Artificial Intelligence (AI) has become a core feature of today's real-world applications, making it a trending topic within the software engineering (SE) community. The rise in the …
A Dogan, D Birant - 2019 4th International Conference on …, 2019 - ieeexplore.ieee.org
Ensemble learning combines a series of base classifiers and the final result is assigned to the corresponding class by using a majority voting mechanism. However, the base …
A Alsaeedi, MZ Khan - Journal of Software Engineering and Applications, 2019 - scirp.org
An essential objective of software development is to locate and fix defects ahead of schedule that could be expected under diverse circumstances. Many software development …
Defect prediction at early stages of software development life cycle is a crucial activity of quality assurance process and has been broadly studied in the last two decades. The early …
SS Rathore, S Kumar - Applied Intelligence, 2021 - Springer
Previously, many researchers have performed analysis of various techniques for the software fault prediction (SFP). Oddly, the majority of such studies have shown the limited …
Ensemble learning is an algorithm that utilizes various types of classification models. This algorithm can enhance the prediction efficiency of component models. However, the …
Abstract Software Defect Prediction (SDP) is a major research field in the software development life cycle. The accurate SDP would assist software developers and engineers …
R Kumar, A Chaturvedi - IEEE Transactions on Reliability, 2023 - ieeexplore.ieee.org
An accurate prediction of bugs in software projects can help in improving software projects' quality. A simple majority voting (SMV) ensemble is an effective technique for bug prediction …
M Panda, AT Azar - Handbook of research on modeling, analysis …, 2021 - igi-global.com
Software bugs (or malfunctions) pose a serious threat to software developers with many known and unknown bugs that may be vulnerable to computer systems, demanding new …