The occurrences of noisy data in data set can significantly impact prediction of any
meaningful information. Many empirical studies have shown that noise in data set …

Several prediction approaches are contained in the arena of software engineering such as
prediction of effort, security, quality, fault, cost, and re-usability. All these prediction …

Recent advancements in technology have emerged the requirements of hardware and
software applications. Along with this technical growth, software industries also have faced …

Automated generate-and-validate (GV) program repair techniques (APR) typically rely on
hard-coded rules, thus only fixing bugs following specific fix patterns. These rules require a …

The use of learning-based techniques to achieve automated software vulnerability detection
has been of longstanding interest within the software security domain. These data-driven …

Software defect prediction, which predicts defective code regions, can help developers find
bugs and prioritize their testing efforts. To build accurate prediction models, previous studies …

In the research of mining software repositories, we need to label a large amount of data to
construct a predictive model. The correctness of the labels will affect the performance of a …

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, which predicts defective code regions, can assist developers in
finding bugs and prioritizing their testing efforts. Traditional defect prediction features often …

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 …