Enhancing Dynamic Symbolic Execution by Automatically Learning Search Heuristics

We present a technique to automatically generate search heuristics for dynamic symbolic execution. A key challenge in dynamic symbolic execution is how to effectively explore the program's execution paths to achieve high code coverage in a limited time budget. Dynamic symbolic execution employs...

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Published in:IEEE transactions on software engineering Vol. 48; no. 9; pp. 3640 - 3663
Main Authors: Cha, Sooyoung, Hong, Seongjoon, Bak, Jiseong, Kim, Jingyoung, Lee, Junhee, Oh, Hakjoo
Format: Journal Article
Language:English
Published: New York IEEE 01.09.2022
IEEE Computer Society
Subjects:
Algorithms
concolic testing
Dynamic symbolic execution
execution-generated testing
Heuristic
Heuristic algorithms
Learning
Open source software
search heuristics
Search problems
Searching
Software algorithms
Software testing
Testing
ISSN:0098-5589, 1939-3520
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Abstract We present a technique to automatically generate search heuristics for dynamic symbolic execution. A key challenge in dynamic symbolic execution is how to effectively explore the program's execution paths to achieve high code coverage in a limited time budget. Dynamic symbolic execution employs a search heuristic to address this challenge, which favors exploring particular types of paths that are most likely to maximize the final coverage. However, manually designing a good search heuristic is nontrivial and typically ends up with suboptimal and unstable outcomes. The goal of this paper is to overcome this shortcoming of dynamic symbolic execution by automatically learning search heuristics. We define a class of search heuristics, namely a parametric search heuristic, and present an algorithm that efficiently finds an optimal heuristic for each subject program. Experimental results with industrial-strength symbolic execution tools (e.g., KLEE) show that our technique can successfully generate search heuristics that significantly outperform existing manually-crafted heuristics in terms of branch coverage and bug-finding.
AbstractList We present a technique to automatically generate search heuristics for dynamic symbolic execution. A key challenge in dynamic symbolic execution is how to effectively explore the program's execution paths to achieve high code coverage in a limited time budget. Dynamic symbolic execution employs a search heuristic to address this challenge, which favors exploring particular types of paths that are most likely to maximize the final coverage. However, manually designing a good search heuristic is nontrivial and typically ends up with suboptimal and unstable outcomes. The goal of this paper is to overcome this shortcoming of dynamic symbolic execution by automatically learning search heuristics. We define a class of search heuristics, namely a parametric search heuristic, and present an algorithm that efficiently finds an optimal heuristic for each subject program. Experimental results with industrial-strength symbolic execution tools (e.g., KLEE) show that our technique can successfully generate search heuristics that significantly outperform existing manually-crafted heuristics in terms of branch coverage and bug-finding.
Author Lee, Junhee
Cha, Sooyoung
Bak, Jiseong
Kim, Jingyoung
Oh, Hakjoo
Hong, Seongjoon
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Cites_doi 10.1109/ICSE.2012.6227146
10.1145/2110356.2110358
10.1145/3167132.3167289
10.1145/390016.808445
10.1145/2509136.2509552
10.1145/2408776.2408795
