1 citations · 1 across the 4 of their papers we have counts for
4 papers
LLM-based Low-Level Integration Test Generation for Java
Qinghua Xu, Guancheng Wang, Lionel Briand +2
Large language models (LLMs) show promise for automated test generation, but most approaches target unit tests with mocked dependencies. Low-level integration testing instead exerc…
Call-Chain-Aware LLM-Based Test Generation for Java Projects
Guancheng Wang, Qinghua Xu, Lionel C. Briand +2
Large language models (LLMs) have recently shown strong potential for generating project-level unit tests. However, existing state-of-the-art approaches primarily rely on execution…
Large Language Models for Unit Test Generation: Achievements, Challenges, and Opportunities
Bei Chu, Yang Feng, Kui Liu +5
Unit tests help detect faults and prevent regressions, but writing them manually is costly. Automated unit test generation involves constructing inputs that exercise the code and o…
PALM: Synergizing Program Analysis and LLMs to Enhance Rust Unit Test Coverage
Bei Chu, Yang Feng, Kui Liu +4
Unit testing is essential for ensuring software reliability and correctness. Classic Search-Based Software Testing (SBST) methods and concolic execution-based approaches for genera…