We describe a largely automated and systematic analysis of TLS implementations by what
we call 'protocol state fuzzing': we use state machine learning to infer state machines from …

This paper reviews the development of Register Automaton learning, an enhancement of
active automata learning to deal with infinite-state systems. We will revisit the precursor …

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 apply model learning on three SSH implementations to infer state machine models, and
then use model checking to verify that these models satisfy basic security properties and …

SSL/TLS is the most commonly deployed family of protocols for securing network
communications. The security guarantees of SSL/TLS are critically dependent on the correct …

We describe a large collection of benchmarks, publicly available through the wiki automata.
cs. ru. nl, of different types of state machine models: DFAs, Moore machines, Mealy …

Links are established between three widely used modeling frameworks for reactive systems:
the ioco theory of Tretmans, the interface automata of De Alfaro and Henzinger, and Mealy …

Learning techniques allow the automatic inference of the behaviour of a system as a finite
state machine. We demonstrate that learning techniques can be used to extract such formal …

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 …

Active automata learning is a technique to automatically infer behavioral models of black-
box systems. Today's learning algorithms enable the deduction of models that describe …