---
title: "CAV (A*): papers and universities"
description: "CAV (Computer Aided Verification) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 232 of its papers from 2024–2026 (69 in 2024, 81 in 2025, 82 in 2026). By the countries of the authors' institutions, the most papers come from the United States (78), Germany (44) and China (33)."
url: https://scholar4ai.com/proceedings/cav
markdown_url: https://scholar4ai.com/proceedings/cav.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "CAV (Computer Aided Verification) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 232 of its papers from 2024–2026 (69 in 2024, 81 in 2025, 82 in 2026). (as of 2026-11-02)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-02T12:20:52+09:00
window: 2026-10-04 to 2026-11-02
source: OpenAlex (CC0)
---

# CAV: Computer Aided Verification — papers and institutions, 2024–2026

Papers of CAV, Computer Aided Verification (CORE rank A*; field: Software engineering, Theory of computation), 2024–2026: per year, the institutions, countries and topics, and the most-cited papers. Ranks are those of the CORE Conference Rankings, edition ICORE2026 (portal.core.edu.au), applied to every year shown. Papers are the works OpenAlex lists for the conference's proceedings, or for the issues of a conference-linked journal that publishes its papers (such as PACMPL, PVLDB or ACM TOG), by publication year; workshops, companion volumes, posters and Findings are left out. A paper counts once for each institution and country among its authors' affiliations as OpenAlex assigns them; papers without affiliations in OpenAlex count for none. For conferences published in book series that OpenAlex files as one source (LNCS, LIPIcs, SIAM and IOS Press proceedings), the papers are found by DOI: those of the volumes with the conference's title in Crossref, or LIPIcs DOIs, which name the conference. Conferences without DOIs (PMLR, USENIX, OpenReview) are listed without counts. A dash (–) for a year means OpenAlex has no papers of the conference for it yet: the proceedings are not published or indexed yet, or the conference did not meet that year (some meet every other year). 2026 counts what OpenAlex had indexed by 2026-11-02.

All conferences: https://scholar4ai.com/proceedings.md

## Key findings

- CAV (Computer Aided Verification) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 232 of its papers from 2024–2026 (69 in 2024, 81 in 2025, 82 in 2026).
- By the countries of the authors' institutions, the most papers come from the United States (78), Germany (44) and China (33).
- The institutions with the most papers are TU Wien (13), Chinese Academy of Sciences (13) and Institute of Software (13).
- Its most-cited paper of these years is “Enchanting Program Specification Synthesis by Large Language Models Using Static Analysis and Program Verification” (2024), with 70 citations.

## Papers per year

*CAV papers per publication year in OpenAlex (–: not in OpenAlex yet)*

| Year | Papers | With affiliations |
|---|---:|---:|
| 2024 | 69 | 69 |
| 2025 | 81 | 81 |
| 2026 | 82 | 82 |

## Sources

*Where OpenAlex lists the papers*

| OpenAlex source | Which papers |
|---|---|
| [S106296714](https://openalex.org/S106296714) | Papers of the volumes titled “Computer Aided Verification” (LNCS), found by DOI through Crossref |

## Who publishes there

*Institutions with the most CAV papers, 2024–2026*

| # | Institution | Papers |
|---:|---|---:|
| 1 | TU Wien | 13 |
| 2 | [Chinese Academy of Sciences](https://scholar4ai.com/institutions/chinese-academy-of-sciences.md) | 13 |
| 3 | Institute of Software | 13 |
| 4 | [Stanford University](https://scholar4ai.com/institutions/stanford-university.md) | 13 |
| 5 | [University of Oxford](https://scholar4ai.com/institutions/university-of-oxford.md) | 10 |
| 6 | Helmholtz Center for Information Security | 10 |
| 7 | Radboud University Nijmegen | 9 |
| 8 | [University of Toronto](https://scholar4ai.com/institutions/university-of-toronto.md) | 9 |
| 9 | Technical University of Munich | 9 |
| 10 | ETH Zurich | 8 |

