Showing papers on "Domain (software engineering) published in 1985"

The Expanding Domain of Economics

Abstract: As to Marshall, how terribly narrow, dull, bourgeois! Must we economists limit our attention to the ordinary, the crassly material business of life? While equally prosaic, Robbins' "relationship between ends and scarce means" does open the door wider. After all, the ends that men and women seek include not just bread and butter but also reputation, adventure, sex, status, eternal salvation, the meaning of life, and a good night's sleep the means for achieving any of these being, too often, notably scarce. In dealing with economics as an expansive imperialist discipline (see Gerard Radnitzky and Peter Bernholz [1985]), a geopolitical metaphor may be illuminating. Our heartland is an intellectual territory carved off by two narrowing conceptions: (1) of manas rational, selfinterested decisionmaker, and (2) of social interaction as typified by market exchange. However, the logic of ideas irresistibly draws economists beyond these core areas. Rational self-interested choice plays a role in many domains of life other than markets, for example in politics, warfare, mate selection, engineering design, and statistical decisions. Conversely, even within the domain of market behavior, economists can hardly deny that what people want to buy and sell is influenced by cultural, ethical, and even "irrational" forces more customarily studied by social psychologists and anthropologists. And how people go about their dealings in the market touches upon issues also involving law and sociology. Responding to these intellectual attractions, the rhetoric of an economic imperialist like Gary S. Becker is notably more muscular:

The Role of Domain Expenence in Software Design

Abstract: A designer's expertise rests on the knowledge and skills which develop with experience in a domain. As a result, when a designer is designing an object in an unfamiliar domain he will not have the same knowledge and skills available to him as when he is designing an object in a familiar domain. In this paper we look at the software designer's underlying constellation of knowledge and skills, and at the way in which this constellation is dependent upon experience in a domain. What skills drop out, what skills, or interactions of skills come forward as experience with the domain changes? To answer the above question, we studied expert designers in experimentally created design contexts with which they were differentially familiar. In this paper we describe the knowledge and skills we found were central to each of the above contexts and discuss the functional utility of each. In addition to discussing the knowledge and skills we observed in expert designers, we will also compare novice and expert behavior.

The concept and implementation of skeletal plans

Abstract: A new method for automated planning, refinement of skeletal plans, has been developed for the problem of experiment design in the domain of molecular biology. The method resulted from a study of the problem-solving behavior of scientists which showed that design usually consisted of look-up of abstracted plans followed by hierarchical plan-step refinement. The skeletal plan method has been implemented through two generations of problem-solving systems, the second generation involving a synthesis with the metaplanning approach of Stefik.

Selection of an Appropriate Domain for an Expert System

Abstract: This article discusses the selection of the domain for a knowledge-based expert system for a corporate application. The selection of the domain is a critical task in an expert system development. At the start of a project looking into the development of an expert system, the knowledge engineering project team must investigate one or several possible expert system domains. They must decide whether the selected application(s) are best suited to solution by present expert system technology, or if there might be a better way (or, possibly, no way) to attack the problems. If there are several possibilities, the team must also rank the potential applications and select the best available. To evaluate the potential of possible application domains, it has proved very useful to have a set of desired attributes for good expert domain. This article presents such a set of attributes. The attribute set was developed as part of a major expert system development project at GTE Laboratories. It was used recurrently (and modified and expanded continually) throughout an extensive application domain evaluation and selection process.

Domain-Specific Automatic Programming

Abstract: Domain knowledge is crucial to an automatic programming system and the interaction between domain knowledge and programming at the current time. The NIX project at Schlumberger-Doll Research has been investigating this issue in the context of two application domains related to oil well logging. Based on these experiments we have developed a framework for domain-specific automatic programming. Within the framework, programming is modeled in terms of two activities, formalization and implementation, each of which transforms descriptions of the program as it proceeds through intermediate states of development. The activities and transformations may be used to characterize the interaction of programming knowledge and domain knowledge in an automatic programming system.

MORE: an intelligent knowledge acquisition tool

Abstract: MORE is a tool that assists in eliciting knowledge from domain experts. Acquired information is added to a domain model of qualitative causal relations that may hold among hypotheses, symptoms, and background conditions. After generating diagnostic rules from the domain model, MORE prompts for additional information that would allow a stronger set of diagnostic rules to be generated, MORE'S primary value lies in its understanding of what kinds of knowledge are likely to be diagnostically significant. By formulating its questions in a way that focuses on such knowledge, it makes the most effective use of the domain experts' time.

