Defect prediction models help software quality assurance teams to allocate their limited
resources to the most defect-prone modules. Model validation techniques, such as-fold …

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 …

Defect prediction models-classifiers that identify defect-prone software modules-have
configurable parameters that control their characteristics (eg, the number of trees in a …

Defect models that are trained on class imbalanced datasets (ie, the proportion of defective
and clean modules is not equally represented) are highly susceptible to produce inaccurate …

Defect prediction models are a well-known technique for identifying defect-prone files or
packages such that practitioners can allocate their quality assurance efforts (eg, testing and …

Many software defect prediction approaches have been proposed and most are effective in
within-project prediction settings. However, for new projects or projects with limited training …

Software code review, ie, the practice of having other team members critique changes to a
software system, is a well-established best practice in both open source and proprietary …

Software code review, ie, the practice of having third-party team members critique changes
to a software system, is a well-established best practice in both open source and proprietary …

Logs are often used for troubleshooting in large-scale software systems. For a cloud-based
online system that provides 24/7 service, a huge number of logs could be generated every …

Defect prediction on new projects or projects with limited historical data is an interesting
problem in software engineering. This is largely because it is difficult to collect defect …