2011
DOI: 10.1145/1970398.1970403
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Two-variable logic on data words

Abstract: In a data word each position carries a label from a finite alphabet and a data value from some infinite domain. This model has been already considered in the realm of semistructured data, timed automata, and extended temporal logics. This article shows that satisfiability for the two-variable fragment FO 2 (∼,<,+1) of first-order logic with data equality test ∼ is decidable over finite and infinite data words. Here +1 and <… Show more

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Cited by 144 publications
(160 citation statements)
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“…Several specification mechanisms for data languages have been suggested, such as register automata [12], pebble automata [15], quasi-regular expressions [13], data automata [3], and LTL with a freeze quantifier [5]. For an overview, see [18].…”
Section: Introductionmentioning
confidence: 99%
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“…Several specification mechanisms for data languages have been suggested, such as register automata [12], pebble automata [15], quasi-regular expressions [13], data automata [3], and LTL with a freeze quantifier [5]. For an overview, see [18].…”
Section: Introductionmentioning
confidence: 99%
“…Due to the limited access to data values, they can be represented by an equivalence relation. First-order logic on data strings is undecidable, but the two-variable fragment has a decidable satisfiability problem [3]. In its decidability proof, the latter paper introduced a new automaton model for data strings, data automata (DAs).…”
Section: Introductionmentioning
confidence: 99%
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“…Recently, there has been a significant amount of work in this direction. See, for example, [3,4,6,9,13,15].…”
Section: Introductionmentioning
confidence: 99%
“…Later in [4] first-order logic for data languages was considered, and, in particular, the so-called data automata was introduced. It was shown that data automata define the fragment of existential monadic second-order logic for data languages in which the first-order part is restricted to two variables only.…”
Section: Introductionmentioning
confidence: 99%