A computer model of case-based reasoning in problem solving: an investigation in the domain of dispute mediation (analogy, machine learning, conceptual memory)

Abstract: Abstract : Rather than approach each problem as a unique event, people often try to solve problems by recalling similar previous experiences as guides to problem solving. This analogical process, which we call case-based reasoning, seems to provide an explanation for the change in problem solving behavior of people over time. This research presents a computer process model of problem solving based on the use of case-based reasoning. The necessary reasoning processes, operational measures of similarity, and memory structures needed for effective storage and retrieval are presented via the specifications for an advisory system called the MEDIATOR, which offers advice on resolving common sense disputes. In this context, issues associated with enabling machines to dynamically adapt their reasoning and automatically recover from failure are discussed. The model of case-based problem solving which has been developed seems to offer promise as an integrated solution for some issues in problem solving, analogical reasoning, and machine learning.

Knowledge Acquisition from Multiple Experts

Abstract: Expert system projects are often based on collaboration with single domain expert. This leads to difficulties in judging the suitability of the chosen task and in acquiring the detailed knowledge required to carry out the task. This anecdotal article considers some of the advantages of using a diverse collection of domain experts.

Understanding and automating algorithm design

Abstract: Algorithm design is a challenging intellectual activity that provides a rich source of observation and a test domain for a theory of problem-solving behavior. This paper describes a theory of the algorithm design process based on observations of human design and also outlines a framework for automatic design. The adaptation of the theory of human design to a framework for automation in the DESIGNER system helps us understand human design better, and the implementation process helps validate the framework. Issues discussed in this paper include the problem spaces used for design, the loci of knowledge and problem-solving power, and the relationship to other methods of algorithm design and to automatic programming as a whole.

A critical study of the effectiveness of the single and double exponential models for I–V characterization of solar cells

Abstract: The current-voltage characteristics of photovoltaic solar cells can be described by implicit equations related to a single exponential model (SEM) or to a double exponential model (DEM). Different sets of computer parameters can be found from numerical procedures for one single experimental characteristic measured under specified illumination and temperature conditions. A criterion of effectiveness is defined to evaluate the performance of a set of computer parameters and helps to derive the best-descriptive set of parameters. These are related to the physical parameters and their variations are established from dark to light concentration. It is concluded that the model can produce a good description of the experimental characteristic in a restricted bias domain only.

Domain-Specific Dss Tools for Knowledge-Based Model Building

Abstract: The formulation of complex planning models, such as linearprogramming (LP) systems, is a difficult task that enjoys little supportby current decision support systems tools. It is hypothesized thatcurrent artificial intelligence technology is insufficient to buildgeneralized formulation tools that would be usable by OR-naive endusers. As an alternative, this paper presents a domain-specificapproach to knowledge-based model formulation which combines the use of"syntactic" knowledge about linear programming with A¢Â¬ÂSsemanticA¢Â¬Â? guidanceby knowledge specific to some application domain. As a prototype of thisapproach, a model formulation tool for LP-based production management isunder development at New York University.

Editing by example

Abstract: An editing by example system is an automatic program synthesis facility embedded in a text editor that can be used to solve repetitive text editing problems The user provides the editor with a few examples of a text transformation The system analyzes the examples and generalizes them into a program that can perform the transformation to the rest of the user's text This paper presents an overview of the design, analysis, and implementation of a practical editing by example system It studies the problem of synthesizing a text processing program that generalizes the transformation implicitly described by a small number of input/output examples A class of text processing programs called gap programs is defined and the problems associated with synthesizing them from examples are examined, leading to an efficient heuristic that provably synthesizes a gap program from examples of its input/output behavior The editing by example system derived from this analysis has been embedded in a production text editor By developing an editing by example system that solves a useful class of text processing problems, this work demonstrates that program synthesis is feasible in the domain of text editing

A Computer Model of Case-Based Reasoning in Problem Solving: An Investigation in the Domain of Dispute Mediation.

