To address the challenges associated with the abundance of features in software datasets,
this study proposes a novel hybrid feature selection method that combines quantum particle …

Detecting software defects before they occur is crucial in software engineering as it impacts
software system quality and reliability. Previous studies on predicting software defects have …

Software defect prediction plays a crucial role in ensuring software quality and minimizing
the potential risks associated with defects. This study aims to develop a comprehensive …

Software testing is a vital phase in the software development life cycle. Testing validates a
developed software against the input test cases by identifying the defects present in the …

Software defect prediction models are used for predicting high risk software components.
Feature selection has significant impact on the prediction performance of the software defect …

Objective: Defects in delivered software products not only have financial implications but
also affect the reputation of the organisation and lead to wastage of time and human …

Software defects may cause severe crashes in the system, leading to the software's high
maintenance costs. Early identification of these defects would lead to high-quality software …

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 …

Software Testing is an essential activity in the development process of a software product. A
defect-free software is the need of the hour. Identifying the defects as early as possible is …

In software defect prediction, noisy attributes and high-dimensional data remain to be a
critical challenge. This paper introduces a novel approach known as multi correlation-based …