Machine Learning for Software User Interface Testing
Tracing functional and non-functional requirements within user interface test cases
Beschreibung
In this project, various technical aspects for tracing functional/non-functional requirements within user interface test cases were investigated. Originally, this project aimed to detect bugs in user interfaces automatically by using machine learning algorithms. During the execution of the project, we decided to replace the machine learning algorithms by other Artificial Intelligence technique that proved to be more successful: an automatic reasoner based on ontologies. Such automatic reasoner allows testers for detecting inconsistencies—that could lead to bugs—between functional/non-functional requirements and user interfaces test cases generated by LogicFlow AG platform.
Eckdaten
Projektleitung
Dr. Lukas Fievet, Jose David Mosquera Tobón
Co-Projektleitung
Projektpartner
LogicFlow AG
Projektstatus
abgeschlossen, 09/2021 - 06/2022
Institut/Zentrum
Institut für Informatik (InIT)
Drittmittelgeber
Innovationsscheck / Projekt Nr. 54089.1 INNO-ICT