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Journal ArticleDOI

Constructing Induction Rules for Deductive Synthesis Proofs

01 Mar 2006-Electronic Notes in Theoretical Computer Science (Elsevier Science Publishers B. V.)-Vol. 153, Iss: 1, pp 3-21
TL;DR: It is shown that a combination of rippling and the use of meta-variables as a least-commitment device can provide novelty in induction rule construction techniques that can introduce novel recursive structures.
About: This article is published in Electronic Notes in Theoretical Computer Science.The article was published on 2006-03-01 and is currently open access. It has received 2969 citations till now. The article focuses on the topics: Recursion & Mathematical proof.
Citations
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Book ChapterDOI
13 Sep 2004
TL;DR: This is a tutorial paper on the tool Uppaal to be a short introduction on the flavor of timed automata implemented in the tool, to present its interface, and to explain how to use the tool.
Abstract: This is a tutorial paper on the tool Uppaal. Its goal is to be a short introduction on the flavor of timed automata implemented in the tool, to present its interface, and to explain how to use the tool. The contribution of the paper is to provide reference examples and modeling patterns.

1,686 citations

Journal ArticleDOI
01 Mar 2006
TL;DR: In this paper, a taxonomy of model transformation is proposed based on the discussions of a working group on model transformation of the Dagstuhl seminar on Language Engineering for Model-Driven Software Development.
Abstract: This article proposes a taxonomy of model transformation, based on the discussions of a working group on model transformation of the Dagstuhl seminar on Language Engineering for Model-Driven Software Development. This taxonomy can be used, among others, to help developers in deciding which model transformation language or tool is best suited to carry out a particular model transformation activity.

975 citations

Journal ArticleDOI
TL;DR: Minimal recursion semantics (MRS) as discussed by the authors is a framework for computational semantics that is suitable for parsing and generation and can be implemented in typed feature structure formalisms, which enables a simple formulation of the grammatical constraints on lexical and phrasal semantics, including the principles of semantic composition.
Abstract: Minimal recursion semantics (MRS) is a framework for computational semantics that is suitable for parsing and generation and that can be implemented in typed feature structure formalisms. We discuss why, in general, a semantic representation with minimal structure is desirable and illustrate how a descriptively adequate representation with a nonrecursive structure may be achieved. MRS enables a simple formulation of the grammatical constraints on lexical and phrasal semantics, including the principles of semantic composition. We have integrated MRS with a broad-coverage HPSG grammar.

960 citations

Book ChapterDOI
09 Apr 2008
TL;DR: Pex automatically produces a small test suite with high code coverage for a .NET program by performing a systematic program analysis using dynamic symbolic execution, similar to path-bounded model-checking, to determine test inputs for Parameterized Unit Tests.
Abstract: Pex automatically produces a small test suite with high code coverage for a .NET program. To this end, Pex performs a systematic program analysis (using dynamic symbolic execution, similar to path-bounded model-checking) to determine test inputs for Parameterized Unit Tests. Pex learns the program behavior by monitoring execution traces. Pex uses a constraint solver to produce new test inputs which exercise different program behavior. The result is an automatically generated small test suite which often achieves high code coverage. In one case study, we applied Pex to a core component of the .NET runtime which had already been extensively tested over several years. Pex found errors, including a serious issue.

900 citations

Journal ArticleDOI
TL;DR: The main characteristics of a good quality process are discussed, the key testing phases are surveyed and modern functional and model-based testing approaches are presented.

658 citations

References
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01 Jan 1999
TL;DR: The topics in LNAI include automated reasoning, automated programming, algorithms, knowledge representation, agent-based systems, intelligent systems, expert systems, machine learning, natural-language processing, machine vision, robotics, search systems, knowledge discovery, data mining, and related programming languages.
Abstract: LNAI was established in the mid-1980s as a topical subseries of LNCS focusing on artificial intelligence. This subseries is devoted to the publication of state-of-the-art research results in artificial intelligence, at a high level and in both printed and electronic versions making use of the well-established LNCS publication machinery. As with the LNCS mother series, proceedings and postproceedings are at the core of LNAI; however, all other sublines are available for LNAI as well. The topics in LNAI include automated reasoning, automated programming, algorithms, knowledge representation, agent-based systems, intelligent systems, expert systems, machine learning, natural-language processing, machine vision, robotics, search systems, knowledge discovery, data mining, and related programming languages.

3,464 citations

Book
01 Jan 1979
TL;DR: This paper presents a meta-modelling simulation of the response of the immune system to changes in the environment through the course of natural selection.
Abstract: • Constraint domains in which the possible values that a variable can take are restricted to a finite set. • Examples: Boolean constraints, or integer constraints in which each variable is constrained to lie in within a finite range of integers. • Widely used in constraint programming. • Many real problems can be easily represented using constraint domains, e.g.: scheduling, routing and timetabling. • They involve choosing amongst a finite number of possibilities. • Commercial importance to many businesses: e.g. deciding how air crews should be allocated to aircraft flights. • Developed methods by different research communities: Arc and node consistency techniques (artificial intelligence). Bounds propagation techniques (constraint programming). Integer programming (operations research).

1,123 citations

Journal ArticleDOI
Michael Hanus1
TL;DR: This paper surveys the development of the operational semantics as well as the improvement of the implementation of functional logic languages.
Abstract: Functional and logic programming are the most important declarative programming paradigms, and interest in combining them has grown over the last decade. Early research concentrated on the definition and improvement of execution principles for such integrated languages, while more recently efficient implementations of these execution principles have been developed so that these languages became relevant for practical applications. In this paper, we survey the development of the operational semantics as well as the improvement of the implementation of functional logic languages.

489 citations

Book ChapterDOI
28 Jul 2003
TL;DR: The IsaPlanner as mentioned in this paper is a generic framework for proof planning in the interactive theorem prover Isabelle, which facilitates the encoding of reasoning techniques, which can be used to conjecture and prove theorems automatically.
Abstract: IsaPlanner is a generic framework for proof planning in the interactive theorem prover Isabelle. It facilitates the encoding of reasoning techniques, which can be used to conjecture and prove theorems automatically. This paper introduces our approach to proof planning, gives and overview of IsaPlanner, and presents one simple yet effective reasoning technique.

225 citations

Journal ArticleDOI
TL;DR: It is shown how the failure if rippling can be used in bridging gaps in the search for inductive proofs, and a novel theorem-proving architecture for supporting the automatic discovery of eureka steps is presented.
Abstract: Proof by mathematical induction gives rise to various kinds of eureka steps, e.g., missing lemmata and generalization. Most inductive theorem provers rely upon user intervention in supplying the required eureka steps. In contrast, we present a novel theorem-proving architecture for supporting the automatic discovery of eureka steps. We build upon rippling, a search control heuristic designed for inductive reasoning. We show how the failure if rippling can be used in bridging gaps in the search for inductive proofs.

184 citations