The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Predicting vulnerable software components
Abstract
Where do most vulnerabilities occur in software? Our Vulture tool automatically mines existing vulnerability databases and version archives to map past vulnerabilities to components. The resulting ranking of the most vulnerable components is a perfect base for further investigations on what makes components vulnerable.
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Citations
Cites
The Nature of Statistical Learning Theory
Vapnik, V. N. (1995) · doi:10.1007/978-1-4757-2440-0 · Cited by 39,138
The Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970
The Elements of Statistical Learning
Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162
Cited by
Shin, Y., Meneely, A., Williams, L., & Osborne, J. A. (2011) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2010.81 · Cited by 607
Predicting Vulnerable Software Components via Text Mining
Scandariato, R., Walden, J., Hovsepyan, A., & Joosen, W. (2014) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2014.2340398 · Cited by 337
Vulnerability detection with fine-grained interpretations
Li, Y., Wang, S., & Nguyen, T. N. (2021) · Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering · doi:10.1145/3468264.3468597 · Cited by 282
On the reliability of coverage-based fuzzer benchmarking
Böhme, M., Szekeres, L., & Metzman, J. (2022) · Proceedings of the 44th International Conference on Software Engineering · doi:10.1145/3510003.3510230 · Cited by 104
On the Relationship between Program Evolution and Fault-Proneness: An Empirical Study
Jaafar, F., Hassaine, S., Gueheneuc, Y., Hamel, S., & Adams, B. (2013) · 2013 17th European Conference on Software Maintenance and Reengineering · doi:10.1109/csmr.2013.12 · Cited by 5
Metadata
- Authors
- Neuhaus, S., Zimmermann, T., Holler, C., & Zeller, A.
- Venue
- Proceedings of the 14th ACM conference on Computer and communications security
- Publisher
- ACM
- Published
- 2007-10-28
- Pages
- 529-540
- ISSN
- 1543-7221 (ISSN-L)
- OpenAlex
- W2166336492
- Cited by
- 416
- References
- 3
- FWCI
- 12.36
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Predicting vulnerable software components. https://app.cochat.ai/papers/10.1145/1315245.1315311
- The paper
- Neuhaus, S., Zimmermann, T., Holler, C., & Zeller, A. (2007). Predicting vulnerable software components. Proceedings of the 14th ACM conference on Computer and communications security. https://doi.org/10.1145/1315245.1315311
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.
