Research from UNamur Makes Artificial Intelligence Tools More Reliable

Before artificial intelligence can recognize an image, understand a text, or answer a question, it must first be trained. To do this, developers and data scientists use specialized software libraries—true “toolboxes” that enable the construction of these AI models.

A research team comprising the University of Namur, the University of Passau (Germany), and TU Delft (Netherlands) has been studying this software. Their goal: to detect bugs that are particularly difficult to spot and that could cause a program to crash suddenly.

To verify that these libraries are functioning properly, researchers use software capable of automatically generating thousands of tests. The purpose of these tests is to push the programs to their limits in order to identify any potential errors. 

Until now, however, these tools had a major limitation: whenever a test caused a software library to malfunction, the software responsible for running the tests would also stop working. This made it impossible to pinpoint the exact source of the problem or report it to the developers. 

Researchers at UNamur have therefore devised a new method. Now, each test is run separately. If one of them causes a crash, it is isolated: the testing software continues to run, logs the error, and carries on with its analysis. This makes it possible to automatically detect bugs that previously went unnoticed. 

Using this new method, researchers analyzed 1,648 modules from the leading machine learning libraries and uncovered 32 previously unknown bugs. Several of these affected software that has become indispensable for training artificial intelligence models.

These issues were reported to the development teams. Several have already been acknowledged and fixed. “When a bug is fixed at this level, potentially thousands, or even millions, of users benefit,” notes Xavier Devroey, a professor in the Faculty of Computer Science at UNamur and a member of the PReCISE research center at the Namur Digital Institute (NaDI). Beyond these fixes, this research helps make the software on which so many artificial intelligence applications rely today more reliable.

This breakthrough originated from Lucas Berg’s master’s thesis, completed at UNamur under the supervision of Professor Xavier Devroey. As part of his research internship, Lucas Berg then joined Professor Annibale Panichella’s team at TU Delft to work on Pynguin, the open-source automated test generation tool developed at the University of Passau by Professor Gordon Fraser’s team, mentioned earlier. 

Initially, his goal was to improve this tool. By preventing crashes while discovering bugs, this first contribution subsequently caught the attention of researchers at the University of Passau, who were facing the same problem, leading to an international collaboration that would result in a joint scientific publication. 

Lucas Berg is currently pursuing a Ph.D. at the Faculty of Computer Science at UNamur under the supervision of Professors Wim Vanhoof and Xavier Devroey. The results of this research were presented at the IEEE International Conference on Software Testing, Verification, and Validation (ICST 2026), one of the most prestigious international conferences in the field of software testing.  

This research also received support from the Wallonia Public Service (SPW Research) and Wallonia-Brussels International. This recognition underscores the quality of this work and its significance to the international scientific community. 

At NaDI, researchers develop innovative solutions to the new societal challenges posed by the digital revolution (eGov, eHealth, eServices, big data, etc.). Drawing from a variety of disciplines, the researchers combine their expertise in computer science, technology, ethics, law, management, and sociology. Comprising six research centers, the Namur Digital Institute offers unique multidisciplinary expertise in all areas of computer science, its applications, and its social impact.