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Inferring Canonical Register Automata [chapter]

Falk Howar, Bernhard Steffen, Bengt Jonsson, Sofia Cassel
2012 Lecture Notes in Computer Science  
The application of our algorithm to a small example indicates the impact of learning register automata models: Not only are the inferred models much more expressive than finite state machines, but the  ...  This effect is expressed by means of registers and guarded transitions in the resulting register automata models.  ...  This approach could probably be generalized to infer register automata.  ... 
doi:10.1007/978-3-642-27940-9_17 fatcat:x3hdyqw3jrbf5cqqzc2sznc6bm

A Fresh Approach to Learning Register Automata [chapter]

Benedikt Bollig, Peter Habermehl, Martin Leucker, Benjamin Monmege
2013 Lecture Notes in Computer Science  
and model-checking problem (unlike register automata).  ...  Using these results, we establish a learning algorithm to infer session automata through membership and equivalence queries.  ...  Introduction Learning automata deals with the inference of automata based on some partial information, for example samples, which are words that either belong to their accepted language or not.  ... 
doi:10.1007/978-3-642-38771-5_12 fatcat:2yrvahxsevepbdrr4twmois44m

A Robust Class of Data Languages and an Application to Learning

Benedikt Bollig, Peter Habermehl, Martin Leucker, Benjamin Monmege, Orna Kupferman
2014 Logical Methods in Computer Science  
Using these results, we establish a learning algorithm to infer session automata through membership and equivalence queries.  ...  Session automata have an expressiveness partly extending, partly reducing that of classical register automata.  ...  Canonical Session Automata.  ... 
doi:10.2168/lmcs-10(4:19)2014 fatcat:yva6qkttozfgli7mhtr2a6g3k4

Inferring Semantic Interfaces of Data Structures [chapter]

Falk Howar, Malte Isberner, Bernhard Steffen, Oliver Bauer, Bengt Jonsson
2012 Lecture Notes in Computer Science  
Algorithmic key to the automated synthesis of these semantic interfaces is the extension of an active learning algorithm for Register Automata to explicitly deal with output.  ...  Our semantic interfaces are a generalized form of Register Automata (RA), comprising parameterized input and output, allowing to model control-and data-flow in component interfaces concisely.  ...  Our algorithm is based on the one for inferring Register Automata as presented in [11] .  ... 
doi:10.1007/978-3-642-34026-0_41 fatcat:buktd6rbjvfghgv5ptxfwjtt5m

Learning register automata: from languages to program structures

Malte Isberner, Falk Howar, Bernhard Steffen
2013 Machine Learning  
This paper reviews the development of Register Automaton learning, an enhancement of active automata learning to deal with infinite-state systems.  ...  learning to also inferring optimal alphabet abstractions, and Register Mealy Machines, which can be regarded as programs restricted to data-independent data processing as it is typical for protocols or  ...  It allows us to relate data languages and register automata more easily than explicit disjunctions when constructing canonical automata for data languages. 7 Technically, the more adequate perspective  ... 
doi:10.1007/s10994-013-5419-7 fatcat:wz3atcp7vjcf7irzgejh45a2li

Active Automata Learning in Practice [chapter]

Falk Howar, Bernhard Steffen
2018 Lecture Notes in Computer Science  
Five years ago (in 2011) we have surveyed the then current state of active automata learning research and applications of active automata learning in practice.  ...  As systems become ever more complex and development becomes more distributed, inferred models of system behavior become an increasingly valuable asset for understanding and analyzing a system's behavior  ...  Aarts and co-authors develop a slightly different approach for inferring register automata models that can compare registers and data parameter for equality [3, 2] .  ... 
doi:10.1007/978-3-319-96562-8_5 fatcat:jtpzftrzvzf3tdtbncntfc4s4q

Active Automata Learning: From DFAs to Interface Programs and Beyond

Bernhard Steffen, Falk Howar, Malte Isberner
2012 Journal of machine learning research  
We are convinced that this development has the potential to transform active automata learning into a technology of high practical importance.  ...  not only states but also optimal alphabet abstractions, and Register Mealy Machines, which can be regarded as programs restricted to data-independent data processing as it is typical for protocols or  ...  Grinchtein et al. (2010) present a learning algorithm for a restricted class of timed automata, capable of inferring clock guards, and Howar et al. (2012b) extend active learning to register automata  ... 
dblp:journals/jmlr/SteffenHI12 fatcat:jpz7ckra5vg3bodir64t4isegy

A Succinct Canonical Register Automaton Model for Data Domains with Binary Relations [chapter]

Sofia Cassel, Bengt Jonsson, Falk Howar, Bernhard Steffen
2012 Lecture Notes in Computer Science  
The model is based on register automata.  ...  A major contribution is a construction of succinct canonical register automata, which is parameterized on the set of relations by which elements in the data domain can be compared.  ...  based criteria [14, 17] , and in automata learning (aka regular inference) [2, 9, 19] .  ... 
doi:10.1007/978-3-642-33386-6_6 fatcat:tqu6rvymfbh6jjpviubxxyxzkq

