A Comparative Study of Different Software Complexity Metrics in Measuring Software Interoperability
Udara Rangika Herath1, Dilshan De Silva2, Virajini Godapitiya3, Piumi Navoda Wanni Arachchige4, Heshan Kotuwe Gedara5, Rashmi Premadasa6
1Udara Rangika Herath, Department of Information Technology, Sri Lanka Institute of Information Technology, Colombo,Western Province, Sri Lanka.
2Dilshan De Silva, Department of Information Technology, Sri Lanka Institute of Information Technology, Colombo, Western Province, Sri Lanka.
3Virajini Godapitiya, Department of Information Technology, Sri Lanka Institute of Information Technology, Colombo, Western Province, Sri Lanka.
4Piumi Navoda Wanni Arachchige, Department of Information Technology, Sri Lanka Institute of Information Technology, Colombo, Western Province, Sri Lanka.
5Heshan Kotuwe Gedara, Department of Information Technology, Sri Lanka Institute of Information Technology, Colombo,Western Province, Sri Lanka.
6Rashmi Premadasa, Department of Information Technology, Sri Lanka Institute of Information Technology, Colombo, Western Province, Sri Lanka.
Manuscript received on 02 May 2023 | Revised Manuscript received on 08 July 2023 | Manuscript Accepted on 15 July 2023 | Manuscript published on 30 July 2023 | PP: 1-4 | Volume-3 Issue-2, July 2023 | Retrieval Number: 100.1/ijsepm.B76520712223 | DOI: 10.54105/ijsepm.B7652.073223
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© The Authors. Published by Lattice Science Publication (LSP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Software interoperability is crucial for organizations that rely on multiple software systems to perform their operations. However, due to the complexity and variety of software systems, ensuring interoperability can be difficult. Measuring software complexity metrics can be used to identify potential problems and assess how well different interoperability strategies work. In this study, we investigated and compared the effectiveness of different software complexity metrics in measuring software interoperability. We used statistical methods to analyze data collected from a sample of software systems. The results of our study show that certain metrics, such as coupling and cohesion, are more effective than others in measuring software interoperability. By selecting appropriate metrics, developers can ensure better productivity, lower costs, and more adaptable use of software systems. The findings of this study have implications for the creation of software and can guide businesses in choosing the right criteria to achieve software interoperability.
Keywords: Complexity Metrics, Software Interoperability.
Scope of the Article: Software Testing and Integration