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Wellnested context unification
 In CADE 2005, LNCS 3632
"... Abstract. Context unification (CU) is the open problem of solving context equations for trees. We distinguish a new decidable variant of CU– wellnested CU – and present a new unification algorithm that solves wellnested context equations in nondeterministic polynomial time. We show that minimal w ..."
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Cited by 16 (9 self)
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Abstract. Context unification (CU) is the open problem of solving context equations for trees. We distinguish a new decidable variant of CU– wellnested CU – and present a new unification algorithm that solves wellnested context equations in nondeterministic polynomial time. We show that minimal wellnested solutions of context equations can be composed from the material present in the equation (see Theorem 1). This property is wishful when modeling natural language ellipsis in CU. 1
Monadic secondorder unification is NPcomplete
 In RTA’04, volume 3091 of LNCS
, 2004
"... Abstract. Bounded SecondOrder Unification is the problem of deciding, for a given secondorder equation t? = u and a positive integer m, whether there exists a unifier σ such that, for every secondorder variable F, the terms instantiated for F have at most m occurrences of every bound variable. I ..."
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Cited by 12 (7 self)
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Abstract. Bounded SecondOrder Unification is the problem of deciding, for a given secondorder equation t? = u and a positive integer m, whether there exists a unifier σ such that, for every secondorder variable F, the terms instantiated for F have at most m occurrences of every bound variable. It is already known that Bounded SecondOrder Unification is decidable and NPhard, whereas general SecondOrder Unification is undecidable. We prove that Bounded SecondOrder Unification is NPcomplete, provided that m is given in unary encoding, by proving that a sizeminimal solution can be represented in polynomial space, and then applying a generalization of Plandowski’s polynomial algorithm that compares compacted terms in polynomial time. 1
Context matching for compressed terms
 In LICS 2008
, 2008
"... This paper is an investigation of the matching problem for term equations s = t where s contains context variables, and both terms s and t are given using some kind of compressed representation. In this setting, term representation with dags, but also with the more general formalism of singleton t ..."
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Cited by 12 (8 self)
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This paper is an investigation of the matching problem for term equations s = t where s contains context variables, and both terms s and t are given using some kind of compressed representation. In this setting, term representation with dags, but also with the more general formalism of singleton tree grammars, are considered. The main result is a polynomial time algorithm for context matching with dags, when the number of different context variables is fixed for the problem. NPcompleteness is obtained when the terms are represented using singleton tree grammars. The special cases of firstorder matching and also unification with STGs are shown to be decidable in PTIME. 1
Stratified context unification is npcomplete
 In Proc. of the 3rd International Joint Conference on Automated Reasoning, IJCAR’06
, 2006
"... Abstract. Context Unification is the problem to decide for a given set of secondorder equations E where all secondorder variables are unary, whether there exists a unifier, such that for every secondorder variable X, theabstractionλx.r instantiated for X has exactly one occurrence of the bound va ..."
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Cited by 11 (3 self)
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Abstract. Context Unification is the problem to decide for a given set of secondorder equations E where all secondorder variables are unary, whether there exists a unifier, such that for every secondorder variable X, theabstractionλx.r instantiated for X has exactly one occurrence of the bound variable x in r. Stratified Context Unification is a specialization where the nesting of secondorder variables in E is restricted. It is already known that Stratified Context Unification is decidable, NPhard, and in PSPACE, whereas the decidability and the complexity of Context Unification is unknown. We prove that Stratified Context Unification is in NP by proving that a sizeminimal solution can be represented in a singleton tree grammar of polynomial size, and then applying a generalization of Plandowski’s polynomial algorithm that compares compacted terms in polynomial time. This also demonstrates the high potential of singleton tree grammars for optimizing programs maintaining large terms. A corollary of our result is that solvability of rewrite constraints is NPcomplete. 1
THE COMPLEXITY OF MONADIC SECONDORDER UNIFICATION ∗
, 1113
"... Abstract. Monadic secondorder unification is secondorder unification where all function constants occurring in the equations are unary. Here we prove that the problem of deciding whether a set of monadic equations has a unifier is NPcomplete, where we use the technique of compressing solutions us ..."
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Cited by 5 (2 self)
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Abstract. Monadic secondorder unification is secondorder unification where all function constants occurring in the equations are unary. Here we prove that the problem of deciding whether a set of monadic equations has a unifier is NPcomplete, where we use the technique of compressing solutions using singleton contextfree grammars. We prove that monadic secondorder matching is also NPcomplete.
Normalization of sequential topdown treetoword transducers
 In Language and Automata Theory and Applications (LATA), LNCS
, 2011
"... Abstract. We study normalization of deterministic sequential topdown treetoword transducers (stws), that capture the class of deterministic topdown nestedword to word transducers. We identify the subclass of earliest stws (estws) that yield normal forms when minimized. The main result of this p ..."
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Cited by 3 (1 self)
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Abstract. We study normalization of deterministic sequential topdown treetoword transducers (stws), that capture the class of deterministic topdown nestedword to word transducers. We identify the subclass of earliest stws (estws) that yield normal forms when minimized. The main result of this paper is an effective normalization procedure for stws. It consists of two stages: we first convert a given stw to an equivalent estw, and then, we minimize the estw. 1
Fast Equality Test for StraightLine Compressed Strings
, 2011
"... The paper describes a simple and fast randomized test for equality of grammarcompressed strings. The thorough running time analysis is done by applying a logarithmic cost measure. ..."
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Cited by 1 (0 self)
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The paper describes a simple and fast randomized test for equality of grammarcompressed strings. The thorough running time analysis is done by applying a logarithmic cost measure.
WellNested Context Unification. Proc. of the 20th Int. Conf. on Automated Deduction (CADE20). WellNested Context Unification ⋆
"... Abstract. Context unification (CU) is the open problem of solving context equations for trees. We distinguish a new decidable variant of CU – wellnested CU – and present a new unification algorithm that solves wellnested context equations in nondeterministic polynomial time. We show that minimal ..."
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Abstract. Context unification (CU) is the open problem of solving context equations for trees. We distinguish a new decidable variant of CU – wellnested CU – and present a new unification algorithm that solves wellnested context equations in nondeterministic polynomial time. We show that minimal wellnested solutions of context equations can be composed from the material present in the equation (see Theorem 1). This property is wishful when modeling natural language ellipsis in CU. 1