collaborators

7 papers

cs.SE2026

Semantic Drift in Bug Resolution: How Behavioral Signals Propagate from Reports to Tests and Patches

Wendkûuni C. Ouédraogo, Wendkûuni C. Ouédraogo, Yinghua Li +10

Desc2Fix is a framework for measuring semantic alignment between bug reports, triggering tests, and developer-written fixes. Alignment is operationalized through structured behavio…

cs.SE2026

Humanizing Automatically Generated Unit Test Suites with LLM-Based Refactoring

Wendkûuni C. Ouédraogo, Yinghua Li, Xueqi Dang +7

Search-based test generation tools such as EvoSuite produce compilable and high-coverage unit tests at scale, but their suites are often hard to read and maintain. LLMs can generat…

cs.SE2026

Large-scale, Independent and Comprehensive study of the power of LLMs for test case generation

Wendkûuni C. Ouédraogo, Kader Kaboré, Yinghua Li +5

Unit testing is essential for software reliability, yet manual test creation is time-consuming and often neglected. Search-based software testing improves efficiency but produces t…

cs.SE2025

On the Diffusion of Test Smells in LLM-Generated Unit Tests

Wendkûuni C. Ouédraogo, Yinghua Li, Xueqi Dang +5

LLMs promise to transform unit test generation from a manual burden into an automated solution. Yet, beyond metrics such as compilability or coverage, little is known about the qua…

cs.SE2025

Human-Aligned Code Readability Assessment with Large Language Models

Wendkûuni C. Ouédraogo, Yinghua Li, Xueqi Dang +6

Code readability is crucial for software comprehension and maintenance, yet difficult to assess at scale. Traditional static metrics often fail to capture the subjective, context-s…

cs.SE2025

Beyond Surface Similarity: Evaluating LLM-Based Test Refactorings with Structural and Semantic Awareness

Wendkûuni C. Ouédraogo, Yinghua Li, Xueqi Dang +5

Large Language Models (LLMs) are increasingly used to refactor unit tests, improving readability and structure while preserving behavior. Evaluating such refactorings, however, rem…