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Sharing architecture knowledge through models: quality and cost

Published online by Cambridge University Press:  01 September 2009

Peng Liang ,
Anton Jansen  and
Paris Avgeriou
Peng Liang
Affiliation:
Department of Mathematics and Computing Science, University of Groningen, 9700 AK, Groningen, The Netherlands; e-mail: liangp@cs.rug.nl, anton@cs.rug.nl, paris@cs.rug.nl
Anton Jansen
Affiliation:
Department of Mathematics and Computing Science, University of Groningen, 9700 AK, Groningen, The Netherlands; e-mail: liangp@cs.rug.nl, anton@cs.rug.nl, paris@cs.rug.nl
Paris Avgeriou
Affiliation:
Department of Mathematics and Computing Science, University of Groningen, 9700 AK, Groningen, The Netherlands; e-mail: liangp@cs.rug.nl, anton@cs.rug.nl, paris@cs.rug.nl
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Abstract

In the field of software architecture, there has been a paradigm shift from describing structural information, such as components and connectors, to documenting architectural knowledge (AK), such as design decisions and rationale. To this end, a series of industrial and academic domain models have been proposed for defining the concepts and their relationships in the field of AK. To a large extent the merit of this new paradigm is to share and reuse AK across organizations, especially in geographically distributed settings. However, the employment of different AK domain models by different parties makes effective AK sharing challenging, as it needs to be mapped from one domain model to another. In this paper, we investigate two different approaches for sharing AK, based on either direct or indirect mapping between different AK domain models. We compare the cost and quality of these two approaches, with respect to the processing of large amounts of AK instances. To predict the quality and costs of this processing in advance, a prediction model is proposed and validated with a concrete AK sharing case. Based on the comparison results, stakeholders involved with AK sharing can select an appropriate approach by trading off quality and cost in their own context.

Type
Original Article
Information
The Knowledge Engineering Review , Volume 24 , Special Issue 3: Software and system engineering – part 2 , September 2009 , pp. 225 - 244
Copyright
Copyright © Cambridge University Press 2009

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