A Class of Automata for the Verification of Infinite, Resource-Allocating Behaviours [chapter]

Vincenzo Ciancia, Matteo Sammartino
2014 Lecture Notes in Computer Science  
In this paper we investigate nominal automata that accept infinite words. These automata are a generalisation of deterministic Muller automata to the setting of nominal sets.  ...  The key to obtain such results is to use finite representations of the (otherwise infinite-state) defined class of automata.  ...  The authors thank Nikos Tzevelekos, Emilio Tuosto and Gianluca Mezzetti for several fruitful discussions related to nominal automata.  ... 
doi:10.1007/978-3-662-45917-1_7 fatcat:ajl4loivava5dhkej22mrmpf4i

A decidable class of (nominal) omega-regular languages over an infinite alphabet [article]

Vincenzo Ciancia, Matteo Sammartino
2013 arXiv   pre-print
The automata used for recognition are a generalisation of deterministic Muller automata to the setting of nominal sets.  ...  We define a class of languages of infinite words over infinite alphabets, and the corresponding automata.  ...  The authors thank Nikos Tzevelekos, Emilio Tuosto and Gianluca Mezzetti for several fruitful discussions related to nominal automata.  ... 
arXiv:1310.3945v1 fatcat:64x454hhcjgyfnn7yuq6exdk74

A Finite Exact Representation of Register Automata Configurations

Yu-Fang Chen, Bow-Yaw Wang, Di-De Yen
2014 Electronic Proceedings in Theoretical Computer Science  
We moreover define a computation tree logic for register automata and solve its model checking problem.  ...  Using the finitary representation, we give an algorithm solving the reachability problem for register automata.  ...  A canonical representation theorem similar to Myhill-Nerode theorem for deterministic register automata is developed in [1] . In [2] , a learning algorithm for register automata is proposed.  ... 
doi:10.4204/eptcs.140.2 fatcat:aps6qfm3grch3hxjr64gnks6hi

Learning Extended Finite State Machines [chapter]

Sofia Cassel, Falk Howar, Bengt Jonsson, Bernhard Steffen
2014 Lecture Notes in Computer Science  
We present an active learning algorithm for inferring extended finite state machines (EFSM)s, combining data flow and control behavior.  ...  The learning algorithm uses the tree queries to infer symbolic data constraints on parameters, e.g., sequence numbers, time stamps, identifiers, or even simple arithmetic.  ...  Register automata are similar to the symbolic transducers of [26] .  ... 
doi:10.1007/978-3-319-10431-7_18 fatcat:y22ilav76baqdjdqn4bifs7zea

Extending Automata Learning to Extended Finite State Machines [chapter]

Sofia Cassel, Falk Howar, Bengt Jonsson, Bernhard Steffen
2018 Lecture Notes in Computer Science  
Automata learning is an established class of techniques for inferring automata models by observing how they respond to a sample of input words.  ...  Recently, approaches have been presented that extend these techniques to infer extended finite state machines (EFSMs) by dynamic black-box analysis.  ...  The challenge that faces AAL for register automata is to infer all the features of an RA, including locations, registers, guards, and assignments, using only membership queries and counterexamples returned  ... 
doi:10.1007/978-3-319-96562-8_6 fatcat:ao4ovlmamzgopde4r655zpohya

Learning-Based Testing the Sliding Window Behavior of TCP Implementations [chapter]

Paul Fiterău-Broştean, Falk Howar
2017 Lecture Notes in Computer Science  
We develop a learning-based testing framework for register automaton models that can express the windowing behavior of TCP, thereby presenting the first significant application of register automata learning  ...  to realistic software for a class of automata with Boolean-arithmetic constraints over data values.  ...  Our learning setup can infer more expressive register automata, and requires no form of abstraction other than a general one for handling fresh values. Outline.  ... 
doi:10.1007/978-3-319-67113-0_12 fatcat:7d2tcjdldjevfff3jrndeey4li

Grey-Box Learning of Register Automata [article]

Bharat Garhewal, Frits Vaandrager, Falk Howar, Timo Schrijvers, Toon Lenaerts, Rob Smits
2020 arXiv   pre-print
Existing model learning tools for infinite state systems face scalability problems and can only be applied to restricted classes of systems (register automata with equality/inequality).  ...  Model learning (a.k.a. active automata learning) is a highly effective technique for obtaining black-box finite state models of software components.  ...  So far, however, white-box techniques have never been integrated with learning algorithms for register automata.  ... 
arXiv:2009.09975v1 fatcat:awdvx2kotfgxvmrawf3kfeokka
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