--- title: "ESEM (A): papers and universities" description: "ESEM (International Symposium on Empirical Software Engineering and Measurement) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 134 of its papers from 2024–2026 (66 in 2024, 68 in 2025; 2026 not in OpenAlex yet). By the countries of the authors' institutions, the most papers come from the United States (29), Canada (21) and Italy (18)." url: https://scholar4ai.com/proceedings/esem markdown_url: https://scholar4ai.com/proceedings/esem.md license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/) share_text: "ESEM (International Symposium on Empirical Software Engineering and Measurement) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 134 of its papers from 2024–2026 (66 in 2024, 68 in 2025; 2026 not… (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) --- # ESEM: International Symposium on Empirical Software Engineering and Measurement — papers and institutions, 2024–2026 Papers of ESEM, International Symposium on Empirical Software Engineering and Measurement (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 - ESEM (International Symposium on Empirical Software Engineering and Measurement) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 134 of its papers from 2024–2026 (66 in 2024, 68 in 2025; 2026 not in OpenAlex yet). - By the countries of the authors' institutions, the most papers come from the United States (29), Canada (21) and Italy (18). - The institutions with the most papers are Blekinge Institute of Technology (7), University of Salerno (6) and University of L'Aquila (6). - Its most-cited paper of these years is “Evaluating Large Language Models in Exercises of UML Class Diagram Modeling” (2024), with 43 citations. ## Papers per year *ESEM papers per publication year in OpenAlex (–: not in OpenAlex yet)* | Year | Papers | With affiliations | |---|---:|---:| | 2024 | 66 | 66 | | 2025 | 68 | 58 | | 2026 | – | – | ## Sources *Where OpenAlex lists the papers* | OpenAlex source | Which papers | |---|---| | [S4210197744](https://openalex.org/S4210197744) | The conference's proceedings | ## Who publishes there *Institutions with the most ESEM papers, 2024–2026* | # | Institution | Papers | |---:|---|---:| | 1 | Blekinge Institute of Technology | 7 | | 2 | University of Salerno | 6 | | 3 | University of L'Aquila | 6 | | 4 | Universidade Tecnológica Federal do Paraná | 4 | | 5 | Northern Arizona University | 4 | | 6 | University College London | 4 | | 7 | University of Bari Aldo Moro | 4 | | 8 | Colorado State University | 4 | | 9 | University of Oulu | 4 | | 10 | Dalhousie University | 3 | *Countries with the most ESEM papers, 2024–2026* | # | Country | Papers | |---:|---|---:| | 1 | United States | 29 | | 2 | Canada | 21 | | 3 | Italy | 18 | | 4 | Brazil | 15 | | 5 | Sweden | 12 | | 6 | China | 11 | | 7 | United Kingdom | 10 | | 8 | Germany | 9 | | 9 | Finland | 8 | | 10 | Spain | 7 | *Keywords with the most ESEM papers, 2024–2026* | # | Keyword | Papers | |---:|---|---:| | 1 | [large language models](https://scholar4ai.com/keywords/large-language-models.md) | 31 | | 2 | open source software | 12 | | 3 | ChatGPT | 9 | | 4 | software maintainability | 7 | | 5 | Java | 6 | | 6 | algorithmic fairness | 6 | | 7 | systematic reviews | 6 | | 8 | Stack Overflow | 5 | | 9 | prompt engineering | 5 | | 10 | software quality | 5 | ## Most-cited papers *Most-cited ESEM papers of 2024–2026 (citations counted by OpenAlex)* | # | Citations | Title | Published | Authors | |---:|---:|---|---|---| | 1 | 43 | [Evaluating Large Language Models in Exercises of UML Class Diagram Modeling](https://doi.org/10.1145/3674805.3690741) | 2024-10-15 | Daniele De Bari, Giacomo Garaccione, Riccardo Coppola et al. | | 2 | 35 | [An Exploratory Mixed-methods Study on General Data Protection Regulation (GDPR) Compliance in Open-Source Software](https://doi.org/10.1145/3674805.3686692) | 2024-10-15 | Lucas Franke, Huayu Liang, Sahar Farzanehpour et al. | | 3 | 28 | [ChatGPT application in Systematic Literature Reviews in Software Engineering: an evaluation of its accuracy to support the selection activity](https://doi.org/10.1145/3674805.3686666) | 2024-10-15 | Katia Romero Felizardo, Marcia Heloísa Tavares de Figueredo Lima, Anderson Deizepe et al. | | 4 | 25 | [Detecting Code Smells using ChatGPT: Initial Insights](https://doi.org/10.1145/3674805.3690742) | 2024-10-15 | Luciana Lourdes Silva, Janio Rosa da Silva, João Eduardo Montandon et al. | | 5 | 23 | [What do we know about Hugging Face? A systematic literature review and quantitative validation of qualitative claims](https://doi.org/10.1145/3674805.3686665) | 2024-10-15 | Jason Jones, Wenxin Jiang, Nicholas M. Synovic et al. | | 6 | 20 | [Beyond Words: On Large Language Models Actionability in Mission-Critical Risk Analysis](https://doi.org/10.1145/3674805.3695401) | 2024-10-15 | Matteo Esposito, Francesco Palagiano, Valentina Lenarduzzi et al. | | 7 | 19 | [Documenting Ethical Considerations in Open Source AI Models](https://doi.org/10.1145/3674805.3686679) | 2024-10-15 | Haoyu Gao, Mansooreh Zahedi, Christoph Treude et al. | | 8 | 18 | [Automatic Library Migration Using Large Language Models: First Results](https://doi.org/10.1145/3674805.3690746) | 2024-10-15 | Aylton Almeida, Laerte Xavier, Marco Túlio Valente | | 9 | 15 | [Threats to Validity in Software Engineering – hypocritical paper section or essential analysis?](https://doi.org/10.1145/3674805.3686691) | 2024-10-15 | Patricia Lago, Per Runeson, Qunying Song et al. | | 10 | 13 | [DetectBERT: Towards Full App-Level Representation Learning to Detect Android Malware](https://doi.org/10.1145/3674805.3690745) | 2024-10-15 | Tiezhu Sun, Nadia Daoudi, Kisub Kim et al. | ## Cite this page Scholar4AI. (2026). ESEM: International Symposium on Empirical Software Engineering and Measurement — papers and institutions, 2024–2026. Journal and Conference Research Rankings. Retrieved November 2, 2026, from https://scholar4ai.com/proceedings/esem ```bibtex @misc{scholar4ai-proceedings-esem, author = {{Scholar4AI}}, title = {ESEM: International Symposium on Empirical Software Engineering and Measurement — papers and institutions, 2024–2026}, year = {2026}, howpublished = {\url{https://scholar4ai.com/proceedings/esem}}, 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/).