7 citations · 19 across the 11 of their papers we have counts for
4 papers · 1 filter
Clarifying Semantics of In-Context Examples for Unit Test Generation
Chen Yang, Lin Yang, Ziqi Wang +3
Recent advances in large language models (LLMs) have enabled promising performance in unit test generation through in-context learning (ICL). However, the quality of in-context exa…
Reflective Unit Test Generation for Precise Type Error Detection with Large Language Models
Chen Yang, Ziqi Wang, Yanjie Jiang +4
Type errors in Python often lead to runtime failures, posing significant challenges to software reliability and developer productivity. Existing static analysis tools aim to detect…
Improving Retrieval-Augmented Deep Assertion Generation via Joint Training
Quanjun Zhang, Chunrong Fang, Yi Zheng +7
Unit testing attempts to validate the correctness of basic units of the software system under test and has a crucial role in software development and testing. Very recent work prop…
Improving Deep Assertion Generation via Fine-Tuning Retrieval-Augmented Pre-trained Language Models
Quanjun Zhang, Chunrong Fang, Yi Zheng +7
Unit testing validates the correctness of the units of the software system under test and serves as the cornerstone in improving software quality and reliability. To reduce manual…