---
title: "ICSE (A*): papers and universities"
description: "ICSE (International Conference on Software Engineering) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 1,307 of its papers from 2024–2026 (395 in 2024, 342 in 2025, 570 in 2026). By the countries of the authors' institutions, the most papers come from China (423), the United States (368) and Canada (150)."
url: https://scholar4ai.com/proceedings/icse
markdown_url: https://scholar4ai.com/proceedings/icse.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "ICSE (International Conference on Software Engineering) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 1,307 of its papers from 2024–2026 (395 in 2024, 342 in 2025, 570 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)
---

# ICSE: International Conference on Software Engineering — papers and institutions, 2024–2026

Papers of ICSE, International Conference on Software Engineering (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

- ICSE (International Conference on Software Engineering) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 1,307 of its papers from 2024–2026 (395 in 2024, 342 in 2025, 570 in 2026).
- By the countries of the authors' institutions, the most papers come from China (423), the United States (368) and Canada (150).
- The institutions with the most papers are Singapore Management University (53), Zhejiang University (50) and Nanyang Technological University (45).
- Its most-cited paper of these years is “Using an LLM to Help With Code Understanding” (2024), with 370 citations.

## Papers per year

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

| Year | Papers | With affiliations |
|---|---:|---:|
| 2024 | 395 | 392 |
| 2025 | 342 | 319 |
| 2026 | 570 | 569 |

## Sources

*Where OpenAlex lists the papers*

| OpenAlex source | Which papers |
|---|---|
| [S4210203175](https://openalex.org/S4210203175) | The conference's proceedings |

## Who publishes there

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

| # | Institution | Papers |
|---:|---|---:|
| 1 | Singapore Management University | 53 |
| 2 | [Zhejiang University](https://scholar4ai.com/institutions/zhejiang-university.md) | 50 |
| 3 | [Nanyang Technological University](https://scholar4ai.com/institutions/nanyang-technological-university.md) | 45 |
| 4 | [Peking University](https://scholar4ai.com/institutions/peking-university.md) | 44 |
| 5 | [Chinese Academy of Sciences](https://scholar4ai.com/institutions/chinese-academy-of-sciences.md) | 39 |
| 6 | [Nanjing University](https://scholar4ai.com/institutions/nanjing-university.md) | 36 |
| 7 | [Sun Yat-sen University](https://scholar4ai.com/institutions/sun-yat-sen-university.md) | 34 |
| 8 | Huawei Technologies (China) | 34 |
| 9 | Carnegie Mellon University | 33 |
| 10 | [Monash University](https://scholar4ai.com/institutions/monash-university.md) | 32 |

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

| # | Country | Papers |
|---:|---|---:|
| 1 | China | 423 |
| 2 | United States | 368 |
| 3 | Canada | 150 |
| 4 | Germany | 133 |
| 5 | Singapore | 110 |
| 6 | Australia | 84 |
| 7 | Hong Kong | 63 |
| 8 | United Kingdom | 60 |
| 9 | Netherlands | 48 |
| 10 | Brazil | 40 |

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

| # | Keyword | Papers |
|---:|---|---:|
| 1 | [large language models](https://scholar4ai.com/keywords/large-language-models.md) | 331 |
| 2 | vulnerability detection | 53 |
| 3 | static analysis | 52 |
| 4 | open source software | 48 |
| 5 | bug detection | 47 |
| 6 | code generation | 46 |
| 7 | software engineering education | 41 |
| 8 | test case generation | 41 |
| 9 | prompt engineering | 37 |
| 10 | automated program repair | 34 |

## Most-cited papers

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

| # | Citations | Title | Published | Authors |
|---:|---:|---|---|---|
| 1 | 370 | [Using an LLM to Help With Code Understanding](https://doi.org/10.1145/3597503.3639187) | 2024-04-12 | Daye Nam, Andrew Macvean, Vincent Josua Hellendoorn et al. |
| 2 | 231 | [Fuzz4All: Universal Fuzzing with Large Language Models](https://doi.org/10.1145/3597503.3639121) | 2024-04-12 | Chunqiu Steven Xia, Matteo Paltenghi, Jia Le Tian et al. |
| 3 | 218 | [GPTScan: Detecting Logic Vulnerabilities in Smart Contracts by Combining GPT with Program Analysis](https://doi.org/10.1145/3597503.3639117) | 2024-04-12 | Yuqiang Sun, Daoyuan Wu, Yue Xue et al. |
| 4 | 205 | [A Large-Scale Survey on the Usability of AI Programming Assistants: Successes and Challenges](https://doi.org/10.1145/3597503.3608128) | 2024-02-06 | Jenny T. Liang, Chenyang Yang, Brad A. Myers |
| 5 | 181 | [Prompting Is All You Need: Automated Android Bug Replay with Large Language Models](https://doi.org/10.1145/3597503.3608137) | 2024-02-06 | Sidong Feng, Chunyang Chen |
| 6 | 172 | [Evaluating Large Language Models in Class-Level Code Generation](https://doi.org/10.1145/3597503.3639219) | 2024-04-12 | Xueying Du, Mingwei Liu, Kaixin Wang et al. |
| 7 | 163 | [Large Language Models are Few-Shot Summarizers: Multi-Intent Comment Generation via In-Context Learning](https://doi.org/10.1145/3597503.3608134) | 2024-02-06 | Mingyang Geng, Shangwen Wang, Dezun Dong et al. |
| 8 | 157 | [RepairAgent: An Autonomous, LLM-Based Agent for Program Repair](https://doi.org/10.1109/icse55347.2025.00157) | 2025-04-26 | Islem Bouzenia, Prémkumar Dévanbu, Michael Pradel |
| 9 | 144 | [Large Language Models for Test-Free Fault Localization](https://doi.org/10.1145/3597503.3623342) | 2024-02-06 | Aidan Z. H. Yang, Claire Le Goues, Ruben Martins et al. |
| 10 | 140 | [CoderEval: A Benchmark of Pragmatic Code Generation with Generative Pre-trained Models](https://doi.org/10.1145/3597503.3623316) | 2024-02-06 | Hao Yu, Bo Shen, Dezhi Ran et al. |

## Cite this page

Scholar4AI. (2026). ICSE: International Conference on Software Engineering — papers and institutions, 2024–2026. Journal and Conference Research Rankings. Retrieved November 2, 2026, from https://scholar4ai.com/proceedings/icse

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