The Experts below are selected from a list of 98193 Experts worldwide ranked by ideXlab platform
Sudeep Juvekar - One of the best experts on this subject based on the ideXlab platform.
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wise Automated Test generation for worst case complexity
International Conference on Software Engineering, 2009Co-Authors: Jacob Burnim, Sudeep JuvekarAbstract:Program analysis and Automated Test generation have primarily been used to find correctness bugs. We present complexity Testing, a novel Automated Test generation technique to find performance bugs. Our complexity Testing algorithm, which we call WISE (Worst-case Inputs from Symbolic Execution), operates on a program accepting inputs of arbitrary size. For each input size, WISE attempts to construct an input which exhibits the worst-case computational complexity of the program. WISE uses exhaustive Test generation for small input sizes and generalizes the result of executing the program on those inputs into an “input generator.” The generator is subsequently used to efficiently generate worst-case inputs for larger input sizes. We have performed experiments to demonstrate the utility of our approach on a set of standard data structures and algorithms. Our results show that WISE can effectively generate worstcase inputs for several of these benchmarks.
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wise Automated Test generation for worst case complexity
International Conference on Software Engineering, 2009Co-Authors: Jacob Burnim, Sudeep Juvekar, Koushik SenAbstract:Program analysis and Automated Test generation have primarily been used to find correctness bugs. We present complexity Testing, a novel Automated Test generation technique to find performance bugs. Our complexity Testing algorithm, which we call WISE (Worst-case Inputs from Symbolic Execution), operates on a program accepting inputs of arbitrary size. For each input size, WISE attempts to construct an input which exhibits the worst-case computational complexity of the program. WISE uses exhaustive Test generation for small input sizes and generalizes the result of executing the program on those inputs into an “input generator.” The generator is subsequently used to efficiently generate worst-case inputs for larger input sizes. We have performed experiments to demonstrate the utility of our approach on a set of standard data structures and algorithms. Our results show that WISE can effectively generate worstcase inputs for several of these benchmarks.
Insup Lee - One of the best experts on this subject based on the ideXlab platform.
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Automated Test coverage measurement for reactor protection system software implemented in function block diagram
Departmental Papers (CIS), 2012Co-Authors: Eunkyoung Jee, Sungdeok Cha, Suin Kim, Insup LeeAbstract:We present FBDTestMeasurer, an Automated Test coverage measurement tool for function block diagram (FBD) programs which are increasingly used in implementing safety critical systems such as nuclear reactor protection systems. We have defined new structural Test coverage criteria for FBD programs in which dataflow-centric characteristics of FBD programs were well reflected. Given an FBD program and a set of Test cases, FBDTestMeasurer produces Test coverage score and uncovered Test requirements with respect to the selected coverage criteria. Visual representation of uncovered data paths enables Testers to easily identify which parts of the program need to be Tested further. We found many aspects of the FBD logic that were not Tested sufficiently when conducting a case study using Test cases prepared by domain experts for reactor protection system software. Domain experts found this technique and tool highly intuitive and useful to measure the adequacy of FBD Testing and generate additional Test cases.
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SAFECOMP - Automated Test coverage measurement for reactor protection system software implemented in function block diagram
Lecture Notes in Computer Science, 2010Co-Authors: Eunkyoung Jee, Sungdeok Cha, Suin Kim, Insup LeeAbstract:We present FBDTestMeasurer, an Automated Test coverage measurement tool for function block diagram (FBD) programs which are increasingly used in implementing safety critical systems such as nuclear reactor protection systems. We have defined new structural Test coverage criteria for FBD programs in which dataflow-centric characteristics of FBD programs were well reflected. Given an FBD program and a set of Test cases, FBDTestMeasurer produces Test coverage score and uncovered Test requirements with respect to the selected coverage criteria. Visual representation of uncovered data paths enables Testers to easily identify which parts of the program need to be Tested further. We found many aspects of the FBD logic that were not Tested sufficiently when conducting a case study using Test cases prepared by domain experts for reactor protection system software. Domain experts found this technique and tool highly intuitive and useful to measure the adequacy of FBD Testing and generate additional Test cases.
Jacob Burnim - One of the best experts on this subject based on the ideXlab platform.
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wise Automated Test generation for worst case complexity
International Conference on Software Engineering, 2009Co-Authors: Jacob Burnim, Sudeep JuvekarAbstract:Program analysis and Automated Test generation have primarily been used to find correctness bugs. We present complexity Testing, a novel Automated Test generation technique to find performance bugs. Our complexity Testing algorithm, which we call WISE (Worst-case Inputs from Symbolic Execution), operates on a program accepting inputs of arbitrary size. For each input size, WISE attempts to construct an input which exhibits the worst-case computational complexity of the program. WISE uses exhaustive Test generation for small input sizes and generalizes the result of executing the program on those inputs into an “input generator.” The generator is subsequently used to efficiently generate worst-case inputs for larger input sizes. We have performed experiments to demonstrate the utility of our approach on a set of standard data structures and algorithms. Our results show that WISE can effectively generate worstcase inputs for several of these benchmarks.
