• Title/Summary/Keyword: Satisfiability Modulo Theory

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Test Case Generation For Simulink/Stateflow Model Using Yices and Model Information (Yices와 모델 정보를 이용한 Simulink/Stateflow 모델의 테스트 케이스 생성 기법)

  • Park, Han Gon;Chung, Kihyun;Choi, Kyunghee
    • KIPS Transactions on Software and Data Engineering
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    • v.6 no.6
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    • pp.293-302
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    • 2017
  • This paper proposes a method that generates test cases from Simulink/Stateflow(SL/SF) using a SMT (Satisfiability Modulo Theory) solver, Yices and information of SL/SF model. The most difficult problem to generate test cases from SL/SF model is to solve reachability problem. In the propose method, Yices and the tables built with the model information are utilized to solve the reachability problem. The method utilizes the SMT model, that is the SL/SF model transformed in Yices. The tables built from SL/SF are used for backward processing of the proposed method and increases test generation efficiency. A commercial refrigerator model and two car ECU (Electrical Control Unit) models are used to evaluate the performance of the proposed algorithm..

Generating Test Cases of Simulink/Stateflow Model Based on RRT Algorithm Using Heuristic Input Analysis (휴리스틱 입력 분석을 이용한 RRT 기반의 Simulink/Stateflow 모델 테스트 케이스 생성 기법)

  • Park, Hyeon Sang;Choi, Kyung Hee;Chung, Ki Hyun
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.12
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    • pp.829-840
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    • 2013
  • This paper proposes a modified RRT (Rapidly exploring Random Tree) algorithm utilizing a heuristic input analysis and suggests a test case generation method from Simulink/Stateflow model using the proposed RRT algorithm. Though the typical RRT algorithm is an efficient method to solve the reachability problem to definitely be resolved for generating test cases of model in a black box manner, it has a drawback, an inefficiency of test case generation that comes from generating random inputs without considering the internal states and the test targets of model. The proposed test case generation method increases efficiency of test case generation by analyzing the test targets to be satisfied at the current state and heuristically deciding the inputs of model based on the analysis during expanding an RRT, while maintaining the merit of RRT algorithm. The proposed method is evaluated with the models of ECUs embedded in a commercial passenger's car. The performance is compared with that of the typical RRT algorithm.