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20232026
most citedLarge-scale, Independent and Comprehensive study of the power of LLMs for test case generation

5 citations · 8 across the 10 of their papers we have counts for

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9 papers · 1 filter

cs.SE2026

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

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

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.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…

cs.SE2025

Rethinking Cognitive Complexity for Unit Tests: Toward a Readability-Aware Metric Grounded in Developer Perception

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

Automatically generated unit tests-from search-based tools like EvoSuite or LLMs-vary significantly in structure and readability. Yet most evaluations rely on metrics like Cyclomat…

cs.SE2024

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.SE2024★ 5 cited

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.SE2023★ 2 cited

Enriching Automatic Test Case Generation by Extracting Relevant Test Inputs from Bug Reports

Wendkûuni C. Ouédraogo, Laura Plein, Kader Kaboré +4

The quality of software is closely tied to the effectiveness of the tests it undergoes. Manual test writing, though crucial for bug detection, is time-consuming, which has driven s…

cs.SE2023★ 1 cited

Automatic Generation of Test Cases based on Bug Reports: a Feasibility Study with Large Language Models

Laura Plein, Wendkûuni C. Ouédraogo, Jacques Klein +1

Software testing is a core discipline in software engineering where a large array of research results has been produced, notably in the area of automatic test generation. Because e…