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Software Engineering, IEEE Transactions on

Issue 11 • Date Nov. 1985

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Displaying Results 1 - 17 of 17
  • IEEE Transactions on Software Engineering - Table of contents

    Publication Year: 1985 , Page(s): c1
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    Freely Available from IEEE
  • IEEE Computer Society

    Publication Year: 1985 , Page(s): c2
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  • Foreword What is AI? And What Does It Have to Do with Software Engineering?

    Publication Year: 1985 , Page(s): 1253 - 1256
    Cited by:  Papers (2)
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  • A 15 Year Perspective on Automatic Programming

    Publication Year: 1985 , Page(s): 1257 - 1268
    Cited by:  Papers (103)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4040 KB)  

    Automatic programming consists not only of an automatic compiler, but also some means of acquiring the high-level specification to be compiled, some means of determining that it is the intended specification, and some (interactive) means of translating this high-level specification into a lower-level one which can be automatically compiled. View full abstract»

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  • Automating the Transformational Development of Software

    Publication Year: 1985 , Page(s): 1268 - 1277
    Cited by:  Papers (44)
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    This paper reports on efforts to extend the transformational implementation (TI) model of software development [1]. In particular, we describe a system that uses AI techniques to automate major portions of a transformational implementation. The work has focused on the formalization of the goals, strategies, selection rationale, and finally the transformations used by expert human developers. A system has been constructed that includes representations for each of these problem-solving components, as well as machinery for handling human-system interaction and problem-solving control. We will present the system and illustrate automation issues through two annotated examples. View full abstract»

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  • Research on Knowledge-Based Software Environments at Kestrel Institute

    Publication Year: 1985 , Page(s): 1278 - 1295
    Cited by:  Papers (37)
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    We present a summary of the CHI project conducted at Kestrel Institute through mid-1984. The objective of this project was to perform research on knowledge-based software environments. Toward this end, key portions of a prototype environment, called CHI, were built that established the feasibility of this approach. One result of this research was the development of a wide-spectrum language that could be used to express all stages of the program development process in the system. Another result was that the prototype compiler was used to synthesize itself from very-high-level description of itself. In this way the system was bootstrapped. We describe the overall nature of the work done on this project, give highlights of implemented prototypes, and describe the implications that this work suggests for the future of software engineering. In addition to this historical perspective, current research projects at Kestrel Institute as well as commercial applications of the technology at Reasoning Systems are briefly surveyed. View full abstract»

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  • The Programmer's Apprentice: A Session with KBEmacs

    Publication Year: 1985 , Page(s): 1296 - 1320
    Cited by:  Papers (46)  |  Patents (1)
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    The Knowledge-Based Editor in Emacs (KBEmacs) is the current demonstration system implemented as part of the Programmer's Apprentice project. KBEmacs is capable of acting as a semiexpert assistant to a person who is writing a program-taking over some parts of the programming task. Using KBEmacs, it is possible to construct a program by issuing a series of high level comnmands. This series of commands can be as much as an order of magnitude shorter than the program it describes. View full abstract»

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  • Domain-Specific Automatic Programming

    Publication Year: 1985 , Page(s): 1321 - 1336
    Cited by:  Papers (53)
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    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. View full abstract»

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  • Enhanced Maintenance and Explanation of Expert Systems Through Explicit Models of Their Development

    Publication Year: 1985 , Page(s): 1337 - 1351
    Cited by:  Papers (20)  |  Patents (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4728 KB)  

    Principled development techniques could greatly enhance the understandability of expert systems for both users and system developers. Current systems have limited explanatory capabilities and present maintenance problems because of a failure to explicitly represent the knowledge and reasoning that went into their design. This paper describes a paradigm for constructing expert systems which attempts to identify that tacit knowledge, provide means for capturing it in the knowledge bases of expert systems, and, apply it towards more perspicuous machine-generated explanations and more consistent and maintainable system organization. View full abstract»

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  • The Role of Domain Expenence in Software Design

    Publication Year: 1985 , Page(s): 1351 - 1360
    Cited by:  Papers (35)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4800 KB)  

    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. View full abstract»

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  • Understanding and Automating Algorithm Design

