From the 1 of 11 linked papers with an AI index.
11 papers
Have I Seen You? Embedding Behavior Signals Synthetic Face Dataset Membership
PaweŠBorsukiewicz, Daniele Lunghi, Wendkûuni C. Ouédraogo +2
Synthetic face datasets are increasingly used to reduce privacy exposure and data access constraints in biometric recognition. Yet the generators that produce these datasets are tr…
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…
Benchmarking Face Recognition without Real Faces
PaweŠBorsukiewicz, Daniele Lunghi, Wendkûuni C. Ouédraogo +2
The paper evaluates whether synthetic face datasets can replace real‑face benchmarks for assessing face recognition models, finding that the best synthetic sets achieve comparable…
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…
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…
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…