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DOI Prefix: 10.47001/IRJIET

A Survey of Software Systems Anomaly States Prediction Based on Artificial Techniques

Raghda Azad HassanStudent, Department of Software, College of Computer & Math., University of Mosul, IraqIbrahim Ahmed SalehProfessor, Department of Software, College of Computer & Math., University of Mosul, Iraq

Vol 8 No 3 (2024): Volume 8, Issue 3, March 2024 | Pages: 173-180

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 04-04-2024

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Abstract

Predicting software anomaly is essential for improving software quality and saving costs and time associated with software testing and maintenance in advanced stages life of software development. Complex software systems can be made more reliable and field failures reduced by having the ability to anticipate failures before they occur, as the field of forecasting has witnessed. Software defect prediction (SDP) has seen recent developments, such as combining several classification algorithms to create an ensemble or hybrid approach. Many laterals have been conducted in the field of predicting, including predicting anomalies and disruptions in performance and predicting software errors. This paper presents a study and review of the literature on predicting anomalies in software systems, strategies and methods for detecting them, and a brief overview of predicting defects and future trends in forecasting, as the results of the reviews showed. Because ensemble predictors can, in some cases, enhance bug detection performance, many problems have been solved by machine learning techniques as a result of this recent success.

Keywords

software engineering, ensemble learning, software anomaly detection, Software defect prediction


Citation of this Article

          

Raghda Azad Hassan, Ibrahim Ahmed Saleh, “A Survey of Software Systems Anomaly States Prediction Based on Artificial Techniques”, Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 8, Issue 3, pp 173-180, March 2024. Article DOI https://doi.org/10.47001/IRJIET/2024.803023

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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