ENHANCING THE SOFTWARE LIFE CYCLE OF KNOWLEDGE-BASED SYSTEMS USING A TASK-BASED SPECIFICATION METHODOLOGY

1993 ◽  
Vol 03 (01) ◽  
pp. 3-15 ◽  
Author(s):  
JONATHAN LEE ◽  
JOHN YEN
Keyword(s):  
Life Cycle ◽  
Knowledge Engineering ◽  
Maintenance Phase ◽  
Life Cycles ◽  
Knowledge Based Systems ◽  
Software Life Cycle ◽  
Knowledge Based ◽  
Decomposition Structure ◽  
Solution Specification ◽  
Specification Methodology

Several methodologies have been developed to enhance the software life cycle of knowledge-based systems by emphasizing on the use of both prototypes and specifications. However, these methodologies focus on the development phase of knowledge-based systems. The roles of prototypes and specifications in the maintenance phase has not been fully explored. Because a suitable problem specification for a knowledge-based system is often difficult to acquire, validating changes to non-executable solution specification during the maintenance phase can be a problem. To address this, we propose an alternative paradigm in which the prototype complements the specification throughout the life cycle. The traceability between them is facilitated by organizing both types of artifacts using a common functional decomposition structure. Based on our task-based specification methodology (TBSM), we have also developed a knowledge engineering tool (called TAME) to facilitate the acquisition and the organization of the specification and the prototype. The proposed methodology and the tool together can thus enhance the verification, validation, and the maintenance of knowledge-based systems through their life cycles.

Knowledge-Based Strategies and Systems

2011 ◽  
pp. 1-62 ◽  
Author(s):  
Meir Russ ◽  
J. Greg Jones ◽  
Jeannette K Jones
Keyword(s):  
Knowledge Management ◽  
Life Cycle ◽  
Early Stage ◽  
Management Strategies ◽  
Academic Research ◽  
Business Strategies ◽  
Knowledge Based Systems ◽  
Academic Literature ◽  
Knowledge Based ◽  
New Research

Knowledge management strategies and implementation of knowledge-based systems have gained importance over the last decade. However, many organizations are not able to develop “winning” knowledge-based strategies and others waste signifi- cant monies when the knowledge-based systems they invest in fail to produce the desired results. To address the challenges faced by these organizations, a recently developed framework for strategic dilemmas was proposed by Russ, Jones, and Fineman (2006) to aid in the development of knowledge-based (KB) strategies. The framework (C3EEP) identifies six dilemmas that organizations should balance when considering their knowledge management and business strategies. Examples of such dilemmas include the balance between concealment (secrecy) vs. transparency, complementary vs. destroying, and the balance between exploitation and exploration. The framework compliments the six stages in the life cycle of KB systems (KBS) as identified by the academic literature that discusses the development and implementation of KBS from the information systems (IS) perspective (e.g., Lytras, Pouloudi, & Poulymenakou, 2002; Nissen, Kamel, & Sengupta, 2000). This interaction/ linkage between KB strategies and systems is crucial for the success of both. Academic research supports the complex relationship between the two. However, there is no conclusive formula for managing this relationship to achieve success. The purpose of this study will be to identify crossovers between the two streams (strategy and systems) of research by using a systematic literature review. For example, is the academic literature focusing mostly on the learning aspect (late stage in the life cycle) of the exploration strategy while largely ignoring the discussion about attracting the appropriate knowledge (early stage in the life cycle) for this kind of strategy? Or does the academic literature focus on populating a KBS with appropriate complementary knowledge while largely ignoring the dynamics of the transfer of destroying knowledge (learning aspect)? The authors hope to accomplish three goals in this study: (1) to continue the validation of the two (C3EEP and KBS life cycle) frameworks; (2) to identify new research opportunities; and (3) to focus managerial attention on areas of importance in KB strategies and systems that lack depth of academic discussion.

