Skip to Main content Skip to Navigation
Conference papers

Inferring Mealy Machines

Abstract : Automata learning techniques are getting significant importance for their applications in a wide variety of software engineering problems, especially in the analysis and testing of complex systems. In recent studies, a previous learning approach [1] has been extended to synthesize Mealy machine models which are specifically tailored for I/O based systems. In this paper, we discuss the inference of Mealy machines and propose improvements that reduces the worst-time learning complexity of the existing algorithm. The gain over the complexity of the proposed algorithm has also been confirmed by experimentation on a large set of finite state machines.
Document type :
Conference papers
Complete list of metadata

https://hal.inria.fr/hal-00953587
Contributor : Catherine Oriat <>
Submitted on : Friday, February 28, 2014 - 1:54:23 PM
Last modification on : Tuesday, December 8, 2020 - 10:18:09 AM

Links full text

Identifiers

Collections

Citation

Muzammil Shahbaz, Roland Groz. Inferring Mealy Machines. Formal Methods 2009, 2009, Eindhoven, Netherland, pp.207-222, ⟨10.1007/978-3-642-05089-3_14⟩. ⟨hal-00953587⟩

Share

Metrics

Record views

552