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Test Generation for Embedded Executables via Concolic Execution in a Real Environment
IEEE Transactions on Reliability, 2015Traditional software testing methods are not effective for testing embedded software thoroughly due to the fact that generating effective test inputs to cover all code is extremely difficult. In this work, we propose an automatic method to generate test inputs for embedded executables which is based on concolic execution. The core idea of our method is
Ting Chen
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RELEASE: Generating Exploits Using Loop-Aware Concolic Execution
2011 Fifth International Conference on Secure Software Integration and Reliability Improvement, 2011Automatically finding vulnerabilities and even generating exploits are desirable for software testing. For the protection of intellectual property and copyright, programs being tested may be lack of source code and symbol table information. Concolic execution is a novel technique, which takes advantage of the rapid executing speed of concrete execution
Shiuhpyng Shieh
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About the Concolic Execution and Symbolic ASM Function Promotion in CASM
Lecture Notes in Computer Science, 2021Abstract State Machines (ASMs) are a well-known state based formal method to describe systems at a very high level and can be executed either through a concrete or symbolic interpretation. By symbolically executing an ASM specification, certain properties can be checked by transforming the described ASM into a suitable input for model checkers or ...
Philipp Paulweber, Uwe Zdun, Zdun Uwe
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Backsolver: Adapting Preceding Execution Paths to Solve Constraints for Concolic Execution
ACM Transactions on Software Engineering and MethodologyConcolic execution follows the execution paths of concrete inputs, capable of generating new inputs for unexplored code by solving negated path constraints. However, implicit flows can hinder concolic execution, reducing the code coverage. Implicit flows occur when inputs influence control flow, and the control flow variation affects the values of some
Hongsong Zhu, Limin Sun
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Concolic Execution on Small-Size Binaries: Challenges and Empirical Study
2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2017Concolic execution has achieved great success in many binary analysis tasks. However, it is still not a primary option for industrial usage. A well-known reason is that concolic execution cannot scale up to large-size programs. Many research efforts have focused on improving its scalability.
Hui Xu, Yangfan Zhou, Michael R Lyu
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Optimizing decision making in concolic execution using reinforcement learning
2020 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW), 2020This paper presents an improvement to a new opensource testing tool capable of performing concolic execution on x86 binaries. The novelty is to use a reinforcement learning solution that reduces the number of symbolically executed states. It does so by learning a set of models that predict how efficiently it would be to change the conditions at various
Ciprian Paduraru +2 more
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Concolic execution for RPA testing
2023 27th International Conference on Engineering of Complex Computer Systems (ICECCS), 2023Ciprian Paduraru
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Parameterized Search Heuristic Prediction for Concolic Execution
2023 30th Asia-Pacific Software Engineering Conference (APSEC), 2023Maryam Mouzarani
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SIFOL: Solving Implicit Flows in Loops for Concolic Execution
2022 IEEE International Performance, Computing, and Communications Conference (IPCCC), 2022Zhihui Zhao, Hongsong Zhu, Limin Sun
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A Novel Concolic Execution Approach on Embedded Device
Proceedings of the 2020 4th International Conference on Cryptography, Security and Privacy, 2020With the widely use of embeded device, its security issues cause high attention. As one of the popular program testing techniques, symbolic execution tests a program by treating the program's input as symbols and interpreting the program over these inputs. Due to the complex environment and lackage of computing resources, there is no efficient symbolic
Chengwei Ai, Weiyu Dong, Zicong Gao
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