Evaluation of workbenches which support the CommonKADS methodology

1995 ◽  
Vol 10 (3) ◽  
pp. 269-300 ◽  
Author(s):  
John K. C. Kingston ◽  
Jim G. Doheny ◽  
Ian M. Filby
Keyword(s):  
Knowledge Engineering ◽  
Good Knowledge ◽  
Knowledge Based Systems ◽  
Considerable Effort ◽  
Case Tools ◽  
Knowledge Based ◽  
Specific Support ◽  
Modelling Techniques ◽  
Software Engineers ◽  
Automated Support

AbstractThe KADS methodology and its successor, CommonKADS, have gained a reputation for being useful approaches to building knowledge-based systems in a manner which is both systematic and well documented. However, these methods require considerable effort to use them completely. It has been suggested that automated support for KADS or CommonKADS users, in the form of “knowledge engineering workbenches”, could be very useful. These tools would provide computerised assistance to knowledge engineers in organising and representing knowledge, in a similar fashion to the support which CASE tools provide for software engineers. To provide support for KADS or CommonKADS, the workbenches should provide specific support for the modelling techniques recommended by these methods, which are very detailed in the representation and analysis stages of knowledge engineering. A good knowledge engineering workbench should also be easy to use, should be robust and reliable, and should generate output in a presentable format.This paper reports on an evaluation of two commercially available workbenches for supporting the KADS approach: KADS Tool from ILOG and Open KADS Tool from Bull. This evaluation was carried out by AIAI as part of the CATALYST project, funded by the European Community's ESSI programme, which aimed to introduce CommonKADS to two technology-oriented companies. Information is also presented on two other workbenches: the CommonKADS workbench (which will soon become commercially available) and the VITAL workbench. The results show various strengths and weaknesses in each tool.

TRENDS IN LIFE-CYCLE MODELS FOR SE AND KE: PROPOSAL FOR A SPIRAL-CONICAL LIFE-CYCLE APPROACH

1995 ◽  
Vol 05 (03) ◽  
pp. 445-465 ◽  
Author(s):  
F. ALONSO ◽  
N. JURISTO ◽  
J. PAZOS
Keyword(s):  
Life Cycle ◽  
Software Engineering ◽  
Software Development ◽  
21St Century ◽  
Knowledge Engineering ◽  
Life Cycle Approach ◽  
Life Cycle Model ◽  
Cycle Model ◽  
Knowledge Based ◽  
Technological Tools

The ten-year gap between the emergence of Software Engineering (SE) and Knowledge Engineering (KE) has led to the two disciplines developing along different methodological lines. In this paper, we point out that, after having passed through a period during which they ignored each other, followed by a competitive phase, the two disciplines have now reached a meeting point. We see the need for a life-cycle model for systems that integrate traditional and knowledge-based software. Besides, software development in the 21st century will entail open requirements and technological tools that will evolve during the life-cycle. Finally, the paper discusses a proposal for a conical-type spiral life-cycle model that seeks to meet all those needs.

scholarly journals A comparison of languages which operationalize and formalize KADS models of expertise

1994 ◽  
Vol 9 (2) ◽  
pp. 105-146 ◽  
Author(s):  
Dieter Fensel ◽  
Frank van Harmelen
Keyword(s):  
Problem Solving ◽  
Rapid Prototyping ◽  
Conceptual Model ◽  
Model Evaluation ◽  
Conceptual Models ◽  
Knowledge Engineering ◽  
Future Research ◽  
Knowledge Based Systems ◽  
Research Issues ◽  
Knowledge Based

AbstractIn the field of knowledge engineering, dissatisfaction with therapid-prototypingapproach has led to a number of more principled methodologies for the contruction of knowledge-based systems. Instead of immediately implementing the gathered and interpreted knowledge in a given implementation formalism according to the rapid-prototyping approach, many such methodologies centre around the notion of a conceptual model: an abstract, implementation independent description of the relevant problem solving expertise. A conceptual model should describe the task which is solved by the system and the knowledge which is required by it. Although such conceptual models more precisely, and operationally as a means for model evaluation. In this paper, we study a number of such formal and operational languages for specifying conceptual models. To enable a meaningful comparison of such languages, we focus on languages which are all aimed at the same underlying conceptual model, namely that from the KADS method for building KBS. We describe eight formal languages for KADS models of expertise, and compare these languages with respect to their modelling primitives, their semantics, their implementations and their applications, Future research issues in the area of formal and operational specification languages for KBS are identified as the result of studying these languages. The paper also contains an extensive bibliography of research in this area.

