NPATH: a measure of execution path complexity and its applications
Communications of the ACM
Testability of Software Components
IEEE Transactions on Software Engineering
Software Testability: The New Verification
IEEE Software
Testability Measurements for Data Flow Designs
METRICS '97 Proceedings of the 4th International Symposium on Software Metrics
Identifying Test-Critical Dependencies
ICSM '02 Proceedings of the International Conference on Software Maintenance (ICSM'02)
Information Theory, Inference & Learning Algorithms
Information Theory, Inference & Learning Algorithms
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In this paper, we present our approach to analyze the testability of data-flow designs of reactive systems. We use the SATAN technology which is based on the information theory to model the information transfer in the system. We extend this technology with: a common formalism to represent data-flow designs produced from different CASE tools; a flattening mechanism to allow a flexible analysis of testability. We also improve the testability analysis by introducing: a statistical evaluation of information loss coefficient of operators, and a cyclic analysis that takes into account the recurring behavior of reactive systems. Our approach was integrated into a tool allowing an automatic analysis of testability of graphical data-flow designs of reactive systems.