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2008
Springer

Regular Inference for State Machines Using Domains with Equality Tests

9 years 29 days ago
Regular Inference for State Machines Using Domains with Equality Tests
Abstract. Existing algorithms for regular inference (aka automata learning) allows to infer a finite state machine by observing the output that the machine produces in response to a selected sequence of input strings. We generalize regular inference techniques to infer a class of state machines with an infinite state space. We consider Mealy machines extended with state variables that can assume values from a potentially unbounded domain. These values can be passed as parameters in input and output symbols, and can be used in tests for equality between state variables and/or message parameters. This is to our knowledge the first extension of regular inference to infinite-state systems. We intend to use these techniques to generate models of communication protocols from observations of their input-output behavior. Such protocols often have parameters that represent node adresses, connection identifiers, etc. that have a large domain, and on which test for equality is the only meaningful...
Therese Berg, Bengt Jonsson, Harald Raffelt
Added 19 Oct 2010
Updated 19 Oct 2010
Type Conference
Year 2008
Where FASE
Authors Therese Berg, Bengt Jonsson, Harald Raffelt
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