In this paper, we present LearnLib, a library for active automata learning. The current, open-
source version of LearnLib was completely rewritten from scratch, incorporating the lessons …

We present a black-box active learning algorithm for inferring extended finite state machines
(EFSM) s by dynamic black-box analysis. EFSMs can be used to model both data flow and …

We present a survey of the recent research efforts in integrating model learning with model-
based testing. We distinguished two strands of work in this domain, namely test-based …

Software systems are present all around us and playing their vital roles in our daily life. The
correct functioning of these systems is of prime concern. In addition to classical testing …

The wealth of model-based techniques in software engineering—such as model checking or
model-based testing—is starkly contrasted with a frequent lack of formal models in practical …

The problem of learning automata from example traces (but no equivalence or membership
queries) is fundamental in automata learning theory and practice. In this paper, we study this …

We present a new algorithm for active learning of register automata. Our algorithm uses
counterexample-guided abstraction refinement to automatically construct a component …

Inferring models of program behavior from execution samples can provide useful information
about a system, also in the increasingly common case of systems that evolve and adapt in …

Active learning of register automata infers extended finite state machines (EFSMs) with
registers for storing values from a possibly infinite domain, and transition guards that …

A distributed protocol is typically modeled as a set of communicating processes, where each
process is described as an extended state machine along with fairness assumptions …