Abstract Model learning has gained increasing interest in recent years. It derives
behavioural models from test data of black-box systems. The main advantage offered by …

Abstract Model-based testing is a promising technique for quality assurance. In practice,
however, a model is not always present. Hence, model learning techniques attain increasing …

We present a technique for learning explainable timed automata from passive observations
of a black-box function, such as an artificial intelligence system. Our method accepts a …

Linear Temporal Logic (LTL) Model Checking (MC) has been applied to many fields.
However, the state explosion problem and the exponentially computational complexity …

The construction of faithful system models for quantitative analysis, eg, performance
evaluation, is challenging due to the inherent systems' complexity and unknown operating …

Model learning has gained increasing interest in recent years. It derives behavioural models
from test data of black-box systems. The main advantage offered by such techniques is that …

In the present work, we tackle the problem of modeling and evaluating performance in the
context of embedded systems design. These have become essential for modern societies …

Learning techniques are being used increasingly to improve software verification and
validation activities. For example, automata learning techniques have been used for …

Intelligent cyber-physical systems, such as self-driving cars, smart homes or e-health
solutions, will increasingly influence our daily lives. They will deal with increasingly …

We present a technique for learning explainable timed automata from passive observations
of a black-box function, such as an artificial intelligence system. Our method accepts a …