Software Product Quality Metrics: A Systematic Mapping Study

• Published in: IEEE access Vol. 9; pp. 44647 - 44670
• Main Authors: Colakoglu, Fatima Nur, Yazici, Ali, Mishra, Alok
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial intelligence; Continuous improvement; Internet of Things; ISO Standards; Machine learning; Mapping; Measurement; metrics; New technology; Object oriented modeling; Product design; Product quality; Quality assessment; Robotics; Software; software product quality; Software quality; systematic mapping
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2021.3054730

In the current competitive world, producing quality products has become a prominent factor to succeed in business. In this respect, defining and following the software product quality metrics (SPQM) to detect the current quality situation and continuous improvement of systems have gained tremendous importance. Therefore, it is necessary to review the present studies in this area to allow for the analysis of the situation at hand, as well as to enable us to make predictions regarding the future research areas. The present research aims to analyze the active research areas and trends on this topic appearing in the literature during the last decade. A Systematic Mapping (SM) study was carried out on 70 articles and conference papers published between 2009 and 2019 on SPQM as indicated in their titles and abstract. The result is presented through graphics, explanations, and the mind mapping method. The outputs include the trend map between the years 2009 and 2019, knowledge about this area and measurement tools, issues determined to be open to development in this area, and conformity between conference papers, articles and internationally valid quality models. This study may serve as a foundation for future studies that aim to contribute to the development in this crucial field. Future SM studies might focus on this subject for measuring the quality of network performance and new technologies such as Artificial Intelligence (AI), Internet of things (IoT), Cloud of Things (CoT), Machine Learning, and Robotics.