Software defect detection (SDD) is crucial to ensure the reliability of software systems and
identify defects in classification. One of the key challenges in defect detection is to select …

As software systems undergo escalating complexity, the identification of bugs and defects
becomes pivotal for ensuring seamless user experiences and averting potentially costly post …

Ensuring the quality of software systems is essential for effective and efficient usage in
complex software development procedures. A vital component of the whole procedure is the …

Various techniques in machine learning have been used for building software defect
prediction (SDP) models to identify the defective software modules. However, a major …

This study explores machine learning (ML) techniques for Software defects prediction (SDP)
by using Mathematical Modelling & Simulation. The SDP is also used in the critical systems …

One of the most crucial methods for assessing software quality and cutting development
costs is software defect prediction (SDP). Software defects can be predicted using data …

Prediction of software bugs from process logs, temporal access logs, behavior analysis, etc.
requires estimation of a wide variety of high-density feature sets. Extracted feature sets must …

The deep learning model (DL) S-ResNet-152 (Squeeze-based ResNet-152) is used to pull
out the features. Then, a bidirectional gated auto network (Bi-GRU-AN) is used to predict …

Given the escalating magnitude and intricacy of software systems, software measurement
data often contains irrelevant and redundant features, resulting in significant resource and …

Software quality assurance is a set of activities that ensures the quality of the software from
different aspects. This process continues in parallel with the development of the software to …