Abstract: : Rather than approach each problem as a unique event, people often try to solve problems by recalling similar previous experiences as guides to problem solving. This analogical process, which we call case-based reasoning, seems to provide an explanation for the change in problem solving behavior of people over time. This research presents a computer process model of problem solving based on the use of case-based reasoning. The necessary reasoning processes, operational measures of similarity, and memory structures needed for effective storage and retrieval are presented via the specifications for an advisory system called the MEDIATOR, which offers advice on resolving common sense disputes. In this context, issues associated with enabling machines to dynamically adapt their reasoning and automatically recover from failure are discussed. The model of case-based problem solving which has been developed seems to offer promise as an integrated solution for some issues in problem solving, analogical reasoning, and machine learning.

Design as exploring constraints

Abstract: A theory of designing is proposed, developed, and illustrated with examples from the domain of physical form. Designing is seen as the exploration of alternative sets of constraints and of the regions of alternative solutions they bound. Designers with different objectives reach different solutions within the same set of constraints, as do designers with the same objectives operating under different constraints. Constraints represent design rules, relations, conventions, and natural laws to be maintained. Some constraints and objectives are given at the outset of a design but many more are adopted along the way. Varying the constraints and the objectives is part of the design process. The theory accounts for various kinds of expertise in designing: knowledge of particular constraints in a design domain; inference--calculating the consequences of design decisions; preference--using objectives to guide decision-making; and partitioning--skill in dividing a large and complicated design into sets of simpler pieces, and understanding the dependencies between decisions. The ability to manage ambiguity and vagueness is an important aspect of design expertise. A computational model supporting the theory is proposed and its implementation discussed briefly. The constraint explorer, a computational environment for designing based on constraint descriptions is described. We see how the constraint explorer might be used in connection with a simple space- planning problem. The problem is taken from the procedures of the Stichting Architecten Research (S.A.R.), a specific architectural design methodology developed to help architects systematically explore layout variability in alternative floorplan designs. Finally, a selected review of related work in constraint-based programming environments, architectural design methods, and the intersection of the two fields is presented.

Learning intermediate concepts in constructing a hierarchical knowledge base

Abstract: In expert systems, hierarchical reasoning can provide better accuracy and understandability. Here, we develop a method of learning hierarchical knowledge from a case library, in which each training instance is described by low level features and high level concepts (e.g., manifestations and diseases) but not by intermediate concepts (e.g., disease states). Learning intermediate knowledge involves exploiting the old partial intermediate knowledge or creating new intermediate concepts by observing the relationship between the low level features and high level concepts. Experiments in the domain of diagnosing causes of jaundice validate the method.

An extensible object-oriented approach to databases for VLSI/CAD

Abstract: This paper describes an approach to the specification and modeling of information associated with the design and evolution of VLSI components. The approach is characterized by combined structural and behavioral descriptions of a component. Database modeling requirements specific to the VLSI design domain are considered and techniques to address the are described. An extensible object-oriented information management framework, the 3DIS (3 Dimensional Information Space), is presented. The framework has been adapted to capture the underlying semantics of the application environment by the addition of new abstraction primitives. An example 3DIS database for a VLSI design system is presented.

Learning In Complex Domains: A Cognitive Analysis of Computer Programming

Abstract: Publisher Summary The study of human learning and cognition attempts to find out the general principles that can be applied to a wide range of situations to understand learning and cognition within a much more restricted domain, such as a subject matter area. This chapter examines the way novices learn and use their first programming language. Learning a programming language, such as BASIC, includes acquiring a mental model of the underlying system. The chapter presents a formal cognitive analysis of the mental model underlying BASIC statements and presents empirical studies that examine the usefulness of this analysis in explaining the way BASIC is learned, used, and comprehended. The time to comprehend a procedural statement, which is expressed in English or in BASIC, is strongly related to the number of transactions that have to be encoded and the number of other statements in the program. The learning of BASIC is enhanced when learners possess a rich bank of conceptual knowledge that is specifically relevant to BASIC.

Representing Control Knowledge as Abstract Task and Metarules

Abstract: A poorly designed knowledge base can be as cryptic as an arbitrary program and just as difficult to maintain. Representing inference procedures abstractly, separately from domain facts and relations, makes the design more transparent and explainable. The combination of abstract procedures and a relational language for organizing domain knowledge provides a generic framework for constructing knowledge bases for related problems in other domains and also provides a useful starting point for studying the nature of strategies. In HERACLES, inference procedures are represented as abstract metarules, expressed in a form of the predicate calculus, organized and controlled as rule sets. A compiler converts the rules into Lisp code and allows domain relations to be encoded as arbitrary data structures for efficiency. Examples are given of the explanation and teaching capabilities afforded by this representation. Different perspectives for understanding HERACLES'' inference procedure and how it defines knowledge bases are discussed in some detail.

