Software Product Quality Metrics: A Systematic Mapping Study

被引:28
作者
Colakoglu, Fatima Nur [1 ]
Yazici, Ali [2 ]
Mishra, Alok [2 ,3 ]
机构
[1] HAVELSAN, TR-06510 Ankara, Turkey
[2] Atilim Univ, Dept Software Engn, TR-06830 Ankara, Turkey
[3] Molde Univ Coll Specialized Univ Logist, Dept Informat & Digitalizat, N-6410 Molde, Norway
关键词
Measurement; Quality assessment; Product design; Market research; Software quality; ISO Standards; Object oriented modeling; software product quality; metrics; systematic mapping; THRESHOLDS;
D O I
10.1109/ACCESS.2021.3054730
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:44647 / 44670
页数:24
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