An information-theoretical framework for modeling component-based systems

Software systems tend to be large scale and complex with the inevitable increase in their functionalities. The increasing costs related to system development and maintenance in correlation to the software size requires new assessment tools for the newly evolving development methodologies. Taking advantage of existing tools and methodologies in a mature field is beneficial to relatively young, related disciplines. Therefore, this paper brings modeling techniques from a well-developed and mature discipline, information theory, into component-based software (CBS) engineering. Information-theoretic representation and analysis techniques in general, noiseless information channel concepts in particular, are good candidates to be adopted to model the dynamic behavior of software components and quantify the interaction between them. This modeling approach is realized by first modeling the component integration units of CBS with cubic control flowgraphs. The arcs in these models can be labeled as functions of parameters of their "hidden" components in the originating nodes or arcs, or both. Each of these labeled graphs defines a Shannon language. Then, a set of metrics, labeled as pervasive Shannon metrics is defined. Four case studies are demonstrated to show the applicability of the proposed metrics for assessment of CBS.