Comprehensive Model-Driven Complexity Metrics for Software Systems
| Title | Comprehensive Model-Driven Complexity Metrics for Software Systems |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Masmali, O., Badreddin, O. |
| Conference Name | 2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C) |
| Date Published | Dec. 2020 |
| Publisher | IEEE |
| ISBN Number | 978-1-7281-8915-4 |
| Keywords | class diagram, Complexity Metric, Complexity theory, Measurement, Metrics, pubcrawl, security, security metrics, Software, software design, Software measurement, Software systems, state machine, sustainable development, UML, Unified modeling language |
| Abstract | Measuring software complexity is key in managing the software lifecycle and in controlling its maintenance. While there are well-established and comprehensive metrics to measure the complexity of the software code, assessment of the complexity of software designs remains elusive. Moreover, there are no clear guidelines to help software designers chose alternatives that reduce design complexity, improve design comprehensibility, and improve the maintainability of the software. This paper outlines a language independent approach to measuring software design complexity using objective and deterministic metrics. The paper outlines the metrics for two major software design notations; UML Class Diagrams and UML State Machines. The approach is based on the analysis of the design elements and their mutual interactions. The approach can be extended to cover other UML design notations. |
| URL | https://ieeexplore.ieee.org/document/9282696 |
| DOI | 10.1109/QRS-C51114.2020.00115 |
| Citation Key | masmali_comprehensive_2020 |