demonstration

SCORE: a scalable concolic testing tool for reliable embedded software

Authors:

Moonzoo KimAuthors Info & Claims

ESEC/FSE '11: Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering

Pages 420 - 423

https://doi.org/10.1145/2025113.2025180

Published: 09 September 2011 Publication History

Abstract

Current industrial testing practices often generate test cases in a manual manner, which degrades both the effectiveness and efficiency of testing. To alleviate this problem, concolic testing generates test cases that can achieve high coverage in an automated fashion. One main task of concolic testing is to extract symbolic information from a concrete execution of a target program at runtime. Thus, a design decision on how to extract symbolic information affects efficiency, effectiveness, and applicability of concolic testing. We have developed a Scalable COncolic testing tool for REliable embedded software (SCORE) that targets embedded C programs. SCORE instruments a target C program to extract symbolic information and applies concolic testing to a target program in a scalable manner by utilizing a large number of distributed computing nodes. In this paper, we describe our design decisions that are implemented in SCORE and demonstrate the performance of SCORE through the experiments on the SIR benchmarks.

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Cited By

Nilizadeh FDashtbani HMouzarani M(2023)Parameterized Search Heuristic Prediction for Concolic Execution2023 30th Asia-Pacific Software Engineering Conference (APSEC)10.1109/APSEC60848.2023.00050(396-404)Online publication date: 4-Dec-2023
https://doi.org/10.1109/APSEC60848.2023.00050
Cha SHong SBak JKim JLee JOh H(2022)Enhancing Dynamic Symbolic Execution by Automatically Learning Search HeuristicsIEEE Transactions on Software Engineering10.1109/TSE.2021.310187048:9(3640-3663)Online publication date: 1-Sep-2022
https://doi.org/10.1109/TSE.2021.3101870
Barisal SDutta AGodboley SSahoo BMohapatra D(2022)Agility Based Coverage ImprovementLean and Agile Software Development10.1007/978-3-030-94238-0_10(170-186)Online publication date: 12-Jan-2022
https://doi.org/10.1007/978-3-030-94238-0_10
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Index Terms

SCORE: a scalable concolic testing tool for reliable embedded software

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Published In

cover image ACM Conferences

ESEC/FSE '11: Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering

September 2011

548 pages

ISBN:9781450304436

DOI:10.1145/2025113

General Chair:
Tibor Gyimóthy
University of Szeged, Hungary
,
Program Chair:
Andreas Zeller
Saarland University, Germany

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGSOFT: ACM Special Interest Group on Software Engineering

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Association for Computing Machinery

New York, NY, United States

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Published: 09 September 2011

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SIGSOFT

ESEC/FSE'11: Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering

September 5 - 9, 2011

Szeged, Hungary

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Overall Acceptance Rate 17 of 128 submissions, 13%

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Cited By

Nilizadeh FDashtbani HMouzarani M(2023)Parameterized Search Heuristic Prediction for Concolic Execution2023 30th Asia-Pacific Software Engineering Conference (APSEC)10.1109/APSEC60848.2023.00050(396-404)Online publication date: 4-Dec-2023
https://doi.org/10.1109/APSEC60848.2023.00050
Cha SHong SBak JKim JLee JOh H(2022)Enhancing Dynamic Symbolic Execution by Automatically Learning Search HeuristicsIEEE Transactions on Software Engineering10.1109/TSE.2021.310187048:9(3640-3663)Online publication date: 1-Sep-2022
https://doi.org/10.1109/TSE.2021.3101870
Barisal SDutta AGodboley SSahoo BMohapatra D(2022)Agility Based Coverage ImprovementLean and Agile Software Development10.1007/978-3-030-94238-0_10(170-186)Online publication date: 12-Jan-2022
https://doi.org/10.1007/978-3-030-94238-0_10
You SFindler RDimoulas C(2021)Sound and Complete Concolic Testing for Higher-order FunctionsProgramming Languages and Systems10.1007/978-3-030-72019-3_23(635-663)Online publication date: 23-Mar-2021
https://doi.org/10.1007/978-3-030-72019-3_23
Cha SOh HDumas MPfahl DApel SRusso A(2019)Concolic testing with adaptively changing search heuristicsProceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3338906.3338964(235-245)Online publication date: 12-Aug-2019
https://dl.acm.org/doi/10.1145/3338906.3338964
Kim YHong S(2019) DEMINER : test generation for high test coverage through mutant exploration Software Testing, Verification and Reliability10.1002/stvr.171531:1-2Online publication date: 28-Oct-2019
https://doi.org/10.1002/stvr.1715
Cha SLee SOh HHuchard MKästner CFraser G(2018)Template-guided concolic testing via online learningProceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering10.1145/3238147.3238227(408-418)Online publication date: 3-Sep-2018
https://dl.acm.org/doi/10.1145/3238147.3238227
Cha SHong SLee JOh HChaudron MCrnkovic IChechik MHarman M(2018)Automatically generating search heuristics for concolic testingProceedings of the 40th International Conference on Software Engineering10.1145/3180155.3180166(1244-1254)Online publication date: 27-May-2018
https://dl.acm.org/doi/10.1145/3180155.3180166
Kim YHong SKo BPhan DKim M(2018)Invasive Software Testing: Mutating Target Programs to Diversify Test Exploration for High Test Coverage2018 IEEE 11th International Conference on Software Testing, Verification and Validation (ICST)10.1109/ICST.2018.00032(239-249)Online publication date: Apr-2018
https://doi.org/10.1109/ICST.2018.00032
Godboley SDutta AMohapatra DMall R(2018)GECOJAPComputer Standards & Interfaces10.1016/j.csi.2017.04.00355:C(27-46)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1016/j.csi.2017.04.003
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