The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Grammar-based whitebox fuzzing
Abstract
Whitebox fuzzing is a form of automatic dynamic test generation, based on symbolic execution and constraint solving, designed for security testing of large applications. Unfortunately, the current effectiveness of whitebox fuzzing is limited when testing applications with highly-structured inputs, such as compilers and interpreters. These applications process their inputs in stages, such as lexing, parsing and evaluation. Due to the enormous number of control paths in early processing stages, whitebox fuzzing rarely reaches parts of the application beyond those first stages.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Introduction to automata theory, languages and computation
(1981) · Mathematics and Computers in Simulation · doi:10.1016/0378-4754(81)90068-9 · Cited by 10,699
Introduction to automata theory, languages, and computation
(1980) · Computer Languages · doi:10.1016/0096-0551(80)90011-9 · Cited by 6,824
Symbolic execution and program testing
King, J. C. (1976) · Communications of the ACM · doi:10.1145/360248.360252 · Cited by 3,031
DART: directed automated random testing
Godefroid, P., Klarlund, N., & Sen, K. (2005) · ACM SIGPLAN Notices · doi:10.1145/1064978.1065036 · Cited by 2,067
Self-citation(2011) · IEEE Software · doi:10.1109/ms.2011.67 · Cited by 1,989
CUTE: a concolic unit testing engine for C
Sen, K., Marinov, D., & Agha, G. (2005) · Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering · doi:10.1145/1081706.1081750 · Cited by 1,651
DART: directed automated random testing
Godefroid, P., Klarlund, N., & Sen, K. (2005) · Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation · doi:10.1145/1065010.1065036 · Cited by 1,570
Self-citationAn empirical study of the reliability of UNIX utilities
Miller, B. P., Fredriksen, L., & So, B. (1990) · Communications of the ACM · doi:10.1145/96267.96279 · Cited by 1,281
Automated Whitebox Fuzz Testing.
Godefroid, P., Levin, M. Y., & Molnar, D. A. (2008) · Cited by 1,095
Self-citationQuickCheck: a lightweight tool for random testing of Haskell programs
Claessen, K., & Hughes, J. (2011) · ACM SIGPLAN Notices · doi:10.1145/1988042.1988046 · Cited by 1,011
Cited by
Finding and understanding bugs in C compilers
Yang, X., Chen, Y., Eide, E., & Regehr, J. (2011) · Proceedings of the 32nd ACM SIGPLAN Conference on Programming Language Design and Implementation · doi:10.1145/1993498.1993532 · Cited by 825
An orchestrated survey of methodologies for automated software test case generation
Anand, S., Burke, E. K., Chen, T. Y., Clark, J., Cohen, M. B., Grieskamp, W., Harman, M., Harrold, M. J., McMinn, P., Bertolino, A., et al. (2013) · Journal of Systems and Software · doi:10.1016/j.jss.2013.02.061 · Cited by 668
Finding and understanding bugs in C compilers
Yang, X., Chen, Y., Eide, E., & Regehr, J. (2011) · ACM SIGPLAN Notices · doi:10.1145/1993316.1993532 · Cited by 586
(2021) · doi:10.1109/tse.2019.2946563 · Cited by 574
FairFuzz: a targeted mutation strategy for increasing greybox fuzz testing coverage
Lemieux, C., & Sen, K. (2018) · Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering · doi:10.1145/3238147.3238176 · Cited by 477
Metadata
- Authors
- Godefroid, P., Kiezun, A., & Levin, M. Y.
- Venue
- Proceedings of the 29th ACM SIGPLAN Conference on Programming Language Design and Implementation
- Publisher
- ACM
- Published
- 2008-06-07
- Pages
- 206-215
- ISSN
- 1531-7102 (ISSN-L)
- OpenAlex
- W2065948900
- Cited by
- 462
- References
- 35
- FWCI
- 14.37
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Grammar-based whitebox fuzzing. https://app.cochat.ai/papers/10.1145/1375581.1375607
- The paper
- Godefroid, P., Kiezun, A., & Levin, M. Y. (2008). Grammar-based whitebox fuzzing. Proceedings of the 29th ACM SIGPLAN Conference on Programming Language Design and Implementation. https://doi.org/10.1145/1375581.1375607
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.