[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 …
Systematic literature review on application of learning-based approaches in continuous integration
Context: Machine learning (ML) and deep learning (DL) analyze raw data to extract valuable
insights in specific phases. The rise of continuous practices in software projects emphasizes …
insights in specific phases. The rise of continuous practices in software projects emphasizes …
Industry–academia research collaboration and knowledge co-creation: Patterns and anti-patterns
Increasing the impact of software engineering research in the software industry and the
society at large has long been a concern of high priority for the software engineering …
society at large has long been a concern of high priority for the software engineering …
State of practical applicability of regression testing research: A live systematic literature review
Context: Software regression testing refers to rerunning test cases after the system under
test is modified, ascertaining that the changes have not (re-) introduced failures. Not all …
test is modified, ascertaining that the changes have not (re-) introduced failures. Not all …
Accelerating Continuous Integration with Parallel Batch Testing
Continuous integration at scale is costly but essential to software development. Various test
optimization techniques including test selection and prioritization aim to reduce the cost …
optimization techniques including test selection and prioritization aim to reduce the cost …
Comparative study of machine learning test case prioritization for continuous integration testing
D Marijan - Software Quality Journal, 2023 - Springer
There is a growing body of research indicating the potential of machine learning to tackle
complex software testing challenges. One such challenge pertains to continuous integration …
complex software testing challenges. One such challenge pertains to continuous integration …
Artificial Intelligence in Software Testing: A Systematic Review
M Islam, F Khan, S Alam… - TENCON 2023-2023 IEEE …, 2023 - ieeexplore.ieee.org
Software testing is a crucial component of software development. With the increasing
complexity of software systems, traditional manual testing methods are becoming less …
complexity of software systems, traditional manual testing methods are becoming less …
Test case prioritization using partial attention
Test case prioritization (TCP) aims to reorder the regression test suite with a goal of
increasing the fault detection rate. Various TCP techniques have been proposed based on …
increasing the fault detection rate. Various TCP techniques have been proposed based on …
Sok: Machine learning for continuous integration
Continuous Integration (CI) has become a well-established software development practice
for automatically and continuously integrating code changes during software development …
for automatically and continuously integrating code changes during software development …
Integration test order generation based on reinforcement learning considering class importance
Y Ding, Y Zhang, G Yuan, S Jiang, W Dai… - Journal of Systems and …, 2023 - Elsevier
The task of ordering classes reasonably in the context of integration testing has been
discussed by many researchers. Existing methods regard the class integration test order …
discussed by many researchers. Existing methods regard the class integration test order …