Software Quality Measurement Analysis based on Techniques, Criteria, Metrics, Models, and Datasets

• Published in: 2022 8th International Conference on Contemporary Information Technology and Mathematics (ICCITM) pp. 176 - 181
• Main Authors: Alnaish, Zakaria A. Hamed, Hasoon, Safwan O.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 31-08-2022
• Subjects: Costs; dataset; Deep learning; machine learning; Mathematical models; metrics; Roads; Software measurement; Software quality; Software quality measurement; Software reliability; techniques
• DOI: 10.1109/ICCITM56309.2022.10031990

Software quality measurement considers a very crucial process in developing software. Achieving high-quality software leads to produce software with high efficiency, and reliability and to reduce the software cost. This study intends to explain the most important factors that have direct effects on the software quality measurement process. In addition, this study summarized the software quality models; where each model could be classified into various scopes such as reliability, functionality, usability, portability, and maintainability. Moreover, the most recent techniques, which are used in software quality measurement, are concluded. Furthermore, the vital metrics that play an important role in the measurement process have been determined. Last but not least, the most commonly used datasets in software quality measurement in many aspects and scopes have been presented. As a result, this paper drew the road map for future work in the field of software engineering to accomplish more research work in developing novel software quality measurement approaches based on machine learning techniques such as deep learning methods and ensemble techniques that may give promising results.