Deep learning (DL), a branch of machine learning (ML), is the core technology in today's
technological advancements and innovations. Deep learning-based approaches are the …

Context: Machine learning software defect prediction is a promising field of software
engineering, attracting a great deal of attention from the research community; however, its …

This study discusses the effects of class imbalance and training data size on the predictive
performance of classifiers. An empirical study was performed on ten classifiers arising from …

Abstract Context: Machine Learning Software Defect Prediction (ML SDP) is a promising
method to improve the quality and minimize the cost of software development. Objective: We …

One of the most important topics in machine learning is how to evaluate the models, which
means measuring how accurately they predict the expected outcome. In addition to …

The quality of the software being developed varies with the size and complexity of the
software. It is a matter of concern in software development as it impairs the faith of customers …

The occurrence of faults in software systems represents an inevitable predicament. Testing
is the most common means to detect such faults; however, exhaustive testing is not feasible …

Software is a complex entity, and its development needs careful planning and a high amount
of time and cost. To assess quality of program, software measures are very helpful. Amongst …

Despite the increasing applications, demands, and capabilities of drones, in practice they
have only limited autonomy for accomplishing complex missions, resulting in slow and …

Software quality assurance has grown in importance in the fast-paced world of software
development. One of trickiest parts of creating and maintaining software is predicting how …