Progress on approaches to software defect prediction
Software defect prediction is one of the most popular research topics in software
engineering. It aims to predict defect‐prone software modules before defects are discovered …
engineering. It aims to predict defect‐prone software modules before defects are discovered …
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 …
Heterogeneous defect prediction
Software defect prediction is one of the most active research areas in software engineering.
We can build a prediction model with defect data collected from a software project and …
We can build a prediction model with defect data collected from a software project and …
How far we have progressed in the journey? an examination of cross-project defect prediction
Background. Recent years have seen an increasing interest in cross-project defect
prediction (CPDP), which aims to apply defect prediction models built on source projects to a …
prediction (CPDP), which aims to apply defect prediction models built on source projects to a …
Improving the prediction of continuous integration build failures using deep learning
Continuous Integration (CI) aims at supporting developers in integrating code changes
constantly and quickly through an automated build process. However, the build process is …
constantly and quickly through an automated build process. However, the build process is …
Transfer learning for performance modeling of configurable systems: An exploratory analysis
Modern software systems provide many configuration options which significantly influence
their non-functional properties. To understand and predict the effect of configuration options …
their non-functional properties. To understand and predict the effect of configuration options …
[HTML][HTML] A three-stage transfer learning framework for multi-source cross-project software defect prediction
J Bai, J Jia, LF Capretz - Information and Software Technology, 2022 - Elsevier
Context Transfer learning techniques have been proved to be effective in the field of Cross-
project defect prediction (CPDP). However, some questions still remain. First, the conditional …
project defect prediction (CPDP). However, some questions still remain. First, the conditional …
Transfer learning for improving model predictions in highly configurable software
Modern software systems are built to be used in dynamic environments using configuration
capabilities to adapt to changes and external uncertainties. In a self-adaptation context, we …
capabilities to adapt to changes and external uncertainties. In a self-adaptation context, we …
Learning to sample: Exploiting similarities across environments to learn performance models for configurable systems
Most software systems provide options that allow users to tailor the system in terms of
functionality and qualities. The increased flexibility raises challenges for understanding the …
functionality and qualities. The increased flexibility raises challenges for understanding the …
Predictive models in software engineering: Challenges and opportunities
Predictive models are one of the most important techniques that are widely applied in many
areas of software engineering. There have been a large number of primary studies that …
areas of software engineering. There have been a large number of primary studies that …