The University of Glasgow uses cookies for analytics. Find out more about our Privacy policy.
Necessary cookies enable core functionality. The website cannot function properly without these cookies, and can only be disabled by changing your browser preferences.
Analytical cookies help us improve our website. We use Google Analytics. All data is anonymised.
Clarity helps us to understand our users’ behaviour by visually representing their clicks, taps and scrolling. All data is anonymised.
Research title: |Topic: Automated Unit Test Generation using LLMs| Our research would be focused on generating unit test cases using large language models (LLMs). We first plan to generate unit test cases from a given natural language description or code snippet by
Das, S., Ghosh, M., Swami, P., Ganguly, D. and Calikli, G. (2025) In-Context Learning as an Effective Estimator of Functional Correctness of LLM-Generated Code. In: 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2025), Padua, Italy, 13-17 July 2025, (Accepted for Publication)
Das, S., Ghosh, M., Swami, P., Ganguly, D. and Calikli, G. (2025) In-Context Learning as an Effective Estimator of Functional Correctness of LLM-Generated Code. In: 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2025), Padua, Italy, 13-17 July 2025, (Accepted for Publication)