    Publication Year: 1985 , Page(s): 1361 - 1374
    Cited by:  Papers (14)
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    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. View full abstract»

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  • The Roles of Execution and Analysis in Algorthm Design

    Publication Year: 1985 , Page(s): 1375 - 1386
    Cited by:  Papers (5)
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    The analysis and execution of partial algorithm descriptions is an important part of the algorithm design process (as is borne out by studying the behavior of human algorithm designers). In this paper, we describe a language for representing partially designed algorithms and a process, developmental evaluation, that can discover useful knowledge to guide design. Using these and other results from our research in artificial intelligence, we are building a system, DESIGNER, that automatically designs algorithms. This paper also compares developmental evaluation to execution and analysis techniques used for testing complete programs and for validation of abstract specifications; concepts similar to those found in developmental evaluation are thus shown to apply to all stages of the software life cycle. View full abstract»

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  • Expert Systems and the "Myth" of Symbolic Reasoning

    Publication Year: 1985 , Page(s): 1386 - 1390
    Cited by:  Papers (7)
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    Elements of the artificial intelligence approach to expert systems offer great productivity advantages over traditional approaches to application systems development, even though the end result may be a program employing no AI techniques. These productivity advantages are the hidden truths behind the "myth" that symbolic reasoning programs are better than ordinary ones. View full abstract»

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  • The "Software Engineering" of Expert Systems: Is Prolog Appropriate?

    Publication Year: 1985 , Page(s): 1391 - 1400
    Cited by:  Papers (7)
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    This paper is a preliminary assessment of the viability of Prolog as a basis for the design of expert systems, where the major competition is assumed to be from Lisp and Lisp-based systems. We critically examine the basic features of Prolog from various perspectives to see to what extent they support (or hinder) expert system development. Our conclusion is that while Prolog has significant assets along several dimensions, Prolog as it exists today needs to be modified and appropriately enhanced to make it competitive to extant Lisp-based systems; we suggest the nature of some of these modifications. View full abstract»

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  • If Prolog is the Answer, What is the Question? or What it Takes to Support AI Programming Paradigms

    Publication Year: 1985 , Page(s): 1401 - 1408
    Cited by:  Papers (9)
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    Knowledge programming, which makes use of the explicit representation and interpretation of knowledge to create intelligent programs, requires specialized languages and tools to help programmers. Prolog, an implementation of a logic programing language, provides some of these tools; it and other languages have been argued to be the "best" way to do such knowledge programming. This paper raises questions which suggest that any single paradigm of programming (e.g., logic programming or object-oriented programming) benefits by being integrated in a single environment with other paradigms of programming. Integration of these paradigms with each other, and within a flexible, user-friendly computing environment is also necessary. Such an environment must provide source level debugging and monitoring facilities, analysis and performance tuning tools, and an extended set of user communication programs. View full abstract»

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  • IEEE Computer Society Publications

    Publication Year: 1985 , Page(s): 1408-a
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  • Call for Papers

    Publication Year: 1985 , Page(s): 1408
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Aims & Scope

The IEEE Transactions on Software Engineering is interested in well-defined theoretical results and empirical studies that have potential impact on the construction, analysis, or management of software. The scope of this Transactions ranges from the mechanisms through the development of principles to the application of those principles to specific environments. Specific topic areas include: a) development and maintenance methods and models, e.g., techniques and principles for the specification, design, and implementation of software systems, including notations and process models; b) assessment methods, e.g., software tests and validation, reliability models, test and diagnosis procedures, software redundancy and design for error control, and the measurements and evaluation of various aspects of the process and product; c) software project management, e.g., productivity factors, cost models, schedule and organizational issues, standards; d) tools and environments, e.g., specific tools, integrated tool environments including the associated architectures, databases, and parallel and distributed processing issues; e) system issues, e.g., hardware-software trade-off; and f) state-of-the-art surveys that provide a synthesis and comprehensive review of the historical development of one particular area of interest.

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Meet Our Editors

Editor-in-Chief
Matthew B. Dwyer
Dept. Computer Science and Engineering
256 Avery Hall
University of Nebraska-Lincoln
Lincoln, NE 68588-0115 USA
tseeicdwyer@computer.org