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dc.contributor.authorLin, SW
dc.contributor.authorAndré, E
dc.contributor.authorDong, JS
dc.contributor.authorSun, J
dc.contributor.authorLiu, Y
dc.description.abstractIn inference of untimed regular languages, given an unknown language to be inferred, an automaton is constructed to accept the unknown language from answers to a set of membership queries each of which asks whether a string is contained in the unknown language. One of the most well-known regular inference algorithms is the L* algorithm, proposed by Angluin in 1987, which can learn a minimal deterministic finite automaton (DFA) to accept the unknown language. In this work, we propose an efficient polynomial time learning algorithm, TL*, for timed regular language accepted by event-recording automata. Given an unknown timed regular language, TL* first learns a DFA accepting the untimed version of the timed language, and then passively refines the DFA by adding time constraints. We prove the correctness, termination, and minimality of the proposed TL* algorithm.
dc.relation.ispartofjournalLecture Notes in Computer Science
dc.relation.ispartofvolume6996 LNCS
dc.subject.fieldofresearchSoftware engineering not elsewhere classified
dc.titleAn efficient algorithm for learning event-recording automata
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.hasfulltextNo Full Text
gro.griffith.authorDong, Jin-Song

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