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A Linear Logical Framework
, 1996
"... We present the linear type theory LLF as the forAppeared in the proceedings of the Eleventh Annual IEEE Symposium on Logic in Computer Science  LICS'96 (E. Clarke editor), pp. 264275, New Brunswick, NJ, July 2730 1996. mal basis for a conservative extension of the LF logical framework. LLF c ..."
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Cited by 217 (44 self)
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We present the linear type theory LLF as the forAppeared in the proceedings of the Eleventh Annual IEEE Symposium on Logic in Computer Science  LICS'96 (E. Clarke editor), pp. 264275, New Brunswick, NJ, July 2730 1996. mal basis for a conservative extension of the LF logical framework. LLF combines the expressive power of dependent types with linear logic to permit the natural and concise representation of a whole new class of deductive systems, namely those dealing with state. As an example we encode a version of MiniML with references including its type system, its operational semantics, and a proof of type preservation. Another example is the encoding of a sequent calculus for classical linear logic and its cut elimination theorem. LLF can also be given an operational interpretation as a logic programming language under which the representations above can be used for type inference, evaluation and cutelimination. 1 Introduction A logical framework is a formal system desig...
Higherorder narrowing with definitional trees
 Neural Computation
, 1996
"... Functional logic languages with a sound and complete operational semantics are mainly based on narrowing. Due to the huge search space of simple narrowing, steadily improved narrowing strategies have been developed in the past. Needed narrowing is currently the best narrowing strategy for firstord ..."
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Cited by 78 (23 self)
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Functional logic languages with a sound and complete operational semantics are mainly based on narrowing. Due to the huge search space of simple narrowing, steadily improved narrowing strategies have been developed in the past. Needed narrowing is currently the best narrowing strategy for firstorder functional logic programs due to its optimality properties w.r.t. the length of derivations and the number of computed solutions. In this paper, we extend the needed narrowing strategy to higherorder functions and λterms as data structures. By the use of definitional trees, our strategy computes only incomparable solutions. Thus, it is the first calculus for higherorder functional logic programming which provides for such an optimality result. Since we allow higherorder logical variables denoting λterms, applications go beyond current functional and logic programming languages.
Inductive Data Type Systems
 THEORETICAL COMPUTER SCIENCE
, 1997
"... In a previous work (“Abstract Data Type Systems”, TCS 173(2), 1997), the last two authors presented a combined language made of a (strongly normalizing) algebraic rewrite system and a typed λcalculus enriched by patternmatching definitions following a certain format, called the “General Schema”, w ..."
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Cited by 44 (10 self)
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In a previous work (“Abstract Data Type Systems”, TCS 173(2), 1997), the last two authors presented a combined language made of a (strongly normalizing) algebraic rewrite system and a typed λcalculus enriched by patternmatching definitions following a certain format, called the “General Schema”, which generalizes the usual recursor definitions for natural numbers and similar “basic inductive types”. This combined language was shown to be strongly normalizing. The purpose of this paper is to reformulate and extend the General Schema in order to make it easily extensible, to capture a more general class of inductive types, called “strictly positive”, and to ease the strong normalization proof of the resulting system. This result provides a computation model for the combination of an algebraic specification language based on abstract data types and of a strongly typed functional language with strictly positive inductive types.
Birewrite systems
, 1996
"... In this article we propose an extension of term rewriting techniques to automate the deduction in monotone preorder theories. To prove an inclusion a ⊆ b from a given set I of them, we generate from I, using a completion procedure, a birewrite system 〈R⊆, R⊇〉, that is, a pair of rewrite relations ..."
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Cited by 29 (9 self)
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In this article we propose an extension of term rewriting techniques to automate the deduction in monotone preorder theories. To prove an inclusion a ⊆ b from a given set I of them, we generate from I, using a completion procedure, a birewrite system 〈R⊆, R⊇〉, that is, a pair of rewrite relations −−− → R ⊆ and −−− → R ⊇ , and seek a common term c such that a −−−→ R ⊆ c and b −−−→
HigherOrder Rewriting
 12th Int. Conf. on Rewriting Techniques and Applications, LNCS 2051
, 1999
"... This paper will appear in the proceedings of the 10th international conference on rewriting techniques and applications (RTA'99). c flSpringer Verlag. ..."
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Cited by 20 (1 self)
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This paper will appear in the proceedings of the 10th international conference on rewriting techniques and applications (RTA'99). c flSpringer Verlag.
A decision algorithm for stratified context unification
 FACHBEREICH INFORMATIK, J.W. GOETHEUNIVERSITAT
, 1999
"... Context unification is a variant of second order unification and also a generalization of string unification. Currently it is not known whether context unification is decidable. A specialization of context unification is stratified context unification. Recently, it turned out that stratified context ..."
