Recent studies of software defect prediction typically produce datasets, methods and
frameworks which allow software engineers to focus on development activities in terms of …

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 …

Feature engineering plays a vital role in big data analytics. Machine learning and data
mining algorithms cannot work without data. Little can be achieved if there are few features …

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 prediction models are classifiers that are trained to identify defect-prone software
modules. Such classifiers have configurable parameters that control their characteristics (eg …

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 …

Background: The accurate prediction of where faults are likely to occur in code can help
direct test effort, reduce costs, and improve the quality of software. Objective: We investigate …

Software defect prediction is one of the most active fields in software engineering. Recently,
some experts have proposed the Just-in-time Defect Prediction Technology. Just-in-time …

Reliably predicting software defects is one of the holy grails of software engineering.
Researchers have devised and implemented a plethora of defect/bug prediction approaches …

Unsupervised models do not require the defect data to build the prediction models and
hence incur a low building cost and gain a wide application range. Consequently, it would …