Automated Synthesis of Safe Timing Behaviors for Requirements Models using CCSL

• Published in: IEEE transactions on computer-aided design of integrated circuits and systems 2023-12, Vol.42 (12), p.1-1
• Main Authors: Hu, Ming, Xia, Jun, Zhang, Min, Chen, Xiaohong, Mallet, Frederic, Chen, Mingsong
• Format: Article
• Language: English
• Subjects: Automation; Behavioral sciences; CCSL; Clocks; Complexity; Computational modeling; Computer Science; Constraint modelling; Embedded systems; Engineers; Integrated circuit modeling; LTL; Requirement Model; Safety; Safety critical; Safety Timing Property; Specification and description languages; Specifications; Synthesis; Timing; Unified modeling language
• ISSN: 0278-0070; 1937-4151
• DOI: 10.1109/TCAD.2023.3285412

As a promising requirement-level specification language for timing behavior modeling, the Clock Constraint Specification Language (CCSL) has become popular in the model-driven design community for safety-critical embedded systems. However, due to the skyrocketing design complexity, in practice, it is hard for requirement engineers to accurately construct requirement models with expected timing behaviors using CCSL, especially for safe timing behaviors. Although more and more CCSL synthesis approaches are designed to facilitate the generation of CCSL specifications, most of them cannot be used directly for the synthesis of requirements models. This is because existing CCSL synthesis methods: i) focus on filling the holes of CCSL constraints rather than completing requirements models; and ii) rely heavily on limited observations of system behaviors, while the (temporal) safety properties of target systems are neglected. To address these issues, this paper proposes a novel method that enables the automated synthesis of safe timing behaviors for requirements models. By specifying the safety timing properties of target systems using safely-LTL, our approach adopts CCSL as an intermediate representation of requirement synthesis, where incomplete requirements models coupled with safely-LTL-based properties are encoded into CCSL constraints with holes. Guided by the samples (expected behaviors) provided by requirement engineers, our approach can automatically figure out the complete version of incomplete requirements models. Comprehensive experimental results on two complex case studies demonstrate that our approach can not only quickly and efficiently synthesize requirement models, but also guarantee that the synthesized models satisfy specified safety properties in Safely-LTL form.