Hostname: page-component-6bf8c574d5-9f2xs Total loading time: 0 Render date: 2025-03-07T00:50:09.470Z Has data issue: false hasContentIssue false
  • English
  • Français

Life cycles in software and knowledge engineering: a comparative review

Published online by Cambridge University Press:  07 July 2009

Michael Wilson ,
David Duce  and
Dan Simpson
Michael Wilson
Affiliation:
Informatics Dept, Rutherford Appleton Laboratory, Chilton, Didcot, Oxon OX11 0QX, UK
David Duce
Affiliation:
Informatics Dept, Rutherford Appleton Laboratory, Chilton, Didcot, Oxon OX11 0QX, UK
Dan Simpson
Affiliation:
Dept of Computing, Brighton Polytechnic
Get access Rights & Permissions [Opens in a new window]

Abstract

Progress in software engineering has led to system development following models of the system life cycle. These models incorporate the use of prototyping and formal methods of program verification. They are becoming supported by integrated project support environments and permit the planning and monitoring of software development projects.

In contrast, knowledge based systems (KBS) are developed using informal views of the system life cycle. Tools have been developed to support some stages of the life cycle in an undisciplined manner. The commercial use of KBS needs development projects to be planned and monitored. This requires methods and tools based on systematic life cycle models to be established for KBS.

This paper reviews the current state of life cycle approaches to software engineering and KBS development projects in order to provide a direction for the development of methodical KBS life cycle models.

Type
Research Article
Information
The Knowledge Engineering Review , Volume 4 , Issue 3 , September 1989 , pp. 189 - 204
Copyright
Copyright © Cambridge University Press 1989

