The adoption of machine learning techniques for software defect prediction: An initial industrial validation
Existing methods for predicting reliability of software are static and need manual
maintenance to adjust to the evolving data sets in software organizations. Machine learning …
maintenance to adjust to the evolving data sets in software organizations. Machine learning …
A framework for adoption of machine learning in industry for software defect prediction
Machine learning algorithms are increasingly being used in a variety of application domains
including software engineering. While their practical value have been outlined …
including software engineering. While their practical value have been outlined …
[HTML][HTML] Industrial applications of software defect prediction using machine learning: A business-driven systematic literature review
S Stradowski, L Madeyski - Information and Software Technology, 2023 - Elsevier
Context: Machine learning software defect prediction is a promising field of software
engineering, attracting a great deal of attention from the research community; however, its …
engineering, attracting a great deal of attention from the research community; however, its …
Empirical assessment of machine learning based software defect prediction techniques
VUB Challagulla, FB Bastani, IL Yen… - International Journal on …, 2008 - World Scientific
Automated reliability assessment is essential for systems that entail dynamic adaptation
based on runtime mission-specific requirements. One approach along this direction is to …
based on runtime mission-specific requirements. One approach along this direction is to …
Authors' reply to “comments on 'researcher bias: The use of machine learning in software defect prediction'”
In 2014 we published a meta-analysis of software defect prediction studies [1]. This
suggested that the most important factor in determining results was Research Group, ie, who …
suggested that the most important factor in determining results was Research Group, ie, who …
A review on machine learning techniques for software defect prediction
F Hassan, S Farhan, MA Fahiem, H Tauseef - Technical Journal, 2018 - tj.uettaxila.edu.pk
Software defect prediction has been an interest of research era because predicting defects
on early stages improves software quality with reduced cost and effective software …
on early stages improves software quality with reduced cost and effective software …
[PDF][PDF] Software defect prediction using supervised machine learning techniques: A systematic literature review
Software defect prediction (SDP) is the process of detecting defectprone software modules
before the testing stage. The testing stage in the software development life cycle is …
before the testing stage. The testing stage in the software development life cycle is …
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 …
[PDF][PDF] Software defect prediction using machine learning algorithms: Current state of the art
One of the essential exploratory fields in the software quality field is software defect
prediction. Software engineering involves many ways to predict software quality assurance …
prediction. Software engineering involves many ways to predict software quality assurance …
A framework for defect prediction in specific software project contexts
D Wahyudin, R Ramler, S Biffl - … Engineering Techniques: Third IFIP TC 2 …, 2011 - Springer
Software defect prediction has drawn the attention of many researchers in empirical software
engineering and software maintenance due to its importance in providing quality estimates …
engineering and software maintenance due to its importance in providing quality estimates …