The process of software defect prediction (SDP) involves predicting which software system
modules or components pose the highest risk of being defective. The projections and …

Automated defect prediction of large and complex software systems is a challenging task.
However, by utilising correlated quality metrics, a defect prediction model can be devised to …

Failure of software systems as a result of software testing is very much rampant as modern
software systems are large and complex. Software testing which is an integral part of the …

Software fault prediction (SFP) is typically used to predict faults in software components.
Machine learning techniques (eg, classification) are widely used to tackle this problem. With …

Feature selection is an essential step in the process of software defect prediction due to the
negative effect of irrelevant features on classification algorithms. Hence selecting the most …

Software testing using software defect prediction aims to detect as many defects as possible
in software before the software release. This plays an important role in ensuring quality and …

Correlated quality metrics extracted from a source code repository can be utilized to design
a model to automatically predict defects in a software system. It is obvious that the extracted …

Search-Based Software Engineering (SBSE) is one of the techniques used for software
defect prediction (SDP), in which search-based optimization algorithms are used to identify …

Classification algorithms that help to identify software defects or faults play a crucial role in
software risk management. Experimental results have shown that ensemble of classifiers are …