*Countries with the most CAV papers, 2024–2026*

| # | Country | Papers |
|---:|---|---:|
| 1 | United States | 78 |
| 2 | Germany | 44 |
| 3 | China | 33 |
| 4 | United Kingdom | 30 |
| 5 | Austria | 23 |
| 6 | Netherlands | 22 |
| 7 | Switzerland | 16 |
| 8 | Canada | 15 |
| 9 | Israel | 13 |
| 10 | France | 12 |

*Keywords with the most CAV papers, 2024–2026*

| # | Keyword | Papers |
|---:|---|---:|
| 1 | formal verification | 30 |
| 2 | SMT solvers | 27 |
| 3 | model checking | 19 |
| 4 | program verification | 16 |
| 5 | linear temporal logic | 12 |
| 6 | Markov decision process | 10 |
| 7 | automated verification | 9 |
| 8 | safety verification | 9 |
| 9 | satisfiability modulo theories | 8 |
| 10 | bounded model checking | 7 |

## Most-cited papers

*Most-cited CAV papers of 2024–2026 (citations counted by OpenAlex)*

| # | Citations | Title | Published | Authors |
|---:|---:|---|---|---|
| 1 | 70 | [Enchanting Program Specification Synthesis by Large Language Models Using Static Analysis and Program Verification](https://doi.org/10.1007/978-3-031-65630-9_16) | 2024-01-01 | Cheng Wen, Jialun Cao, Jie Su et al. |
| 2 | 64 | [CaDiCaL 2.0](https://doi.org/10.1007/978-3-031-65627-9_7) | 2024-01-01 | Armin Biere, Tobias Faller, Katalin Fazekas et al. |
| 3 | 53 | [Marabou 2.0: A Versatile Formal Analyzer of Neural Networks](https://doi.org/10.1007/978-3-031-65630-9_13) | 2024-01-01 | Haoze Wu, Omri Isac, Aleksandar Zeljić et al. |
| 4 | 19 | [End-to-End Mechanized Proof of a JIT-Accelerated eBPF Virtual Machine for IoT](https://doi.org/10.1007/978-3-031-65627-9_16) | 2024-01-01 | Shenghao Yuan, Frédéric Besson, Jean-Pierre Talpin |
| 5 | 19 | [Guiding Enumerative Program Synthesis with Large Language Models](https://doi.org/10.1007/978-3-031-65630-9_15) | 2024-01-01 | Yixuan Li, Julian Parsert, Elizabeth Polgreen |
| 6 | 15 | [lean-smt: An SMT Tactic for Discharging Proof Goals in Lean](https://doi.org/10.1007/978-3-031-98682-6_11) | 2025-01-01 | Abdalrhman Mohamed, Tomaz Mascarenhas, Harun Khan et al. |
| 7 | 15 | [Simulating Quantum Circuits by Model Counting](https://doi.org/10.1007/978-3-031-65633-0_25) | 2024-01-01 | Jingyi Mei, Marcello Bonsangue, Alfons Laarman |
| 8 | 14 | [Verifying Global Two-Safety Properties in Neural Networks with Confidence](https://doi.org/10.1007/978-3-031-65630-9_17) | 2024-01-01 | Anagha Athavale, Ezio Bartocci, Maria Christakis et al. |
| 9 | 14 | [The VerCors Verifier: A Progress Report](https://doi.org/10.1007/978-3-031-65630-9_1) | 2024-01-01 | Lukas Armborst, Pieter Bos, Lars B. van den Haak et al. |
| 10 | 13 | [Stochastic Omega-Regular Verification and Control with Supermartingales](https://doi.org/10.1007/978-3-031-65633-0_18) | 2024-01-01 | Alessandro Abate, Mirco Giacobbe, Diptarko Roy |

## Cite this page

Scholar4AI. (2026). CAV: Computer Aided Verification — papers and institutions, 2024–2026. Journal and Conference Research Rankings. Retrieved November 2, 2026, from https://scholar4ai.com/proceedings/cav

```bibtex
@misc{scholar4ai-proceedings-cav,
  author = {{Scholar4AI}},
  title = {CAV: Computer Aided Verification — papers and institutions, 2024–2026},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/proceedings/cav}},
  urldate = {2026-11-02},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).