10.1145/2379776.2379787
10.1145/3236024.3236049
10.1109/ICST.2015.7102601
10.1145/2491411.2491425
10.14722/ndss.2016.23368
10.1109/ICSE-Companion.2019.00051
10.1145/1065010.1065036
10.1109/SP.2017.40
10.1145/3238147.3238227
10.1145/3133956.3134050
10.1007/11537328_2
10.1145/3092703.3092709
10.1145/2509136.2509553
10.1145/2786805.2786830
10.1145/1083246.1083256
10.1109/ICSE.2015.80
10.1145/2025113.2025180
10.1145/3180155.3180177
10.1109/DSN.2009.5270315
10.1145/2884781.2884843
10.1145/3180155.3180166
10.1109/ICSE.2009.5070545
10.1145/3338906.3338964
10.1145/3092703.3092728
10.1145/2635868.2635889
10.1007/978-3-662-49122-5_16
10.1109/ICST.2018.00020
10.1109/ICSE.2012.6227105
10.1109/SP.2017.23
10.1145/390016.808444
10.1109/ICSE.2013.6606559
10.1145/3180155.3180251
10.14722/ndss.2015.23294
10.1109/ASE.2008.40
10.1145/360248.360252
10.1145/2970276.2970364
10.1145/3238147.3238172
10.1109/ICSE.2007.41
10.1145/2635868.2635872
10.1007/3-540-45322-9_5
10.1145/2254064.2254088
10.1145/1180405.1180445
10.1145/1706299.1706307
10.1145/3182657
10.1109/TSE.2017.2659751
10.1109/ASE.2008.69
10.1145/2568225.2568293
10.1145/1081706.1081750
10.1145/1966445.1966463
10.1109/ICSTW.2011.100
10.1109/ICSE.2017.26
10.1109/ASE.2017.8115618
10.1145/2393596.2393636
10.1145/3238147.3238179
10.1007/978-3-540-73368-3_52
10.1109/TSE.1977.231144
10.1007/978-3-540-78800-3_27
10.1145/1190216.1190226
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References ref13
ref57
ref15
ref14
ref58
ref53
ref52
ref11
ref55
ref10
ref54
ref17
ref16
ref19
ref18
(ref56) 2017
kim (ref8) 2017
godefroid (ref21) 2008
ref51
ref50
dutertre (ref48) 2006
(ref32) 2008
ref45
ref42
ref41
ref44
ref43
ref49
ref7
(ref46) 2005
ref9
ref4
ref3
cadar (ref22) 2008
ref6
ref5
ref40
ref35
ref34
ref78
ref37
ref36
bugrara (ref29) 2013
ref31
ref75
zhang (ref64) 2018
ref74
ref33
ref77
ref76
ref2
ref1
ref39
ref38
ref71
ref70
sun (ref59) 2018
ref73
ref72
ref24
ref68
ref23
ref67
ref26
ref25
ref69
ref20
corteggiani (ref12) 2018
ref63
ref66
ref65
ref28
ref27
(ref47) 2018
ref60
wong (ref30) 2015
ref62
ref61
References_xml – ident: ref35
  doi: 10.1109/ICSE.2012.6227146
– ident: ref34
  doi: 10.1145/2110356.2110358
– ident: ref55
  doi: 10.1145/3167132.3167289
– ident: ref17
  doi: 10.1145/390016.808445
– ident: ref74
  doi: 10.1145/2509136.2509552
– ident: ref19
  doi: 10.1145/2408776.2408795
– start-page: 620
  year: 2015
  ident: ref30
  article-title: DASE: document-assisted symbolic execution for improving automated software testing
  publication-title: Proceedings of the International Conference on Software Engineering ICSE'94
– year: 2006
  ident: ref48
  article-title: The yices SMT solver
– ident: ref78
  doi: 10.1145/2379776.2379787
– ident: ref45
  doi: 10.1145/3236024.3236049
– ident: ref36
  doi: 10.1109/ICST.2015.7102601
– ident: ref60
  doi: 10.1145/2491411.2491425
– ident: ref9
  doi: 10.14722/ndss.2016.23368
– ident: ref14
  doi: 10.1109/ICSE-Companion.2019.00051
– ident: ref2
  doi: 10.1145/1065010.1065036
– ident: ref10
  doi: 10.1109/SP.2017.40
– ident: ref43
  doi: 10.1145/3238147.3238227
– year: 2017
  ident: ref56
– start-page: 14
  year: 2018
  ident: ref64
  article-title: Boost symbolic execution using dynamic state merging and forking
  publication-title: Proc Int Workshop Quantitative Approaches Softw Qual
– ident: ref11
  doi: 10.1145/3133956.3134050
– ident: ref3
  doi: 10.1007/11537328_2
– start-page: 689
  year: 2017
  ident: ref8
  article-title: CAB-Fuzz: Practical concolic testing techniques for COTS operating systems
  publication-title: Proc USENIX Annu Tech Conf
– ident: ref75
  doi: 10.1145/3092703.3092709
– ident: ref25
