The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
The trace partitioning abstract domain
Open accessAbstract
In order to achieve better precision of abstract interpretation-based static analysis, we introduce a new generic abstract domain, the trace partitioning abstract domain. We develop a theoretical framework allowing a wide range of instantiations of the domain, proving that all these instantiations give correct results. From this theoretical framework, we go into implementation details of a particular instance developed in the Astrée static analyzer. We show how the domain is automatically configured in Astrée and the gain and cost in terms of performance and precision.
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
Cousot, P., & Cousot, R. (1977) · Proceedings of the 4th ACM SIGACT-SIGPLAN symposium on Principles of programming languages - POPL '77 · doi:10.1145/512950.512973 · Cited by 6,279
A static analyzer for large safety-critical software
Blanchet, B., Cousot, P., Cousot, R., Feret, J., Mauborgne, L., Miné, A., Monniaux, D., & Rival, X. (2003) · Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation · doi:10.1145/781131.781153 · Cited by 330
Self-citationBlanchet, B., Cousot, P., Cousot, R., Feret, J., Mauborgne, L., Miné, A., Monniaux, D., & Rival, X. (2002) · Lecture Notes in Computer Science · doi:10.1007/3-540-36377-7_5 · Cited by 202
Self-citationThe Arithmetic-Geometric Progression Abstract Domain
Feret, J. (2005) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-30579-8_3 · Cited by 37
Cited by
Ascertaining Uncertainty for Efficient Exact Cache Analysis
Touzeau, V., Maïza, C., Monniaux, D., & Reineke, J. (2017) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-63390-9_2 · Cited by 267
Metadata
- Authors
- Rival, X., & Mauborgne, L.
- Venue
- ACM Transactions on Programming Languages and Systems
- Published
- 2007-08-02
- Volume
- 29
- Issue
- 5
- Pages
- 26
- ISSN
- 0164-0925 (ISSN-L)
- 1558-4593
- OpenAlex
- W2044870852
- Cited by
- 184
- References
- 4
- FWCI
- 7.09
- Type
- journal article
- Language
- en
- Open access
- bronze
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: The trace partitioning abstract domain. https://app.cochat.ai/papers/10.1145/1275497.1275501
- The paper
- Rival, X., & Mauborgne, L. (2007). The trace partitioning abstract domain. ACM Transactions on Programming Languages and Systems. https://doi.org/10.1145/1275497.1275501
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.
