Empirical Software Engineering with LLMs and Machine Learning

Dear Colleagues,

We invite you to submit original contributions on empirical software engineering with large language models (LLMs) and machine learning (ML). Contributions targeting all aspects of the application, evaluation, and impact of LLMs and ML techniques at any phase of the information systems lifecycle are welcome.

We welcome empirical studies, experiments, case studies, benchmarks, replications, industrial experience reports, and meta-analyses based on results published earlier addressing topics such as the following:

• AI-assisted software development and code generation;
• Automated testing, debugging, and maintenance;
• Requirements engineering and software design with LLMs;
• Developer productivity and human–AI collaboration;
• Quality, reliability, security, and trustworthiness of AI-generated software;
• Evaluation methods, datasets, and benchmarks;
• Industrial adoption and real-world applications of LLMs in software engineering.

We hope that together we shall advance the understanding of how LLMs and ML are transforming software engineering based on empirical research results. We look forward to receiving your submissions.

Dr. Jakub Swacha
Dr. Łukasz Radliński
Guest Editors

Manuscript Submission Information

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