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.
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