Software Quality Metrics and their Impact on Embedded Software

Although many improvements for software development are proposed by software engineers, the embedded system community faces a hard task in applying these improvements to software development, due to the strong dependence between software and hardware in embedded systems, which raises a trade-off between software quality, measured by traditional metrics, and optimization for a specific platform. Traditional software quality concerns reuse, abstraction, coupling, and coherence. Such concepts are usually in conflict with performance, memory footprint, and other physical metrics used for design evaluation in embedded systems. The purpose of this work is to evaluate the relationship between quality metrics for software products and physical metrics for embedded systems, in order to guide an embedded designer in selecting the best alternative design during design space exploration already at the model level. After the experiments, we could analyze the correlation between these metrics and highlight the behavior for quality and physical metrics, which help us to better understand the trade-off between reuse and optimization.