Results 1  10
of
49
InductiveDataType Systems
, 2002
"... In a previous work ("Abstract Data Type Systems", TCS 173(2), 1997), the leI two authors presented a combined lmbined made of a (strongl normal3zG9 alrmal rewrite system and a typed #calA#Ik enriched by patternmatching definitions folnitio a certain format,calat the "General Schem ..."
Abstract

Cited by 821 (23 self)
 Add to MetaCart
In a previous work ("Abstract Data Type Systems", TCS 173(2), 1997), the leI two authors presented a combined lmbined made of a (strongl normal3zG9 alrmal rewrite system and a typed #calA#Ik enriched by patternmatching definitions folnitio a certain format,calat the "General Schema", whichgeneral39I theusual recursor definitions fornatural numbers and simil9 "basic inductive types". This combined lmbined was shown to bestrongl normalIk39f The purpose of this paper is toreformul33 and extend theGeneral Schema in order to make it easil extensibl3 to capture a more general cler of inductive types, cals, "strictly positive", and to ease the strong normalgAg9Ik proof of theresulGGg system. Thisresul provides a computation model for the combination of anal"DAfGI specification language based on abstract data types and of astrongl typed functional language with strictly positive inductive types.
Term Rewriting Systems
, 1992
"... Term Rewriting Systems play an important role in various areas, such as abstract data type specifications, implementations of functional programming languages and automated deduction. In this chapter we introduce several of the basic comcepts and facts for TRS's. Specifically, we discuss Abstra ..."
Abstract

Cited by 610 (18 self)
 Add to MetaCart
Term Rewriting Systems play an important role in various areas, such as abstract data type specifications, implementations of functional programming languages and automated deduction. In this chapter we introduce several of the basic comcepts and facts for TRS's. Specifically, we discuss Abstract Reduction Systems
Specification and Proof in Membership Equational Logic
 THEORETICAL COMPUTER SCIENCE
, 1996
"... This paper is part of a longterm effort to increase expressiveness of algebraic specification languages while at the same time having a simple semantic basis on which efficient execution by rewriting and powerful theoremproving tools can be based. In particular, our rewriting techniques provide s ..."
Abstract

Cited by 129 (52 self)
 Add to MetaCart
This paper is part of a longterm effort to increase expressiveness of algebraic specification languages while at the same time having a simple semantic basis on which efficient execution by rewriting and powerful theoremproving tools can be based. In particular, our rewriting techniques provide semantic foundations for Maude's functional sublanguage, where they have been efficiently implemented. Membership equational logic is quite simple, and yet quite powerful. Its atomic formulae are equations and sort membership assertions, and its sentences are Horn clauses. It extends in a conservative way both ordersorted equational logic and partial algebra approaches, while Horn logic can be very easily encoded. After introducing the basic concepts of the logic, we give conditions and proof rules with which efficient equational deduction by rewriting can be achieved. We also give completion techniques to transform a specification into one meeting these conditions. We address the important ...
Automated Theorem Proving by Test Set Induction
 JOURNAL OF SYMBOLIC COMPUTATION
, 1997
"... Test set induction is a goaldirected proof technique which combines the full power of explicit induction and proof by consistency. It works by computing an appropriate explicit induction scheme called a test set, to trigger the induction proof, and then applies a refutation principle using proof by ..."
Abstract

Cited by 28 (10 self)
 Add to MetaCart
Test set induction is a goaldirected proof technique which combines the full power of explicit induction and proof by consistency. It works by computing an appropriate explicit induction scheme called a test set, to trigger the induction proof, and then applies a refutation principle using proof by consistency techniques. We present a general scheme for test set induction together with a simple soundness proof. Our method is based on new notions of test sets, induction variables, and provable inconsistency, which allow us to refute false conjectures even in the case where the functions are not completely deøned. We show how test sets can be computed when the constructors are not free, and give an algorithm for computing induction variables. Finally, we present a procedure for proof by test set induction which is refutationally complete for a larger class of specifications than has been shown in previous work. The method has been implemented in the prover SPIKE. Based on computer ex...
Difference Unification
, 1992
"... We extend previous work on difference identification and reduction as a technique for automated reasoning. We generalize unification so that terms are made equal not only by finding substitutions for variables but also by hiding term structure. This annotation of structural differences serves to dir ..."
Abstract

Cited by 27 (4 self)
 Add to MetaCart
We extend previous work on difference identification and reduction as a technique for automated reasoning. We generalize unification so that terms are made equal not only by finding substitutions for variables but also by hiding term structure. This annotation of structural differences serves to direct rippling, a kind of rewriting designed to remove structural differences in a controlled way. On the technical side, we give a rulebased algorithm for difference unification, and analyze its correctness, completeness, and complexity. On the practical side, we present a novel search strategy (called leftfirst search) for applying these rules in an efficient way. Finally, we show how this algorithm can be used in new ways to direct rippling and how it can play an important role in theorem proving and other kinds of automated reasoning.
Automated Mathematical Induction
, 1992
"... Proofs by induction are important in many computer science and artiøcial intelligence applications, in particular, in program veriøcation and speciøcation systems. We present a new method to prove (and disprove) automatically inductive properties. Given a set of axioms, a wellsuited induction schem ..."
Abstract

Cited by 27 (6 self)
 Add to MetaCart
(Show Context)
Proofs by induction are important in many computer science and artiøcial intelligence applications, in particular, in program veriøcation and speciøcation systems. We present a new method to prove (and disprove) automatically inductive properties. Given a set of axioms, a wellsuited induction scheme is constructed automatically. We call such an induction scheme a test set. Then, for proving a property, we just instantiate it with terms from the test set and apply pure algebraic simpliøcation to the result. This method needs no completion and explicit induction. However it retains their positive features, namely, the completeness of the former and the robustness of the latter. It has been implemented in the theoremprover SPIKE 1 . 1 Introduction 1.1 Motivation Inductive reasoning is simply a method of performing inferences in domains where there exists a wellfounded relation on the objects. It is fundamental when proving properties of numbers, datastructures, or programs axiomat...
Inductive synthesis of equational programs
 In Eighth National Conf. on Arti cial Intelligence
, 1990
"... An equational approach to the synthesis of functional and logic program is taken. In this context, the synthesis task involves nding executable equations such that the given speci cation holds in their standard model. Hence, to synthesize such programs, induction is necessary.We formulate procedures ..."
Abstract

Cited by 27 (3 self)
 Add to MetaCart
An equational approach to the synthesis of functional and logic program is taken. In this context, the synthesis task involves nding executable equations such that the given speci cation holds in their standard model. Hence, to synthesize such programs, induction is necessary.We formulate procedures for inductiveproof,aswell as for program synthesis, using the framework of \ordered rewriting". We also propose heuristics for generalizing from a sequence of equational consequences. These heuristics handle cases where the deductive process alone is inadequate for coming up with a program. 1.
Inductionless Induction
, 1994
"... Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.1 A few words explaining the title . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 Some examples of the problem we are considering . . . . . . . . . . . . . . . . . . . ..."
Abstract

Cited by 23 (0 self)
 Add to MetaCart
Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.1 A few words explaining the title . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 Some examples of the problem we are considering . . . . . . . . . . . . . . . . . . . 3 1.3 Outline of the chapter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2 Formal background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.1 Terms and clauses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.2 Equational deduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.3 Inductive theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.4 Constructors and sufficient completeness . . . . . . . . . . . . . . . . . . . . . . . . 8 2.5 Term Rewriting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.6 Standar