An Experimental Study of Software Metrics for Real-Time Software
H.A. Jensen, K. Vairavan
Abstract
H.A. Jensen, K. Vairavan
Abstract
The rising costs of software development and maintenance have naturally aroused intere5t in tools and measures to quantify and analyze software complexity. Many software metrics have been studied widely because of the potential usefulness in predicting the complexity and quality of software. Most of the work reported in this area has been related to nonreal-time software. In this paper we report and discuss the results of an experimental investigation of some important metrics and their relationship for a class of 202 Pascal programs used in a real-time distributed processing environment. While some of our observations confirm independent studies, we have noted significant differences. For instance the correlations between McCabe's control complexity measure and Halstead's metrics are low in comparison to a previous study. Studies of the type reported here are important for understanding the relationship between software metrics.
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The rising costs of software development and maintenance have naturally aroused intere5t in tools and measures to quantify and analyze software complexity. Many software metrics have been studied widely because of the potential usefulness in predicting the complexity and quality of software. Most of the work reported in this area has been related to nonreal-time software. In this paper we report and discuss the results of an experimental investigation of some important metrics and their relationship for a class of 202 Pascal programs used in a real-time distributed processing environment. While some of our observations confirm independent studies, we have noted significant differences. For instance the correlations between McCabe's control complexity measure and Halstead's metrics are low in comparison to a previous study. Studies of the type reported here are important for understanding the relationship between software metrics.
Key concepts: Computer science, Software metric, Software sizing, Software construction, Software, Programming complexity, Software quality, Software development