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International Symposium on Empirical Software Engineering and Measurement

ESEM

A

CORE rank

CORE rank (raw)

A

Fields of research

Software Engineering

Papers indexed

1,062

2007–2025

Papers per year

200772 peak2025

ESEM papers

1,062 records sourced from DBLP. Search titles, filter by year, sort by recency.

YearTitleAuthors
2024Cross-Language Dependencies: An Empirical Study of Kotlin-Java.Qiong Feng, Huan Ji, Xiaotian Ma, Peng Liang
2024Data extraction for systematic mapping study using a large language model - a proof-of-concept study in software engineering.Ktia Romero Felizardo, Igor Steinmacher, Mrcia Sampaio Lima, Anderson Deizepe, Tayana Ucha Conte, Monalessa Perini Barcellos
2024ChatGPT application in Systematic Literature Reviews in Software Engineering: an evaluation of its accuracy to support the selection activity.Ktia Romero Felizardo, Mrcia Sampaio Lima, Anderson Deizepe, Tayana Ucha Conte, Igor Steinmacher
2024Beyond Words: On Large Language Models Actionability in Mission-Critical Risk Analysis.Matteo Esposito, Francesco Palagiano, Valentina Lenarduzzi, Davide Taibi
2024Contexts Matter: An Empirical Study on Contextual Influence in Fairness Testing for Deep Learning Systems.Chengwen Du, Tao Chen
2024Data Analysis Tools Affect Outcomes of Eye-Tracking Studies.Timon Drzapf, Norman Peitek, Marvin Wyrich, Sven Apel
2024PromptLink: Multi-template prompt learning with adversarial training for issue-commit link recovery.Yang Deng, Bangchao Wang, Zhiyuan Zou, Luyao Ye
2024Exploring LLM-Driven Explanations for Quantum Algorithms.Giordano d'Aloisio, Sophie Fortz, Carol Hanna, Daniel Fortunato, Avner Bensoussan, Eaut Mendiluze Usandizaga, Federica Sarro
2024Evaluating Software Modelling Recommendations: Towards Systematic Guidelines for Modelling.Shalini Chakraborty, Grischa Liebel
2024Are Large Language Models a Threat to Programming Platforms? An Exploratory Study.Md Mustakim Billah, Palash Ranjan Roy, Zadia Codabux, Banani Roy
2024Do Test and Environmental Complexity Increase Flakiness? An Empirical Study of SAP HANA.Alexander Berndt, Thomas Bach, Sebastian Baltes
2024Do Developers Use Static Application Security Testing (SAST) Tools Straight Out of the Box? A large-scale Empirical Study.Gareth Bennett, Tracy Hall, Steve Counsell, Emily Winter, Thomas Shippey
2024Evaluating Large Language Models in Exercises of UML Class Diagram Modeling.Daniele De Bari, Giacomo Garaccione, Riccardo Coppola, Marco Torchiano, Luca Ardito
2024Edge-AI Assurance in the REBECCA Project.Clara Ayora, Arturo S. Garca, Jose Luis de la Vara
2024A Comparative Study on Large Language Models for Log Parsing.Merve Astekin, Max Hort, Leon Moonen
2024Towards Automated Continuous Security Compliance.Florian Angermeir, Jannik Fischbach, Fabiola Moyn, Daniel Mndez
2024Automatic Library Migration Using Large Language Models: First Results.Aylton Almeida, Laerte Xavier, Marco Tlio Valente
2024Negative Results of Image Processing for Identifying Duplicate Questions on Stack Overflow.Faiz Ahmed, Suprakash Datta, Maleknaz Nayebi
2024Multi-language Software Development in the LLM Era: Insights from Practitioners' Conversations with ChatGPT.Lucas Aguiar, Matheus Paixo, Rafael Augusto Ferreira do Carmo, Edson Soares, Antonio Leal, Matheus Freitas, Eliakim Gama
2024A Transformer-based Approach for Augmenting Software Engineering Chatbots Datasets.Ahmad Abdellatif, Khaled Badran, Diego Elias Costa, Emad Shihab
2024An Investigation of How Software Developers Read Machine Learning Code.Thomas Weber, Christina Winiker, Sven Mayer
2024MOOD: Mindfulness fOr sOftware Developers.Simone Romano, Giuseppe Scanniello, Alessandro Marchetto, Paolo Giorgini, Gloria Guidetti, Daniela Converso, Sara Viotti
2024Automatic Categorization of GitHub Actions with Transformers and Few-shot Learning.Phuong T. Nguyen, Juri Di Rocco, Claudio Di Sipio, Mudita Shakya, Davide Di Ruscio, Massimiliano Di Penta
2024On the Accuracy of Effort Estimations based on COSMIC Functional Size Measurement: A Case Study.Ersin Ersoy, Selami Bagriyanik, Hasan Szer
2023An Empirical Study on Low- and High-Level Explanations of Deep Learning Misbehaviours.Tahereh Zohdinasab, Vincenzo Riccio, Paolo Tonella
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