Trustworthy and Responsible AI-Centric Test Engineering
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Software testing is, in general, a notoriously expensive and effort-intensive process. The integration of artificial intelligence (AI) and machine learning (ML) into the software testing and analysis processes offers a transformative approach to optimizing test case design, selection, execution, and maintenance.
AI and ML can be used to automate or support activities throughout the testing process, including the creation of new test cases, extension or maintenance of existing test cases, detection and re-creation of anomalies, analysis of system logs, suggestions on how to improve test suite quality, and prioritization of tests to execute in CI/CD pipelines.
The goal of this project is to explore, investigate, implement, and evaluate a trustworthy, human-centric AI-driven testing process. Our vision is that such a process:
Uses AI and ML to augment, rather than replace, developers.
Enables developers to make effective, data-driven decisions during testing.
Offers trustworthy, repeatable, and explainable results.
| First Name | Last Name | Title |
|---|---|---|
| Eduard Paul | Enoiu | Associate Professor |
| Jean | Malm | Doctoral student |
| Alexandru | Cusmaru | |
| Gregory | Gay |
Ethical Challenges and Software Test Automation (Aug 2025) Per Erik Strandberg, Eduard Paul Enoiu, Mirgita Frasheri AI and Ethics ( AI and Ethics)
An Essay on the Role of Folklore in Software Engineering (Jun 2025) Eduard Paul Enoiu Software Center Reporting Workshop 2025 (SCRW25)
| Partner | Type |
|---|---|
| Chalmers University of Technology | Academic |
| University of Gothenburg | Academic |
| Siemens AB | Industrial |
