155,820 research outputs found

    A Survey of Languages for Specifying Dynamics: A Knowledge Engineering Perspective

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    A number of formal specification languages for knowledge-based systems has been developed. Characteristics for knowledge-based systems are a complex knowledge base and an inference engine which uses this knowledge to solve a given problem. Specification languages for knowledge-based systems have to cover both aspects. They have to provide the means to specify a complex and large amount of knowledge and they have to provide the means to specify the dynamic reasoning behavior of a knowledge-based system. We focus on the second aspect. For this purpose, we survey existing approaches for specifying dynamic behavior in related areas of research. In fact, we have taken approaches for the specification of information systems (Language for Conceptual Modeling and TROLL), approaches for the specification of database updates and logic programming (Transaction Logic and Dynamic Database Logic) and the generic specification framework of abstract state machine

    Languages and Problem Specification

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    Contribution à un ouvrage.Generally, programming problems are formally described as function computation problems. In this paper we want to see programming problems as language recognition problems. More precisely, we sugget to specify the former problems as systems of languages, i.e. recursive languages built from the concatenation and transformation of recursives languages. To understand our grammatical approach we illustrate it by means of typical examples of programming

    Declaratively solving Google Code Jam problems with Picat

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    In this paper we present several examples of solving algorithmic problems from the Google Code Jam programming contest with Picat programming language using declarative techniques: constraint logic programming and tabled logic programming. In some cases the use of Picat simplifies the implementation compared to conventional imperative programming languages, while in others it allows to directly convert the problem statement into an efficiently solvable declarative problem specification without inventing an imperative algorithm

    An Entry Point for Formal Methods: Specification and Analysis of Event Logs

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    Formal specification languages have long languished, due to the grave scalability problems faced by complete verification methods. Runtime verification promises to use formal specifications to automate part of the more scalable art of testing, but has not been widely applied to real systems, and often falters due to the cost and complexity of instrumentation for online monitoring. In this paper we discuss work in progress to apply an event-based specification system to the logging mechanism of the Mars Science Laboratory mission at JPL. By focusing on log analysis, we exploit the "instrumentation" already implemented and required for communicating with the spacecraft. We argue that this work both shows a practical method for using formal specifications in testing and opens interesting research avenues, including a challenging specification learning problem

    Tools reference manual for a Requirements Specification Language (RSL), version 2.0

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    This report describes a general-purpose Requirements Specification Language, RSL. The purpose of RSL is to specify precisely the external structure of a mechanized system and to define requirements that the system must meet. A system can be comprised of a mixture of hardware, software, and human processing elements. RSL is a hybrid of features found in several popular requirements specification languages, such as SADT (Structured Analysis and Design Technique), PSL (Problem Statement Language), and RMF (Requirements Modeling Framework). While languages such as these have useful features for structuring a specification, they generally lack formality. To overcome the deficiencies of informal requirements languages, RSL has constructs for formal mathematical specification. These constructs are similar to those found in formal specification languages such as EHDM (Enhanced Hierarchical Development Methodology), Larch, and OBJ3

    An Enhanced Features Extractor for a Portfolio of Constraint Solvers

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    Recent research has shown that a single arbitrarily efficient solver can be significantly outperformed by a portfolio of possibly slower on-average solvers. The solver selection is usually done by means of (un)supervised learning techniques which exploit features extracted from the problem specification. In this paper we present an useful and flexible framework that is able to extract an extensive set of features from a Constraint (Satisfaction/Optimization) Problem defined in possibly different modeling languages: MiniZinc, FlatZinc or XCSP. We also report some empirical results showing that the performances that can be obtained using these features are effective and competitive with state of the art CSP portfolio techniques
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