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Testing Cyber-Physical Systems Using a Line-Search Falsification Method

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Title: Testing Cyber-Physical Systems Using a Line-Search Falsification Method
Authors: Ramezani, Zahra, 1988, Claessen, Koen, 1975, Smallbone, Nicholas, 1986, Fabian, Martin, 1960, Åkesson, Knut, 1972
Source: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 41(8):2393-2406
Subject Terms: Optimization methods, Testing, Falsification, Computational modeling, Semantics, Additives, Linear programming, Simulation-based Optimization., Benchmark testing, Cyber-Physical Systems
Description: Cyber-physical systems (CPSs) are complex and exhibit both continuous and discrete dynamics, hence it is difficult to guarantee that they satisfy given specifications, i.e., the properties that must be fulfilled by the system. Falsification of temporal logic properties is a testing approach that searches for counterexamples of a given specification that can be used to increase the confidence that a CPS does fulfill its specifications. Falsification can be done using random search methods or optimization methods, both of which have their own benefits and drawbacks. This paper introduces two methods that exploit randomness to different degrees: the optimization-free Hybrid-Corner-Random (), and the direct-search method Line-search Falsification (). combines randomly chosen parameter values with extreme parameter values, which performs surprisingly well on benchmark evaluations. The gradient-free optimization-based LSF optimizes over line segments through a vector of inputs in the n-dimensional parameter space. The two methods are compared to the Nelder-Mead and SNOBFIT methods, using a well-known set of benchmark problems and shows better performance than any of the evaluated methods. Falsification can be done using random search methods or optimization methods. This paper proposes a method based on combining randomly chosen parameter values with parameter extreme values. Evaluation results on benchmark problems show that this method performs well on many of the problems. Optimization-based methods are needed when optimization-free methods do not perform well in falsification. The efficiency of the falsification is affected by the optimization methods used to search for inputs that might falsify the specifications. This paper presents a new optimization method for falsification, Line-search Falsification, where optimization is done over line segments through a vector of inputs in the n-dimensional parameter space. The evaluation results on the benchmark problems show that using this method improves the falsification performance by reducing the number of simulations necessary to falsify a specification. .
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  Data: Testing Cyber-Physical Systems Using a Line-Search Falsification Method
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  Data: <searchLink fieldCode="AR" term="%22Ramezani%2C+Zahra%22">Ramezani, Zahra</searchLink>, 1988<br /><searchLink fieldCode="AR" term="%22Claessen%2C+Koen%22">Claessen, Koen</searchLink>, 1975<br /><searchLink fieldCode="AR" term="%22Smallbone%2C+Nicholas%22">Smallbone, Nicholas</searchLink>, 1986<br /><searchLink fieldCode="AR" term="%22Fabian%2C+Martin%22">Fabian, Martin</searchLink>, 1960<br /><searchLink fieldCode="AR" term="%22Åkesson%2C+Knut%22">Åkesson, Knut</searchLink>, 1972
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  Data: <i>IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems</i>. 41(8):2393-2406
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  Data: <searchLink fieldCode="DE" term="%22Optimization+methods%22">Optimization methods</searchLink><br /><searchLink fieldCode="DE" term="%22Testing%22">Testing</searchLink><br /><searchLink fieldCode="DE" term="%22Falsification%22">Falsification</searchLink><br /><searchLink fieldCode="DE" term="%22Computational+modeling%22">Computational modeling</searchLink><br /><searchLink fieldCode="DE" term="%22Semantics%22">Semantics</searchLink><br /><searchLink fieldCode="DE" term="%22Additives%22">Additives</searchLink><br /><searchLink fieldCode="DE" term="%22Linear+programming%22">Linear programming</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation-based+Optimization%2E%22">Simulation-based Optimization.</searchLink><br /><searchLink fieldCode="DE" term="%22Benchmark+testing%22">Benchmark testing</searchLink><br /><searchLink fieldCode="DE" term="%22Cyber-Physical+Systems%22">Cyber-Physical Systems</searchLink>
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  Data: Cyber-physical systems (CPSs) are complex and exhibit both continuous and discrete dynamics, hence it is difficult to guarantee that they satisfy given specifications, i.e., the properties that must be fulfilled by the system. Falsification of temporal logic properties is a testing approach that searches for counterexamples of a given specification that can be used to increase the confidence that a CPS does fulfill its specifications. Falsification can be done using random search methods or optimization methods, both of which have their own benefits and drawbacks. This paper introduces two methods that exploit randomness to different degrees: the optimization-free Hybrid-Corner-Random (), and the direct-search method Line-search Falsification (). combines randomly chosen parameter values with extreme parameter values, which performs surprisingly well on benchmark evaluations. The gradient-free optimization-based LSF optimizes over line segments through a vector of inputs in the n-dimensional parameter space. The two methods are compared to the Nelder-Mead and SNOBFIT methods, using a well-known set of benchmark problems and shows better performance than any of the evaluated methods. Falsification can be done using random search methods or optimization methods. This paper proposes a method based on combining randomly chosen parameter values with parameter extreme values. Evaluation results on benchmark problems show that this method performs well on many of the problems. Optimization-based methods are needed when optimization-free methods do not perform well in falsification. The efficiency of the falsification is affected by the optimization methods used to search for inputs that might falsify the specifications. This paper presents a new optimization method for falsification, Line-search Falsification, where optimization is done over line segments through a vector of inputs in the n-dimensional parameter space. The evaluation results on the benchmark problems show that using this method improves the falsification performance by reducing the number of simulations necessary to falsify a specification. .
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        Value: 10.1109/TCAD.2021.3110740
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      – SubjectFull: Falsification
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      – SubjectFull: Computational modeling
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      – SubjectFull: Semantics
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      – SubjectFull: Benchmark testing
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      – SubjectFull: Cyber-Physical Systems
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      – TitleFull: Testing Cyber-Physical Systems Using a Line-Search Falsification Method
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