---
title: "ICST (A): papers and universities"
description: "ICST (International Conference on Software Testing, Verification and Validation) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 264 of its papers from 2024–2026 (58 in 2024, 109 in 2025, 97 in 2026). By the countries of the authors' institutions, the most papers come from the United States (45), Germany (33) and Switzerland (20)."
url: https://scholar4ai.com/proceedings/icst
markdown_url: https://scholar4ai.com/proceedings/icst.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "ICST (International Conference on Software Testing, Verification and Validation) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 264 of its papers from 2024–2026 (58 in 2024, 109 in 2025, 97 in… (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)
---

# ICST: International Conference on Software Testing, Verification and Validation — papers and institutions, 2024–2026

Papers of ICST, International Conference on Software Testing, Verification and Validation (CORE rank A; field: Software engineering), 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

- ICST (International Conference on Software Testing, Verification and Validation) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 264 of its papers from 2024–2026 (58 in 2024, 109 in 2025, 97 in 2026).
- By the countries of the authors' institutions, the most papers come from the United States (45), Germany (33) and Switzerland (20).
- The institutions with the most papers are Università della Svizzera italiana (14), Technical University of Munich (11) and Korea Advanced Institute of Science and Technology (8).
- Its most-cited paper of these years is “Understanding the Effectiveness of Large Language Models in Detecting Security Vulnerabilities” (2025), with 64 citations.

## Papers per year

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

| Year | Papers | With affiliations |
|---|---:|---:|
| 2024 | 58 | 49 |
| 2025 | 109 | 102 |
| 2026 | 97 | 87 |

## Sources

*Where OpenAlex lists the papers*

| OpenAlex source | Which papers |
|---|---|
| [S7407085955](https://openalex.org/S7407085955) | The conference's proceedings |

## Who publishes there

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

| # | Institution | Papers |
|---:|---|---:|
| 1 | Università della Svizzera italiana | 14 |
| 2 | Technical University of Munich | 11 |
| 3 | Korea Advanced Institute of Science and Technology | 8 |
| 4 | University of Luxembourg | 8 |
| 5 | [Delft University of Technology](https://scholar4ai.com/institutions/delft-university-of-technology.md) | 8 |
| 6 | University of Bern | 7 |
| 7 | University of Passau | 7 |
| 8 | Simula Research Laboratory | 7 |
| 9 | National Institute of Technology Warangal | 6 |
| 10 | National Institute of Informatics | 6 |

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

| # | Country | Papers |
|---:|---|---:|
| 1 | United States | 45 |
| 2 | Germany | 33 |
| 3 | Switzerland | 20 |
| 4 | Canada | 19 |
| 5 | South Korea | 19 |
| 6 | Italy | 17 |
| 7 | United Kingdom | 15 |
| 8 | China | 13 |
| 9 | Netherlands | 11 |
| 10 | Luxembourg | 9 |

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

| # | Keyword | Papers |
|---:|---|---:|
| 1 | software testing | 42 |
| 2 | [large language models](https://scholar4ai.com/keywords/large-language-models.md) | 41 |
| 3 | automated test generation | 15 |
| 4 | test case generation | 15 |
| 5 | continuous integration | 13 |
| 6 | mutation testing | 13 |
| 7 | test automation | 13 |
| 8 | flaky tests | 12 |
| 9 | simulation-based testing | 11 |
| 10 | code coverage | 10 |

## Most-cited papers

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

| # | Citations | Title | Published | Authors |
|---:|---:|---|---|---|
| 1 | 64 | [Understanding the Effectiveness of Large Language Models in Detecting Security Vulnerabilities](https://doi.org/10.1109/icst62969.2025.10988968) | 2025-03-31 | Avishree Khare, Saikat Dutta, Ziyang Li et al. |
| 2 | 39 | [Intent-Driven Mobile GUI Testing with Autonomous Large Language Model Agents](https://doi.org/10.1109/icst60714.2024.00020) | 2024-05-27 | Juyeon Yoon, ROBERT H. FELDT, Shin Yoo |
| 3 | 37 | [Are We Testing or Being Tested? Exploring the Practical Applications of Large Language Models in Software Testing](https://doi.org/10.1109/icst60714.2024.00039) | 2024-05-27 | Robson Santos, Ítalo Santos, Cleyton V. C. de Magalhães et al. |
| 4 | 26 | [Predicting Safety Misbehaviours in Autonomous Driving Systems Using Uncertainty Quantification](https://doi.org/10.1109/icst60714.2024.00016) | 2024-05-27 | Ruben Grewal, Paolo Tonella, Andrea Stocco |
| 5 | 26 | [METAL: Metamorphic Testing Framework for Analyzing Large-Language Model Qualities](https://doi.org/10.1109/icst60714.2024.00019) | 2024-05-27 | Sangwon Hyun, Mingyu Guo, Muhammad Ali Babar |
| 6 | 18 | [The GitHub Recent Bugs Dataset for Evaluating LLM-Based Debugging Applications](https://doi.org/10.1109/icst60714.2024.00049) | 2024-05-27 | Jae Yong Lee, Sungmin Kang, Juyeon Yoon et al. |
| 7 | 17 | [Test Wars: A Comparative Study of SBST, Symbolic Execution, and LLM-Based Approaches to Unit Test Generation](https://doi.org/10.1109/icst62969.2025.10989033) | 2025-03-31 | Azat Abdullin, Pouria Derakhshanfar, Annibale Panichella |
| 8 | 17 | [KAT: Dependency-Aware Automated API Testing with Large Language Models](https://doi.org/10.1109/icst60714.2024.00017) | 2024-05-27 | Tri Le, Thien Tran, Duy Minh Cao et al. |
| 9 | 16 | [ICST Tool Competition 2025 - Self-Driving Car Testing Track](https://doi.org/10.1109/icst62969.2025.10989045) | 2025-03-31 | Christian Birchler, Stefan Klikovits, Mattia Fazzini et al. |
| 10 | 15 | [Quantizing Large-Language Models for Predicting Flaky Tests](https://doi.org/10.1109/icst60714.2024.00018) | 2024-05-27 | Shanto Rahman, Abdelrahman Baz, Saša Misailovíc et al. |

## Cite this page

Scholar4AI. (2026). ICST: International Conference on Software Testing, Verification and Validation — papers and institutions, 2024–2026. Journal and Conference Research Rankings. Retrieved November 2, 2026, from https://scholar4ai.com/proceedings/icst

```bibtex
@misc{scholar4ai-proceedings-icst,
  author = {{Scholar4AI}},
  title = {ICST: International Conference on Software Testing, Verification and Validation — papers and institutions, 2024–2026},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/proceedings/icst}},
  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/).