A robust class of data languages and an application to learning

Benedikt Bollig*, Peter Habermehl, Martin Leucker, Benjamin Monmege

*Korrespondierende/r Autor/-in für diese Arbeit
3 Zitate (Scopus)


We introduce session automata, an automata model to process data words, i.e., words over an infinite alphabet. Session automata support the notion of fresh data values, which are well suited for modeling protocols in which sessions using fresh values are of major interest, like in security protocols or ad-hoc networks. Session automata have an expressiveness partly extending, partly reducing that of classical register automata. We show that, unlike register automata and their various extensions, session automata are robust: They (i) are closed under intersection, union, and (resource-sensitive) complementation, (ii) admit a symbolic regular representation, (iii) have a decidable inclusion problem (unlike register automata), and (iv) enjoy logical characterizations. Using these results, we establish a learning algorithm to infer session automata through membership and equivalence queries.

ZeitschriftLogical Methods in Computer Science
Seiten (von - bis)1-23
PublikationsstatusVeröffentlicht - 29.12.2014


Untersuchen Sie die Forschungsthemen von „A robust class of data languages and an application to learning“. Zusammen bilden sie einen einzigartigen Fingerprint.