LALGinar: Model-based testing for reactive systems. Intelligent approaches.

On Friday, May 9th, at 11:00 in LALG there was a presentation by Annamária Szenkovits, a guest PhD student at our lab. The talk is summarized below.

Model-based testing for reactive systems. Intelligent approaches.

Testing is a crucial step in the software development life-cycle. It is
common to dedicate at least 50% of the project resources to this step.
Model-based testing is a testing approach that can facilitate the
automatic test-case generation and thus testing costs can be significantly
The goal of this thesis is to address some of the fundamental problems of
automatic test-case generation in safety critical, reactive systems. The
research involved also focuses on the development and analysis of
intelligent methods for the optimization of the automatic test-case
generation process. Some of the main areas of interest are: statistical
testing, evolutionary testing and estimation of distribution algorithms
used in test-automation.
The practical part of the thesis aims to test the proposed methods and
algorithms on problems within the domain of railway automation.

The slides are available here.