Machine/deep learning for software engineering: A systematic literature review
Since 2009, the deep learning revolution, which was triggered by the introduction of
ImageNet, has stimulated the synergy between Software Engineering (SE) and Machine …
ImageNet, has stimulated the synergy between Software Engineering (SE) and Machine …
Improving software bug-specific named entity recognition with deep neural network
C Zhou, B Li, X Sun - Journal of Systems and Software, 2020 - Elsevier
There is a large volume of bug data in the bug repository, which contains rich bug
information. Existing studies on bug data mining mainly rely on using information retrieval …
information. Existing studies on bug data mining mainly rely on using information retrieval …
A framework for continuous regression and integration testing in iot systems based on deep learning and search-based techniques
Tremendous systems are rapidly evolving based on the trendy Internet of Things (IoT) in
various domains. Different technologies are used for communication between the massive …
various domains. Different technologies are used for communication between the massive …
Deep learning-based software bug classification
Context: Accurate classification of bugs can help accelerate the bug triage process, code
inspection, and repair activities. In this context, many machine learning techniques have …
inspection, and repair activities. In this context, many machine learning techniques have …
Recommending pull request reviewers based on code changes
Pull-based development supports collaborative distributed development. It enables
developers to collaborate on projects hosted on GitHub. If a developer wants to collaborate …
developers to collaborate on projects hosted on GitHub. If a developer wants to collaborate …
Software defect prediction using a bidirectional LSTM network combined with oversampling techniques
NAA Khleel, K Nehéz - Cluster Computing, 2024 - Springer
Software defects are a critical issue in software development that can lead to system failures
and cause significant financial losses. Predicting software defects is a vital aspect of …
and cause significant financial losses. Predicting software defects is a vital aspect of …
Improving bug report triage performance using artificial intelligence based document generation model
Artificial intelligence is one of the key technologies for progression to the fourth industrial
revolution. This technology also has a significant impact on software professionals who are …
revolution. This technology also has a significant impact on software professionals who are …
Why and what happened? Aiding bug comprehension with automated category and causal link identification
C Zhou, B Li, X Sun, L Bo - Empirical Software Engineering, 2021 - Springer
When a new bug report is assigned to developers, they first need to understand what the
bug report expresses (what) and why this bug occurs (why). To do so, developers usually …
bug report expresses (what) and why this bug occurs (why). To do so, developers usually …
An empirical study of automated privacy requirements classification in issue reports
The recent advent of data protection laws and regulations has emerged to protect privacy
and personal information of individuals. As the cases of privacy breaches and vulnerabilities …
and personal information of individuals. As the cases of privacy breaches and vulnerabilities …
DHG-BiGRU: Dual-attention based hierarchical gated BiGRU for software defect prediction
R Malhotra, P Singh - Information and Software Technology, 2024 - Elsevier
Context: The goal of software defect prediction (SDP), a well-known field of study, is to detect
errors early in the software lifecycle. Traditional machine learning models are based on …
errors early in the software lifecycle. Traditional machine learning models are based on …