The Application of Basic Principles of Knowledge Engineering in Knowledge Management

2010 ◽  
Vol 108-111 ◽  
pp. 123-128
Author(s):  
Ting Zeng
Keyword(s):  
Knowledge Management ◽  
Knowledge Engineering ◽  
Knowledge Based Systems ◽  
Uncertain Process ◽  
Basic Principles ◽  
Knowledge Based ◽  
Engineering Solution

Knowledge management and knowledge engineering is two important concepts, in recent years. Knowledge Engineering is the engineering solution of the system, emphasizing the process of the acquisition of knowledge and knowledge on behalf of knowledge-based systems in the uncertain process requirements. The purpose of this paper is to discuss how to use the basic principles of knowledge engineering in order to promote knowledge management.

scholarly journals ISSUES WITH META-KNOWLEDGE

2000 ◽  
Vol 10 (04) ◽  
pp. 549-555 ◽  
Author(s):  
TIM MENZIES ◽  
KLAUS-DIETER ALTHOFF ◽  
YANNIS KALFOGLOU ◽  
ENRICO MOTTA
Keyword(s):  
Problem Solving ◽  
Knowledge Engineering ◽  
Knowledge Based Systems ◽  
Reusable Components ◽  
Knowledge Based ◽  
Lively Debate

At the SEKE'99 conference, knowledge engineering researchers held a panel on the merits of meta-knowledge (i.e. problem solving methods and ontologies) for the development of knowledge-based systems. The original panel was framed as a debate on the merits of meta-knowledge for knowledge maintenance [21]. However, the debate quickly expanded. In the end, we were really discussing the merits of different technologies for the specification of reusable components for KBS. In this brief article we record some of the lively debate from that panel and the email exchanges it generated.

Prolonging the Aging of Software Systems

2011 ◽  
pp. 3152-3160
Author(s):  
Constantinos Constantinides ◽  
Venera Arnaoudova
Keyword(s):  
Life Cycle ◽  
Support System ◽  
Maintenance Phase ◽  
Software Systems ◽  
Legacy Systems ◽  
Driving Factor ◽  
Software Life Cycle ◽  
System Complexity ◽  
Software Aging ◽  
Programming Paradigms

The evolution of programming paradigms and languages allows us to manage the increasing complexity of systems. Furthermore, we have introduced (and demanded) increasingly complex requirements because various paradigms provide mechanisms to support their implementation. As a result, complex requirements constitute a driving factor for the evolution of languages which in turn can support system complexity. In this circular relationship, the maintenance phase of the software life cycle becomes increasingly important and factors which affect maintenance become vital. In this chapter we review the notions of software aging and discuss activities undertaken during maintenance. We also discuss challenges and trends for the development of well-maintained systems as well as for aiding in the maintenance of legacy systems.

Knowledge engineering in the communication of Information for safety critical systems

1997 ◽  
Vol 12 (3) ◽  
pp. 249-270 ◽  
Author(s):  
CORIN A. GURR
Keyword(s):  
Knowledge Engineering ◽  
Distributed Teams ◽  
Primary Role ◽  
Knowledge Based Systems ◽  
Critical Systems ◽  
Human Communication ◽  
Critical System ◽  
Safety Critical ◽  
Knowledge Based ◽  
Safety Critical Systems

The design and assessment of safety critical systems often involves broad and distributed teams of designers, suppliers and analysts who represent diverse areas of expertise and motivations. Accurate and effective communication between these groups is therefore an issue of primary importance. The formalisation of specifications and arguments of safety can be of significant benefit in ensuring the consistency of evidence in such cases, when it must be presented across many domains. However, a formal description of a safety critical system may be unconvincing unless it is presented in a form which is (or forms which are) accessible to the broad range of users and assessors of safety cases. This raises issues of human communication which include the tailoring of information to particular communicative tasks; the efficacy of differing media for communication and the cognitive impact that such differing media have. This paper draws together work in fields of knowledge engineering, knowledge based systems and human communication in an effort to address, from a sound theoretical basis, these and other communication issues raised by the use of formal descriptions in safety critical systems. Further, this paper argues that a primary role for knowledge based systems techniques in safety critical systems is in supporting the communication of information.

Life cycles in software and knowledge engineering: a comparative review

1989 ◽  
Vol 4 (3) ◽  
pp. 189-204 ◽  
Author(s):  
Michael Wilson ◽  
David Duce ◽  
Dan Simpson
Keyword(s):  
Life Cycle ◽  
Software Engineering ◽  
Program Verification ◽  
Knowledge Engineering ◽  
System Development ◽  
Life Cycles ◽  
Development Projects ◽  
Comparative Review ◽  
Life Cycle Models ◽  
System Life

AbstractProgress 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.

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