Constraining control

Abstract: Continuations, when available as first-class objects, provide a general control abstraction in programming languages. They liberate the programmer from specific control structures, increasing programming language extensibility. Such continuations may be extended by embedding them in functional objects. This technique is first used to restore a fluid environment when a continuation object is invoked. We then consider techniques for constraining the power of continuations in the interest of security and efficiency. Domain mechanisms, which create dynamic barriers for enclosing control, are implemented using fluids. Domains are then used to implement an unwind-protect facility in the presence of first-class continuations. Finally, we demonstrate two mechanisms, wind-unwind and dynamic-wind, that generalize unwind-protect.

A software classification scheme

Abstract: Author(s): Diaz, Ruben Prieto | Abstract: Reusing code is one approach to software reusability. Code is the end product of the software lifecycle. It is delivered in a low level representation that is difficult to reuse unless an almost perfect match exists between available features and required specifications. There is a need to organize large inventories of software such that reusable code is easy to locate and exchange. The relative success in the reuse of code fragments reported by some software factories is due in part to their capacity to encapsulate domain specific functions and create specialized libraries of components classified by these locally standardized functions.A general software classification scheme that organizes reusability related attributes and common functions from different domains is proposed as a partial solution to the software reusability problem. For the problem of selecting from similar, potentially reusable. components, a partial solution based on evaluation of common characteristics is also proposed. A library system is presented that integrates the proposed classification scheme with an evaluation mechanism based on inherent component attributes, programming languages characteristics and reuser experience.The fundamental contribution of this dissertation is a formal treatment of a faceted scheme for software classification leading to better understanding of reusability at the code level. This approach has been prototyped in a library system for the semi-automatic classification of software components. Analysis were performed to evaluate the classification scheme. The results show the potential of the scheme in organizing collections of code fragments, in improving retrieval, and in simplifying the classification process. Tests of the evaluation mechanism showed positive correlation with evaluations conducted by potential reusers.

Provable isomorphisms and domain equations in models of typed languages

Abstract: The interest in isomorphisms in models for typed langurges mainly arisees from work done in the study d denotational semantics. This work has led to the notion d solving domain equrtiont as a tool for giving mrthematicd meanin to common amstructs in computer sciena, e.g. recursive definitions d data typea.In this p8per we investigrte the question of which domain equations must hold in all models of a paradigmatic functional language, the typed lambda calculus, and of second order (polymorphic) extensions d it.

Design of an Integrated DBMS to Support Advanced Applications

Abstract: New applications of DBMS’s in areas of sciences, engineering and offices have produced new requirements that are not satisfied in current DBMS’s. Included among these requirements are support for both the normalized and non-normalized models directly at the system interface level, support for text processing, and support of the temporal domain. To provide these supports, one can try to build additional functions on top of or into an existing DBMS. This approach has been deemed to be inefficient. It is believed that much can be gained by designing a new system to satisfy the new requirements more directly.

Expert Control

Abstract: The application of expert systems technology is currently being extended to real-time process control. The potential benefit is to allow rapid application of defined expertise to dynamic problems involving hundreds of variables. The system's approach to this requires the consideration of the challenges of real-time inference, in particular the dynamic nature of the domain, the large knowledge base and the requirements for efficient execution.

ASK is transportable in half a dozen ways

Abstract: This paper is a discussion of the technical issues and solutions encountered in making the ASK System transportable. A natural language system can be “transportable” in a number of ways. Although transportability to a new domain is most prominent, other ways are also important if the system is to have viability in the commercial marketplace.On the one hand, transporting a system to a new domain may start with the system prior to adding any domain of knowledge and extend it to incorporate the new domain. On the other hand, one may wish to add to a system that already has knowledge of one domain the knowledge concerning a second domain, that is, to extend the system to cover this second domain. In the context of ASK, it has been natural to implement extending and then achieve transportability as a special case.In this paper, we consider six ways in which the ASK System can be extended to include new capabilities:to a new domain,to a new object type,to access data from a foreign database,to a new natural language,to a new programming language,to a new computer family.Special-purpose applications, such as those to accommodate standard office tasks, would make use of these various means of extension.