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12
Extending ObjectOriented Design for Physical Modeling
, 1996
"... When we build simulation models and construct dynamical models for physical systems, we often do not do so using a clear overall framework that organizes our geometry, dynamics and models. How do geometry and dynamics intertwine to effect system change over multiple abstraction levels? We present a ..."
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Cited by 10 (2 self)
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When we build simulation models and construct dynamical models for physical systems, we often do not do so using a clear overall framework that organizes our geometry, dynamics and models. How do geometry and dynamics intertwine to effect system change over multiple abstraction levels? We present a methodology, called objectoriented physical modeling (OOPM), which builds on the currently accepted computer science approach in objectoriented program design. This type of modeling injects a way of incorporating geometry and dynamics into general objectoriented design. Moreover, we present an approach to dynamical modeling that mirrors major categories of computer programming languages, thereby achieving a definition of system modeling that reinforces the relation of model to program.
A Taxonomy for Simulation Modeling Based on Programming Language Principles
, 1996
"... We present a new modeling taxonomy for computer simulation. The importance of this work centers on a cohesive approach to modeling that attempts to unify heretofore disparate modeling techniques. For example, while there exists a taxonomy for discrete event simulation, this taxonomy does not incorpo ..."
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Cited by 6 (3 self)
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We present a new modeling taxonomy for computer simulation. The importance of this work centers on a cohesive approach to modeling that attempts to unify heretofore disparate modeling techniques. For example, while there exists a taxonomy for discrete event simulation, this taxonomy does not incorporate models whose execution is via continuous time increment. The modeling taxonomy has a similar structure to computer language categories: declarative, functional and constraint. The multimodeling model type permits the creation of a multilevel heterogeneous model that can integrate different model types, rather than displacing them in favor of a singular modeling method. Instead of advocating the removal of existing modeling techniques, our focus has been on organizing modeling techniques from different disciplines to yield unification. A TAXONOMY FOR SIMULATION MODELING BASED ON PROGRAMMING LANGUAGE PRINCIPLES PAUL A. FISHWICK Dept. of Computer & Information Science and Engineering U...
A Visual ObjectOriented Multimodeling Design Approach for Physical Modeling
 ACM Transactions on Modeling and Computer Simulation
, 1996
"... We present a design approach for structuring multimodels in an objectoriented framework for physical modeling. This approach is termed objectoriented physical modeling (OOPM). Multimodels have played a key role in permitting a model designer to construct largescale dynamical models. We have built ..."
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Cited by 5 (4 self)
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We present a design approach for structuring multimodels in an objectoriented framework for physical modeling. This approach is termed objectoriented physical modeling (OOPM). Multimodels have played a key role in permitting a model designer to construct largescale dynamical models. We have built upon earlier work in multimodeling by specifying how multimodels are defined for objectoriented model designs. The objectoriented approach permits class reusability and a more efficient method for designing multimodels. By using basic physical categories, such as pointmass and manyparticle system as metaphors, we explain the use of this new approach to modeling. 1 Introduction Models exist to allow humans to communicate about the dynamics and geometry of real world objects. Our definition of modeling is described at a level where models are translated into executable programs and formal specifications. Objectoriented methodology in simulation has a long history, as with the introducti...
Conceptual Content Management for Software Engineering Processes
 In 9th East European Conference, ADBIS 2005, volume 3631 of LNCS
, 2005
"... Abstract. A major application area of information systems technology and multimedia content management is that of support systems for engineering processes. This includes the particularly important area of software engineering. Effective support of software engineering processes requires large amoun ..."
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Cited by 3 (2 self)
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Abstract. A major application area of information systems technology and multimedia content management is that of support systems for engineering processes. This includes the particularly important area of software engineering. Effective support of software engineering processes requires large amounts of content (texts, diagrams, code, data, executables etc.) from different conceptual domains. The term “software crisis ” disappeared gradually when content modelling and management addressed domains from application analysis and system design in addition to the sheer computational code domain. In this paper we introduce an innovative conceptual content model and apply it in support of software engineering processes and their artefacts. We base our approach on the core model of the computational domain which abstracts computational content (bodies of function code) by the computational concept of signatures (lists of typed function parameters). We generalise this functional abstraction model beyond the computational domain by introducing the notion of asset abstraction which models entities domainindependently by general contentconcept pairs. We introduce an asset language and discuss the essentials of an asset system implementation. In the application part of the paper we argue that software engineering can be substantially simplified by modelling SE entities from all the domains involved in an SE process homogeneously in an assetoriented approach—entities ranging from application domains over intermediate architectural and design domains down to the computational domain. Furthermore, we discuss how the mappings between such domains can be substantially supported by services based on assetoriented information systems.
What is an Efficient Implementation of the λcalculus?
