The DOI matches its Crossref record.
Integrating Verification and Repair into the Control Plane
Open accessAbstract
Network verification has made great progress recently, yet existing solutions are limited in their ability to handle specific protocols or implementation quirks or to diagnose and repair the cause of policy violations. In this positioning paper, we examine whether we can achieve the best of both worlds: full coverage of control plane protocols and decision processes combined with the ability to diagnose and repair the cause of violations. To this end, we leverage the happens-before relationships that exist between control plane I/Os (e.g., route advertisements and forwarding updates). These relationships allow us to identify when it is safe to employ a data plane verifier and track the root-cause of problematic forwarding updates. We show how we can capture errors before they are installed, automatically trace down the source of the error and roll-back the updates whenever possible.
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Prior to the advent of LLMs, research approached configuration as a synthesis problem defined by explicit correctness criteria, which typically focused on translating high level policies into device-level configurations, ensuring invariants are maintained, and protocol semantics are respected [115], [116], [17], [117].”
From Large language models for agentic NetOps and AIOps: Architectures, evaluation, and safety (2027) · cites this paper as [116]
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
No references could be resolved yet.
Research works printed but not linked: 31
- 10.1145/3098822.3098834 · DOI · Paper page
- 10.1145/2934872.2934909 · DOI
- 10.5555/1558977.1559000 · DOI
- 10.1145/1644893.1644909 · DOI
- 10.1145/2934872.2934910 · DOI
- 10.1145/2663716.2663755 · DOI
- 10.1145/2908080.2908124 · DOI
- 10.1007/978-3-319-63390-9_14 · DOI · Paper page
- 10.5555/3026877.3026895 · DOI
- 10.5555/2789770.2789803 · DOI
- 10.1145/3132747.3132753 · DOI
- 10.1145/2934872.2934876 · DOI
- 10.1145/2815675.2815684 · DOI
- 10.5555/2482626.2482638 · DOI
- 10.5555/2228298.2228311 · DOI
- 10.5555/2482626.2482630 · DOI
- 10.1145/359545.359563 · DOI · Paper page
- 10.1145/3132747.3132759 · DOI
- 10.1145/1142473.1142485 · DOI
- 10.1145/1090191.1080126 · DOI
- 10.5555/2789770.2789805 · DOI
- 10.1145/2018436.2018470 · DOI
- 10.1145/2774993.2775004 · DOI
- 10.5555/3154630.3154686 · DOI
- 10.1145/2934872.2934881 · DOI
- 10.1145/3009837.3009845 · DOI
- 10.1145/2983990.2984012 · DOI
- 10.1145/2619239.2626335 · DOI
- 10.5555/2789770.2789776 · DOI
- W. Zhou , S. Mapara , Y. Ren , Y. Li , A. Haeberlen , Z. Ives , B. T. Loo , and M. Sherr . Distributed time-aware provenance . In International Conference on Very Large Data Bases (VLDB) , 2013 . W. Zhou, S. Mapara, Y. Ren, Y. Li, A. Haeberlen, Z. Ives, B. T. Loo, and M. Sherr. Distributed time-aware provenance. In International Conference on Very Large Data Bases (VLDB), 2013.
- 10.1145/1807167.1807234 · DOI
Cited by
Sorted by citations
Large language models for agentic NetOps and AIOps: Architectures, evaluation, and safety
Bilal, M., Crowcroft, J., Wang, R., Xu, X., & Dustdar, S. (2027) · Computer Science Review · doi:10.1016/j.cosrev.2026.101075 · Cited by 10
Metadata
- Authors
- Gember-Jacobson, A., Raiciu, C., & Vanbever, L.
- Affiliations
- Colgate University (US)
- Universitatea Națională de Știință și Tehnologie Politehnica București (RO)
- ETH Zurich (CH)
- Venue
- Proceedings of the 16th ACM Workshop on Hot Topics in Networks
- Publisher
- ACM
- Published
- 2017-11-30
- Pages
- 129-135
- OpenAlex
- W2770728219
- Cited by
- 7
- References
- 0
- Citations by year
- 2025: 1 · 2024: 2 · 2023: 2 · 2022: 1 · 2020: 1
- FWCI
- 0.22
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- ACM Workshop on Hot Topics in Networks (HotNets) (publishedVersion)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, cc-by)
- Funders
- Superfluidity H2020 project (Horizon 2020, European Commission) (671566)
- National Science Foundation (CCF-1637427)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Formal Methods in Verification
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Traffic and Congestion Control
- Keywords
- network verification, network repair, control plane, policy violations, root cause diagnosis, rollback
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