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Cited by 17 (1 self)
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Context unification is a variant of second order unification and also a generalization of string unification. Currently it is not known whether context unification is decidable. A specialization of context unification is stratified context unification. Recently, it turned out that stratified context unification and onestep rewrite constraints are equivalent. This paper contains a description of a decision algorithm SCU for stratified context unification, which shows decidability of stratified context unification as well as of satisfiability of onestep rewrite constraints.
A CallbyNeed Strategy for HigherOrder FunctionalLogic Programming
 LOGIC PROGRAMMING. PROC. OF THE 1995 INTERNATIONAL SYMPOSIUM
, 1995
"... We present an approach to truely higherorder functionallogic programming based on higherorder narrowing. Roughly speaking, we model a higherorder functional core language by higherorder rewriting and extend it by logic variables. For the integration of logic programs, conditional rules are suppo ..."
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Cited by 11 (5 self)
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We present an approach to truely higherorder functionallogic programming based on higherorder narrowing. Roughly speaking, we model a higherorder functional core language by higherorder rewriting and extend it by logic variables. For the integration of logic programs, conditional rules are supported. For solving goals in this framework, we present a complete calculus for higherorder conditional narrowing. We develop several refinements that utilize the determinism of functional programs. These refinements can be combined to a narrowing strategy which generalizes callbyneed as in functional programming, where the dedicated higherorder methods are only used for full higherorder goals. Furthermore, we propose an implementational model for this narrowing strategy which delays computations until needed.
On Reducing the Search Space of HigherOrder Lazy Narrowing
, 1999
"... Higherorder lazy narrowing is a general method for solving Eunification problems in theories presented as sets of rewrite rules. In this paper we study the possibility to improve the search for normalized solutions of a higherorder lazy narrowing calculus LN. We introduce a new calculus, LNff, ob ..."
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Cited by 9 (5 self)
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Higherorder lazy narrowing is a general method for solving Eunification problems in theories presented as sets of rewrite rules. In this paper we study the possibility to improve the search for normalized solutions of a higherorder lazy narrowing calculus LN. We introduce a new calculus, LNff, obtained by extending LN and define an equation selection strategy Sn such that LNff with strategy Sn is complete. The main advantages of using LNff with strategy Sn instead of LN include the possibility to restrict the application of outermost narrowing at variable position, and the computation of more specific solutions because of additional inference rules for solving exex equations. We also show that for orthogonal pattern rewrite systems we can adopt an eager variable elimination strategy that makes the calculus LNff with strategy Sn even more deterministic.
HigherOrder Lazy Narrowing Calculus: A Computation Model for a Higherorder Functional Logic Language
 In Proceedings of Sixth International Joint Conference, ALP '97  HOA '97, LNCS 1298
, 1997
"... this paper we present a computation model for a higherorder functional and logic programming. Although investigations of computation models for higherorder functional logic languages are under way[13, 9, 8, 20, 22], implemented functional logic languages like KLEAF[6] and Babel[18] among others, a ..."
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Cited by 8 (4 self)
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this paper we present a computation model for a higherorder functional and logic programming. Although investigations of computation models for higherorder functional logic languages are under way[13, 9, 8, 20, 22], implemented functional logic languages like KLEAF[6] and Babel[18] among others, are all based on firstorder models of computation. Firstorder narrowing has been used as basic computation mechanism. The lack of higherorderness is exemplified by the following prototypical program
A Structured Set of HigherOrder Problems
 Theorem Proving in Higher Order Logics: TPHOLs 2005, LNCS 3603
, 2005
"... Abstract. We present a set of problems that may support the development of calculi and theorem provers for classical higherorder logic. We propose to employ these test problems as quick and easy criteria preceding the formal soundness and completeness analysis of proof systems under development. Ou ..."
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Cited by 8 (5 self)
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Abstract. We present a set of problems that may support the development of calculi and theorem provers for classical higherorder logic. We propose to employ these test problems as quick and easy criteria preceding the formal soundness and completeness analysis of proof systems under development. Our set of problems is structured according to different technical issues and along different notions of semantics (including Henkin semantics) for higherorder logic. Many examples are either theorems or nontheorems depending on the choice of semantics. The examples can thus indicate the deductive strength of a proof system. 1 Motivation: Test Problems for HigherOrder Reasoning Systems Test problems are important for the practical implementation of theorem provers as well as for the preceding theoretical development of calculi, strategies and heuristics. If the test theorems can be proven (resp. the nontheorems cannot) then they ideally provide a strong indication for completeness (resp. soundness). Examples for early publications providing firstorder test problems are [21,29,23]. For more than decade now the TPTP library [28] has been developed as a systematically structured electronic repository of