, 1991
"... We propose to measure the e#ciency of any implementation of the # calculus as a function of a new parameter #, that is itself a function of any #expression. Complexity is expressed here as a function of # just as runtime is expressed as a function of the input size n in ordinary analysis of alg ..."
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Cited by 2 (0 self)
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We propose to measure the e#ciency of any implementation of the # calculus as a function of a new parameter #, that is itself a function of any #expression. Complexity is expressed here as a function of # just as runtime is expressed as a function of the input size n in ordinary analysis of algorithms. This enables implementations to be compared for worst case e#ciency. We argue that any implementation must have complexity #(#), i.e. a linear lower bound. Furthermore, we show that implementations based upon Turner Combinators or Hughes Supercombinators have complexities 2 #(#) , i.e. an exponential lower bound. It is open whether any implementation of polynomial complexity, # O(1) , exists, although some implementations have been implicitly claimed to have this complexity. Introduction Objectives The aim of this paper is to provide a theoretical basis for e#ciency considerations in the implementation of functional languages. So far, people working in this area have approa...
What is an Efficient Implementation of the λcalculus?
, 1991
"... We propose to measure the efficiency of any implementation of the λcalculus as a function of a new parameter ν, that is itself a function of any λexpression. Complexity is expressed here as a function of ν just as runtime is expressed as a function of the input size n in ordinary analysis of algori ..."
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Cited by 2 (0 self)
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We propose to measure the efficiency of any implementation of the λcalculus as a function of a new parameter ν, that is itself a function of any λexpression. Complexity is expressed here as a function of ν just as runtime is expressed as a function of the input size n in ordinary analysis of algorithms. This enables implementations to be compared for worst case efficiency. We argue that any implementation must have complexity Ω(ν), i.e. a linear lower bound. Furthermore, we show that implementations based upon Turner Combinators or Hughes Supercombinators have complexities 2 Ω(ν), i.e. an exponential lower bound. It is open whether any implementation of polynomial complexity, ν O(1), exists, although some implementations have been implicitly claimed to have this complexity.
A Model for a Listoriented Extension of the Lambda Calculus
, 1997
"... This work is intended to provide a semantics for a fragment of a programming language described by Gyorgy R'ev'esz in [R'ev88], for which no model was known. We begin with a brief presentation of the syntax of the lambda calculus and some relevant extensions. We then describe a class of complete lat ..."
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Cited by 1 (0 self)
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This work is intended to provide a semantics for a fragment of a programming language described by Gyorgy R'ev'esz in [R'ev88], for which no model was known. We begin with a brief presentation of the syntax of the lambda calculus and some relevant extensions. We then describe a class of complete lattices and use them as models for the lambda calculus. We then find specialized sublattices which we use as models for the extensions of the lambda calculus, thus achieving the original goal of finding a semantics for R'ev'esz's language.
A Tutorial Introduction to the Lambda Calculus
"... This paper is a short and painless introduction to the λ calculus. Originally ..."
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This paper is a short and painless introduction to the λ calculus. Originally
A Scheme for Interactive Graphics
, 1990
"... CONTENTS SUMMARY .................................................................................................. 1 INTRODUCTION ........................................................................................ 2 Graphics Today ............................................................... ..."
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CONTENTS SUMMARY .................................................................................................. 1 INTRODUCTION ........................................................................................ 2 Graphics Today ....................................................................................... 2 Tools for Graphics Software ................................................................... 2 Outline of the Paper ................................................................................ 3 Cooperation Needed ................................................................................ 3 Interpreters needed .................................................................................. 4 The Shell as the Central Tool .................................................................. 4 The MetaShell Concept ......................................................................... 5 Engineering a Shell ......................................
Prolog/Mali Reference Manual
"... ion is a kind of quantification: the quantification. It has strong connections with universal quantification which are developed in the sequel. As a quantification, abstraction gives rise to the usual notions of free and bound variables. ffl If E and F are in L, then (E F ) is an application in L ..."
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ion is a kind of quantification: the quantification. It has strong connections with universal quantification which are developed in the sequel. As a quantification, abstraction gives rise to the usual notions of free and bound variables. ffl If E and F are in L, then (E F ) is an application in L. Application is supposed to associate to the left so that nested applications (: : : ((a 1 a 2 ) a 3 ) : : : an ) are written (a 1 a 2 a 3 : : : an ), (a n ), or (a) if the number of individuals does not matter 3 . ffl There is a typing function from L to T that satisfies rules (x:E) = (x) ! (E) and 9ff: ( (E) = ff ! fi) ( (F ) = ff) , ((E F )) = fi A constant that is given a predicate type is called a predicate constant. Example 1.2.2 A term x:E with type ff ! fi can be interpreted as a function with parameter x of type ff and result E of type fi. For instance, x:x with type ff ! ff is the identity function for terms having type ff. It is noted id ff . Concrete syntax for x:x ...