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Cercone, N and McCalla, G, 1987. “What is knowledge representation” In: The Knowledge Frontier: Essays in the Representation of Knowledge Cercone, N and McCalla, G (Eds.) New York: Springer-Verlag. A review of knowledge representation techniques.CrossRefGoogle Scholar
Frieling, M, Alexander, J, Messick, S, Rehfuss, S and Shulman, S, 1985. “Starting a knowledge engineering project: a step-by-step approach” AI Magazine 6(3) 150–165. A guide to the Tektronix knowledge based system development methodology.Google Scholar
Hayes-Roth, F, Waterman, D A, and Lenet, D B, 1983. Building Expert Systems Reading, Mass.: Addison-Wesley.Google Scholar
Laurent, J-P, Ayel, J, Thome, F and Ziebelin, D, 1986. “Comparative evaluation of three expert system development tools: KEE, Knowledge Craft, Art” The Knowledge Engineering Review 1(4) 18–29. A review of the larger toolkits to support knowledge representation and KBS development.CrossRefGoogle Scholar
McGraw, K L and Seale, M R, 1988. “Knowledge elicitation with multiple experts: considerations and techniques” Artificial Intelligence Review 2(1) 31–44.CrossRefGoogle Scholar
Motta, E, Eisenstadt, M, West, M, Pitman, K and Evertsz, R, 1986. “KEATS: the knowledge engineer's assistant” HCRL Report No. 20, Milton Keynes, U.K.: Open University. A description of one of the more advanced tools to support knowledge acquisition.Google Scholar
Neale, I M, 1988. “First generation expert systems: a review of knowledge acquisition methodologies” The Knowledge Engineering Review 3(2) 105–145.CrossRefGoogle Scholar
Peters, L J, 1980. “Software representation and composition techniques” Proceedings of the IEEE 68(9) 1085–93.CrossRefGoogle Scholar
Prerau, D S, 1985. “Selecting an appropriate domain for an expert system” AI Magazine 6(2) Summer 26–30.Google Scholar
Rajan, T, Motta, E and Eisenstadt, M, 1989. “ACQUIST: a tool for knowledge acquisition” In: Research and Development in Expert Systems V Kelly, B and Rector, A (Eds.) 113–125, Cambridge University Press. This paper describes a part of the KEATS-2 suite of tools for KBS development.Google Scholar
Shaw, M L G and Gaines, B R, 1987. “Advances in interactive knowledge engineering” In: Research and Development in Expert Systems III Bramer, M A (Ed.) 111–122, Cambridge: Cambridge University Press. This paper describes the interactive repertory grid elicitation and analysis tools for knowledge acquistion commercially available as RepGrid from the authors.Google Scholar
Williams, A and Lambert, S, 1988. “Expressive power and computability”. In: Approaches to Knowledge Representation: An Introduction, Ringland, G A and Duce, D A (Eds.) Letchworth, England: Research Studies Press.Google Scholar
Wyatt, J, 1987. “The evaluation of clinical decision support systems: a discussion of the methodology in the ACORN project”. In: Proceedings of AIME '87, Fox, J, Fieschi, M and Engelbrecht, R (Eds.), Berlin: Springer-Verlag.Google Scholar
Young, R, 1987. “Intermediate representations”. In: Research and Development in Expert Systems IV Bramer, M A (Ed.), Cambridge: Cambridge University Press.Google Scholar
ANSI/IEEE, 1984. “ANSI/IEEE standard 830–1984” IEEE Guide to Software Requirements Specifications, New York, NY, USA: IEEE Standards Board.Google Scholar
Ashworth, C M, 1988. “Structured systems analysis and design method (SSADM)” Information and Software Technology 30(3) 153–163. This paper outlines the stages of the standard software development method used for UK government projects.CrossRefGoogle Scholar
Boehm, B W, 1981. Software Engineering Economics Englewood Cliffs, NJ, USA: Prentice Hall. This is the standard text on the prediction of the time, effort and resources required for a software development project.Google Scholar
Cambell, I, 1986. “PCTE proposal for a common tool interface”. In: Software Engineering Environments Sommerville, I (Ed.), London: Peter Peregrinus on behalf of the Institution of Electrical Engineers. This is a description of the EEC sponsored interface for software development tools.Google Scholar
Cohen, B, Harwood, W T and Jackson, M I, 1986. The Specification of Complex Systems Wokingham, UK: Addison-Wesley. This review describes several formal notations for the specification of systems, and the formal development approach which can follow from them.Google Scholar
Crispin, R J, 1987. “Experience using VDM in STC”. In: VDM '87: A Formal Method at Work, VDM-Europe Symposium Berlin: Springer Verlag. VDM is the most advanced formal development method, which is described here in terms of its practical application and limitations.Google Scholar
Jackson, M A, 1982. System Development Englewood Cliffs, NJ.: Prentice-Hall International. The Jackson Structured Design method is one of the most popular rigorous development methods along with that described by Yourdon.Google Scholar
Jones, K D, 1987. “Support environments for VDM”. In: VDM '87: A Formal Method at Work, VDM-Europe Symposium Springer Verlag: Berlin. A description of advanced integrated project support environments for formal software engineering methods.Google Scholar
Macro, A and Buxton, J, 1987. The Craft of Software Engineering Reading, Mass.: Addison-Wesley. This is one of the best introductions to the area of software engineering.Google Scholar
Mascot, , 1979. The Official Handbook of MASCOT MASCOT Suppliers Association MASCOT is a rigorous development method for time critical software systems, used by for UK government projects.Google Scholar
Myers, G J, 1979. The Art of Software Testing John Wiley and Sons: New York, NY. Springer-Verlag (Pub.), 1984. Approaches to Prototyping Springer-Verlag: Berlin. The issues associated with prototyping within software engineering are addressed in depth in the papers in this collection.Google Scholar
STARTS Purchasers Groups, 1987. Supplement to the STARTS Purchasers Handbook Manchester: NCC Publications. The STARTS team recommended software tools for software development and the management of software projects in this text.Google Scholar
Yourdon, E, 1972. Techniques of program structure and design Englewood Cliffs, NJ.: Yourdon Press. One of the most popular structured systems methods is described in this book.Google Scholar
Ford, L, 1987. “Artificial intelligence and software engineering: a tutorial introduction to their relationship” Artificial Intelligence Review 1(4) 255–273. An introduction to the role of software engineering in KBS development.CrossRefGoogle Scholar
Green, C J R and Keyes, M M, 1987. “Verification and validation of expert systems”. In: WEST EX 87— Proceedings of the Western Conference on Expert Systems38–43, Washington, D.C.:IEEE Comput. Soc. Press. A description of verification and validation procedures which could be applied to expert systems.Google Scholar
Martinez, J, Munro, P, Silva, M, 1987. “Modelling, validation and software implementation of production systems using high level Petri Nets”, In: Proceedings of the 1987 IEEE International Conference on Robotics and Automation1180–1185, Washington, D.C.:IEEE Computing Society Press. A technique for producing production rule systems which can be validated against user requirements.Google Scholar
Partridge, D and Wilks, Y, 1987. “Does AI have a methodology which is different from software engineering?” Artificial Intelligence Review 1(2) 111–121. A controversial defence of the differences between AI and software engineering methods.CrossRefGoogle Scholar
Anjewierden, A, 1987. “Knowledge acquisition tools” AICOM 0(1) 29–38. This describes the tools being developed to support the KADS KBS development method.CrossRefGoogle Scholar
Breuker, J (Ed.) 1987. Model-Driven Knowledge Acquisition Interpretation Models ESPRIT Project 1098, Deliverable Task A1, University of Amsterdam. A thorough description of the models used in the KADS knowledge acquisition phase.Google Scholar
Breuker, J and Wielinga, B, 1987. “Use of models in the interpretation of verbal data”. In: Knowledge Aquisition for Expert Systems: a Practical Handbook Kidd, A L (Ed.), New York: Plenum Press. A description of the KADS knowledge acquisition phase.Google Scholar
Hayward, S, 1987. “How to build knowledge based systems: techniques, tools, and case studies”. In: ESPRIT '87: Proceedings of the Esprit Conference665–687, Brussels:Commission of the European Economic Community. A brief overview of the complete KADS project.Google Scholar
Wielinga, B and Breuker, J, 1986. “Models of expertise”. In: Proceedings of ECAI 1986 Brighton. This paper provides an overview of the models used in the KADS knowledge acquisition phase.Google Scholar
Keller, R, 1987. Expert System Technology: Development and Application. Englewood Cliffs, NJ, USA: Yourdon Press. A description of the Yourdon structured system development method as applied to KBS.Google Scholar
Montgomery, A 1988. “GEMINI: government expert systems methodology initiative”. In: KBS in Government 88 Duffin, P (Ed.), 75–88, London: Blenheim OnLine Ltd.Google Scholar
Montgomery, A, 1989. “GEMINI: government expert systems methodology initiative”. In: Research and Development in Expert Systems V Kelly, B and Rector, A (Eds.), 14–24, Cambridge: Cambridge University Press.Google Scholar
Worden, R, 1988. “The GEMINI project: preliminary results”. In: KBS in Government 88 Duffin, P (Ed.) 119–130, London: Blenheim OnLine Ltd.Google Scholar