The DOI matches its Crossref record; its reference list is not available.
Value-based program characterization and its application to software plagiarism detection
Abstract
Identifying similar or identical code fragments becomes much more challenging in code theft cases where plagiarizers can use various automated code transformation techniques to hide stolen code from being detected. Previous works in this field are largely limited in that (1) most of them cannot handle advanced obfuscation techniques; (2) the methods based on source code analysis are less practical since the source code of suspicious programs is typically not available until strong evidences are collected; and (3) those depending on the features of specific operating systems or programming languages have limited applicability.
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BPlag is not intended to measure functional equivalence, because tools for measuring similarity through functional equivalence already exist.
“Measuring functional equivalence is not the purpose of BPlag as there are already tools that exist to measure similarity through functional equivalence (e.g.[14], [31], [32], [34], [35]).”
From Academic Source Code Plagiarism Detection by Measuring Program Behavioral Similarity (2021) · cites this paper as [32]
VaPD determines program similarity by analysing, at runtime, the values held in memory while a program executes.
“VaPD identifies program similarity through runtime execution analysis of the values stored in memory during program execution.”
From Academic Source Code Plagiarism Detection by Measuring Program Behavioral Similarity (2021) · cites this paper as [32]
VaPD characterises programs using a fingerprinting method based on values.
“VaPD implements a value-based fingerprinting method to characterise programs.”
From Academic Source Code Plagiarism Detection by Measuring Program Behavioral Similarity (2021) · cites this paper as [32]
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References 33 · Cited by 83
Research works printed but not linked: 29
- 10.5555/832303.836911 · DOI
- 10.5555/998675.999466 · DOI
- 10.5555/850947.853341 · DOI
- 10.1007/978-3-540-70542-0_8 · DOI
- 10.1109/MSECP.2003.1219058 · DOI
- 10.1145/268946.268962 · DOI
- Drape S., 2007, Slicing aided design of obfuscating transforms, ICIS, 00, 1019
- Egele M., 2007, USENIX Annual Technical Conference, 233
- 10.1145/1368088.1368132 · DOI
- 10.1145/1268784.1268807 · DOI
- 10.1109/ICSE.2007.30 · DOI · Paper page
- 10.1145/1287624.1287634 · DOI
- 10.1109/TSE.2002.1019480 · DOI
- 10.1007/11424925_2 · DOI
- Kontogiannis K., 1995, Working Notes of 3rd Workshop on AI and Software Engineering
- 10.5555/832308.837142 · DOI
- 10.1145/1150402.1150522 · DOI · Paper page
- 10.1145/1111542.1111566 · DOI
- 10.1145/1066677.1066753 · DOI
- 10.1007/978-3-540-30144-8_34 · DOI
- Newsome J., 2005, NDSS '05
- Prechelt L., 2000, Universal Computer Science
- 10.1145/1321631.1321672 · DOI
- 10.1145/1572272.1572287 · DOI
- Tamada H., 2004, IASTED SE '04
- Tamada H., 2004, Int'l Symp. on Future Software Technology (ISFST)
- Truong N., 2004, ACE '04: Proc. of the 6th conf. on Australasian computing education
- 10.1145/1653662.1653696 · DOI · Paper page
- 10.1002/spe.4380210706 · DOI
Metadata
- Authors
- Jhi, Y.-C., Wang, X., Jia, X., Zhu, S., Liu, P., & Wu, D.
- Affiliations
- Pennsylvania State University (US)
- Chinese Academy of Sciences (CN)
- Venue
- Proceedings of the 33rd International Conference on Software Engineering
- Publisher
- ACM
- Published
- 2011-05-21
- Pages
- 756-765
- ISSN
- 0270-5257 (ISSN-L)
- OpenAlex
- W2145657894
- Cited by
- 83
- References
- 33
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 2 · 2023: 4 · 2022: 7 · 2021: 4 · 2020: 10 · 2019: 6 · 2018: 7 · 2017: 11 · 2016: 10 · 2015: 7 · 2014: 6 · 2013: 3 · 2012: 4
- FWCI
- 3.12
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) (publishedVersion)
- Funders
- National Natural Science Foundation of China
- Air Force Office of Scientific Research
- Topics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Social Sciences › Education › Academic integrity and plagiarism
- Physical Sciences › Computer Science › Hardware and Architecture › Physical Unclonable Functions (PUFs) and Hardware Security
- Keywords
- software plagiarism detection, code obfuscation, program characterization, binary analysis
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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