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wise Automated Test generation for worst case complexity
International Conference on Software Engineering, 2009Co-Authors: Jacob Burnim, Sudeep Juvekar, Koushik SenAbstract:Program analysis and Automated Test generation have primarily been used to find correctness bugs. We present complexity Testing, a novel Automated Test generation technique to find performance bugs. Our complexity Testing algorithm, which we call WISE (Worst-case Inputs from Symbolic Execution), operates on a program accepting inputs of arbitrary size. For each input size, WISE attempts to construct an input which exhibits the worst-case computational complexity of the program. WISE uses exhaustive Test generation for small input sizes and generalizes the result of executing the program on those inputs into an “input generator.” The generator is subsequently used to efficiently generate worst-case inputs for larger input sizes. We have performed experiments to demonstrate the utility of our approach on a set of standard data structures and algorithms. Our results show that WISE can effectively generate worstcase inputs for several of these benchmarks.
Eunkyoung Jee - One of the best experts on this subject based on the ideXlab platform.
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Automated Test case generation for fbd programs implementing reactor protection system software
Software Testing Verification & Reliability, 2014Co-Authors: Eunkyoung Jee, Donghwan Shin, Sungdeok Cha, Jangsoo Lee, Doohwan BaeAbstract:Automated and effective Testing for function block diagram FBD programs has become an important issue, as FBD is increasingly used in implementing safety-critical systems. This work describes an Automated Test case generation technique for FBD programs and its associated tool-FBDTester. Given an FBD program and desired Test coverage criteria, FBDTester generates Test requirements and invokes the Satisfiability Modulo Theories solver iteratively to derive a set of Test cases. An industrial case study using reactor protection system software shows that the automatically generated Test suites detected at least 82% of the known faults, whereas manually generated Test cases only detected approximately 35%. Mutation analysis revealed that the automatically generated Test suites substantially outperformed manually generated ones. Although Test sequence generation requires some manual effort in the current FBDTester, it is apparent that the proposed approach significantly improves the efficiency and the reliability of FBD Testing. Copyright © 2014 John Wiley & Sons, Ltd.
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Automated Test coverage measurement for reactor protection system software implemented in function block diagram
Departmental Papers (CIS), 2012Co-Authors: Eunkyoung Jee, Sungdeok Cha, Suin Kim, Insup LeeAbstract:We present FBDTestMeasurer, an Automated Test coverage measurement tool for function block diagram (FBD) programs which are increasingly used in implementing safety critical systems such as nuclear reactor protection systems. We have defined new structural Test coverage criteria for FBD programs in which dataflow-centric characteristics of FBD programs were well reflected. Given an FBD program and a set of Test cases, FBDTestMeasurer produces Test coverage score and uncovered Test requirements with respect to the selected coverage criteria. Visual representation of uncovered data paths enables Testers to easily identify which parts of the program need to be Tested further. We found many aspects of the FBD logic that were not Tested sufficiently when conducting a case study using Test cases prepared by domain experts for reactor protection system software. Domain experts found this technique and tool highly intuitive and useful to measure the adequacy of FBD Testing and generate additional Test cases.
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SAFECOMP - Automated Test coverage measurement for reactor protection system software implemented in function block diagram
Lecture Notes in Computer Science, 2010Co-Authors: Eunkyoung Jee, Sungdeok Cha, Suin Kim, Insup LeeAbstract:We present FBDTestMeasurer, an Automated Test coverage measurement tool for function block diagram (FBD) programs which are increasingly used in implementing safety critical systems such as nuclear reactor protection systems. We have defined new structural Test coverage criteria for FBD programs in which dataflow-centric characteristics of FBD programs were well reflected. Given an FBD program and a set of Test cases, FBDTestMeasurer produces Test coverage score and uncovered Test requirements with respect to the selected coverage criteria. Visual representation of uncovered data paths enables Testers to easily identify which parts of the program need to be Tested further. We found many aspects of the FBD logic that were not Tested sufficiently when conducting a case study using Test cases prepared by domain experts for reactor protection system software. Domain experts found this technique and tool highly intuitive and useful to measure the adequacy of FBD Testing and generate additional Test cases.
Koushik Sen - One of the best experts on this subject based on the ideXlab platform.
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wise Automated Test generation for worst case complexity
International Conference on Software Engineering, 2009Co-Authors: Jacob Burnim, Sudeep Juvekar, Koushik SenAbstract:Program analysis and Automated Test generation have primarily been used to find correctness bugs. We present complexity Testing, a novel Automated Test generation technique to find performance bugs. Our complexity Testing algorithm, which we call WISE (Worst-case Inputs from Symbolic Execution), operates on a program accepting inputs of arbitrary size. For each input size, WISE attempts to construct an input which exhibits the worst-case computational complexity of the program. WISE uses exhaustive Test generation for small input sizes and generalizes the result of executing the program on those inputs into an “input generator.” The generator is subsequently used to efficiently generate worst-case inputs for larger input sizes. We have performed experiments to demonstrate the utility of our approach on a set of standard data structures and algorithms. Our results show that WISE can effectively generate worstcase inputs for several of these benchmarks.
