Generating Automated and Online Test Oracles for Simulink Models with Continuous and Uncertain Behaviors

Menghi, Claudio; Nejati, Shiva; Gaaloul, Khouloud; Briand, Lionel C.

doi:10.48550/arxiv.1903.03399

Cited by 1 publication

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Dually, the max operator captures ∨. [27] into quantitative fitness functions to be used in the model testing approach in Figure 1(a) Translation to robustness metric [19,34]…”

Section: Cps Requirements and Patternsmentioning

confidence: 99%

“…. , s n } of signals at time t, we have R (S,t ) (φ) ≥ 0 if and only if φ holds over the set S at time t [19,34]. That is, we can infer boolean satisfaction of STL formulas based on their fitness values computed by R. In Table 3, ϵ is an infinitesimal positive value that is used to ensure the above relation between boolean satisfiability and fitness values of real-valued constraints (i.e., µ rel-op 0) and literals (i.e., ⊤, ⊥, and s B ) in the STL grammar.…”

Section: Cps Requirements and Patternsmentioning

confidence: 99%

See 1 more Smart Citation

Evaluating model testing and model checking for finding requirements violations in Simulink models

Nejati

Gaaloul

Menghi

et al. 2019

Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of

Self Cite

View full text Add to dashboard Cite

Matlab/Simulink is a development and simulation language that is widely used by the Cyber-Physical System (CPS) industry to model dynamical systems. There are two mainstream approaches to verify CPS Simulink models: model testing that attempts to identify failures in models by executing them for a number of sampled test inputs, and model checking that attempts to exhaustively check the correctness of models against some given formal properties. In this paper, we present an industrial Simulink model benchmark, provide a categorization of different model types in the benchmark, describe the recurring logical patterns in the model requirements, and discuss the results of applying model checking and model testing approaches to identify requirements violations in the benchmarked models. Based on the results, we discuss the strengths and weaknesses of model testing and model checking. Our results further suggest that model checking and model testing are complementary and by combining them, we can significantly enhance the capabilities of each of these approaches individually. We conclude by providing guidelines as to how the two approaches can be best applied together.

show abstract

“…Dually, the max operator captures ∨. [27] into quantitative fitness functions to be used in the model testing approach in Figure 1(a) Translation to robustness metric [19,34]…”

Section: Cps Requirements and Patternsmentioning

confidence: 99%

Section: Cps Requirements and Patternsmentioning

confidence: 99%