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2007

Using Bayesian belief networks for change impact analysis in architecture design

8 years 11 months ago
Using Bayesian belief networks for change impact analysis in architecture design
Research into design rationale in the past has focused on argumentation-based design deliberations. These approaches cannot be used to support change impact analysis effectively because the dependency between design elements and decisions are not well represented and cannot be quantified. Without such knowledge, designers and architects cannot easily assess how changing requirements and design decisions may affect the system. In this article, we introduce the Architecture Rationale and Element Linkage (AREL) model to represent the causal relationships between architecture design elements and decisions. We apply Bayesian Belief Networks (BBN) to AREL, to capture the probabilistic causal relationships between design elements and decisions. We employ three different BBN-based reasoning methods to analyse design change impact: predictive reasoning, diagnostic reasoning and combined reasoning. We illustrate the application of the BBN modelling and change impact analysis methods by usin...
Antony Tang, Ann E. Nicholson, Yan Jin, Jun Han
Added 27 Dec 2010
Updated 27 Dec 2010
Type Journal
Year 2007
Where JSS
Authors Antony Tang, Ann E. Nicholson, Yan Jin, Jun Han
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