  doi: 10.1145/2509136.2509553
– ident: ref65
  doi: 10.1145/2786805.2786830
– ident: ref76
  doi: 10.1145/1083246.1083256
– ident: ref7
  doi: 10.1109/ICSE.2015.80
– ident: ref42
  doi: 10.1145/2025113.2025180
– ident: ref51
  doi: 10.1145/3180155.3180177
– ident: ref50
  doi: 10.1109/DSN.2009.5270315
– ident: ref6
  doi: 10.1145/2884781.2884843
– ident: ref26
  doi: 10.1145/3180155.3180166
– ident: ref52
  doi: 10.1109/ICSE.2009.5070545
– ident: ref44
  doi: 10.1145/3338906.3338964
– ident: ref70
  doi: 10.1145/3092703.3092728
– ident: ref66
  doi: 10.1145/2635868.2635889
– ident: ref40
  doi: 10.1007/978-3-662-49122-5_16
– ident: ref73
  doi: 10.1109/ICST.2018.00020
– ident: ref27
  doi: 10.1109/ICSE.2012.6227105
– ident: ref72
  doi: 10.1109/SP.2017.23
– ident: ref15
  doi: 10.1145/390016.808444
– ident: ref33
  doi: 10.1109/ICSE.2013.6606559
– start-page: 151
  year: 2008
  ident: ref21
  article-title: Automated whitebox fuzz testing
  publication-title: Proc Symp Network and Distributed System Security
– ident: ref39
  doi: 10.1145/3180155.3180251
– ident: ref57
  doi: 10.14722/ndss.2015.23294
– ident: ref54
  doi: 10.1109/ASE.2008.40
– ident: ref16
  doi: 10.1145/360248.360252
– ident: ref69
  doi: 10.1145/2970276.2970364
– ident: ref13
  doi: 10.1145/3238147.3238172
– ident: ref53
  doi: 10.1109/ICSE.2007.41
– ident: ref23
  doi: 10.1145/2635868.2635872
– start-page: 199
  year: 2013
  ident: ref29
  article-title: Redundant state detection for dynamic symbolic execution
  publication-title: Proc USENIX Conf Annu Tech Conf
– ident: ref67
  doi: 10.1007/3-540-45322-9_5
– ident: ref38
  doi: 10.1145/2254064.2254088
– year: 2005
  ident: ref46
– year: 2018
  ident: ref59
– ident: ref4
  doi: 10.1145/1180405.1180445
– ident: ref62
  doi: 10.1145/1706299.1706307
– ident: ref58
  doi: 10.1145/3182657
– ident: ref37
  doi: 10.1109/TSE.2017.2659751
– ident: ref20
  doi: 10.1109/ASE.2008.69
– ident: ref5
  doi: 10.1145/2568225.2568293
– ident: ref63
  doi: 10.1145/3238147.3238227
– ident: ref1
  doi: 10.1145/1081706.1081750
– ident: ref28
  doi: 10.1145/1966445.1966463
– ident: ref77
  doi: 10.1109/ICSTW.2011.100
– year: 2008
  ident: ref32
– ident: ref68
  doi: 10.1109/ICSE.2017.26
– ident: ref71
  doi: 10.1109/ASE.2017.8115618
– ident: ref24
  doi: 10.1145/2393596.2393636
– ident: ref31
  doi: 10.1145/3238147.3238179
– ident: ref49
  doi: 10.1007/978-3-540-73368-3_52
– ident: ref18
  doi: 10.1109/TSE.1977.231144
– ident: ref41
  doi: 10.1007/978-3-540-78800-3_27
– start-page: 309
  year: 2018
  ident: ref12
  article-title: Inception: System-wide security testing of real-world embedded systems software
  publication-title: Proc Usenix Secur Symp
– ident: ref61
  doi: 10.1145/1190216.1190226
– year: 2018
  ident: ref47
– start-page: 209
  year: 2008
  ident: ref22
  article-title: KLEE: Unassisted and automatic generation of high-coverage tests for complex systems programs
  publication-title: Proc 8th USENIX Conf Operating Syst Des Implementation
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Snippet We present a technique to automatically generate search heuristics for dynamic symbolic execution. A key challenge in dynamic symbolic execution is how to...
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SubjectTerms Algorithms
concolic testing
Dynamic symbolic execution
execution-generated testing
Heuristic
Heuristic algorithms
Learning
Open source software
search heuristics
Search problems
Searching
Software algorithms
Software testing
Testing
Title Enhancing Dynamic Symbolic Execution by Automatically Learning Search Heuristics
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