22 citations · 57 across the 17 of their papers we have counts for
17 papers
A Detailed Account of Compositional Automata Learning through Alphabet Refinement
Leo Henry, Thomas Neele, Mohammad Reza Mousavi +1
Active automata learning infers automaton models of systems from behavioral observations, a technique successfully applied to a wide range of domains. Compositional approaches have…
ALARM: Active LeArning of Rowhammer Mitigations
Amir Naseredini, Martin Berger, Matteo Sammartino +1
Rowhammer is a serious security problem of contemporary dynamic random-access memory (DRAM) where reads or writes of bits can flip other bits. DRAM manufacturers add mitigations, b…
Guarded Kleene Algebra with Tests: Automata Learning
Stefan Zetzsche, Alexandra Silva, Matteo Sammartino
Guarded Kleene Algebra with Tests (GKAT) is the fragment of Kleene Algebra with Tests (KAT) that arises by replacing the union and iteration operations of KAT with predicate-guarde…
Canonical Automata via Distributive Law Homomorphisms
Stefan Zetzsche, Gerco van Heerdt, Matteo Sammartino +1
The classical powerset construction is a standard method converting a non-deterministic automaton into a deterministic one recognising the same language. Recently, the powerset con…
Generators and Bases for Monadic Closures
Stefan Zetzsche, Alexandra Silva, Matteo Sammartino
It is well-known that every regular language admits a unique minimal deterministic acceptor. Establishing an analogous result for non-deterministic acceptors is significantly more…
Actor-Based Model Checking for SDN Networks
Elvira Albert, Miguel Gómez-Zamalloa, Miguel Isabel +3
Software-Defined Networking (SDN) is a networking paradigm that has become increasingly popular in the last decade. The unprecedented control over the global behavior of the networ…
A Categorical Framework for Learning Generalised Tree Automata
Gerco van Heerdt, Tobias Kappé, Jurriaan Rot +2
Automata learning is a popular technique used to automatically construct an automaton model from queries. Much research went into devising ad hoc adaptations of algorithms for diff…
Residuality and Learning for Nondeterministic Nominal Automata
Joshua Moerman, Matteo Sammartino
We are motivated by the following question: which data languages admit an active learning algorithm? This question was left open in previous work by the authors, and is particularl…
A (co)algebraic theory of succinct automata
Gerco van Heerdt, Joshua Moerman, Matteo Sammartino +1
The classical subset construction for non-deterministic automata can be generalized to other side-effects captured by a monad. The key insight is that both the state space of the d…
Tree Automata as Algebras: Minimisation and Determinisation
Gerco van Heerdt, Tobias Kappé, Jurriaan Rot +2
We study a categorical generalisation of tree automata, as -algebras for a fixed endofunctor endowed with initial and final states. Under mild assumptions about the base cat…
Symbolic Register Automata
Loris D'Antoni, Tiago Ferreira, Matteo Sammartino +1
Symbolic Finite Automata and Register Automata are two orthogonal extensions of finite automata motivated by real-world problems where data may have unbounded domains. These automa…
Optimizing Automata Learning via Monads
Gerco van Heerdt, Matteo Sammartino, Alexandra Silva
Automata learning has been successfully applied in the verification of hardware and software. The size of the automaton model learned is a bottleneck for scalability, and hence opt…
CALF: Categorical Automata Learning Framework
Gerco van Heerdt, Matteo Sammartino, Alexandra Silva
Automata learning is a technique that has successfully been applied in verification, with the automaton type varying depending on the application domain. Adaptations of automata le…
Learning Nominal Automata
Joshua Moerman, Matteo Sammartino, Alexandra Silva +2
We present an Angluin-style algorithm to learn nominal automata, which are acceptors of languages over infinite (structured) alphabets. The abstract approach we take allows us to s…
A coalgebraic semantics for causality in Petri nets
Roberto Bruni, Ugo Montanari, Matteo Sammartino
In this paper we revisit some pioneering efforts to equip Petri nets with compact operational models for expressing causality. The models we propose have a bisimilarity relation an…
Dynamic Programming on Nominal Graphs
Nicklas Hoch, Ugo Montanari, Matteo Sammartino
Many optimization problems can be naturally represented as (hyper) graphs, where vertices correspond to variables and edges to tasks, whose cost depends on the values of the adjace…
A decidable class of (nominal) omega-regular languages over an infinite alphabet
Vincenzo Ciancia, Matteo Sammartino
We define a class of languages of infinite words over infinite alphabets, and the corresponding automata. The automata used for recognition are a generalisation of deterministic Mu…