georgiou, R Tiwari… - ar**
Software defect prediction has been one of the key areas of exploration in the domain of
software quality. In this paper, we perform a systematic map** to analyze all the software …
software quality. In this paper, we perform a systematic map** to analyze all the software …
An empirical study of ensemble techniques for software fault prediction
SS Rathore, S Kumar - Applied Intelligence, 2021 - Springer
Previously, many researchers have performed analysis of various techniques for the
software fault prediction (SFP). Oddly, the majority of such studies have shown the limited …
software fault prediction (SFP). Oddly, the majority of such studies have shown the limited …
The impact of artificial intelligence on software testing
H Hourani, A Hammad, M Lafi - 2019 IEEE Jordan International …, 2019 - ieeexplore.ieee.org
Artificial Intelligence (AI) plays an important role in our life and touch base most of our
surrounding applications and systems. A huge amounts of data are created every day from …
surrounding applications and systems. A huge amounts of data are created every day from …
Comparative analysis of statistical and machine learning methods for predicting faulty modules
R Malhotra - Applied Soft Computing, 2014 - Elsevier
The demand for development of good quality software has seen rapid growth in the last few
years. This is leading to increase in the use of the machine learning methods for analyzing …
years. This is leading to increase in the use of the machine learning methods for analyzing …
[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 …
Defect prediction between software versions with active learning and dimensionality reduction
Accurate detection of defects prior to product release helps software engineers focus
verification activities on defect prone modules, thus improving the effectiveness of software …
verification activities on defect prone modules, thus improving the effectiveness of software …