Abstract
In cyber-physical systems (CPS), physical behaviors are typically controlled by digital hardware. As a consequence, continuous behaviors are discretized by sampling and quantization prior to their processing. Quantifying the similarity between CPS behaviors and their specification is an important ingredient in evaluating correctness and quality of such systems. We propose a novel procedure for measuring robustness between digitized CPS signals and signal temporal logic (STL) specifications. We first equip STL with quantitative semantics based on the weighted edit distance, a metric that quantifies both space and time mismatches between digitized CPS behaviors. We then develop a dynamic programming algorithm for computing the robustness degree between digitized signals and STL specifications. In order to promote hardware-based monitors we implemented our approach in FPGA. We evaluated it on automotive benchmarks defined by research community, and also on realistic data obtained from magnetic sensor used in modern cars.
Highlights
Cyber-physical systems (CPS) integrate heterogeneous collaborative components that are interconnected between themselves and their physical environment
We study signal temporal logic (STL) with both past and future operators interpreted over digital signals of finite length
We are allowed to assume that the configuration of Single Edge Nibble Transmission (SENT) frame is static and its structure cannot change during runtime
Summary
Cyber-physical systems (CPS) integrate heterogeneous collaborative components that are interconnected between themselves and their physical environment. They exhibit complex behaviors that often combine discrete and continuous dynamics. The sophistication, complexity and heterogeneity of CPS makes their verification a difficult task. Runtime monitoring addresses this problem by providing a formal, yet scalable, verification method. It achieves both rigor and efficiency by enabling evaluation of systems according to the properties of their individual behaviors. STL is a formal specification language for describing properties of continuous and hybrid behaviors. The robustness degree provides a finer measure of how far is the behavior from satisfying or violating of the specification
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