A Rationale-based Model for Architecture Design Reasoning

10.3. Reasoning about change impact with AREL
Figure 10.8: A Diagnostic Model
C4 2 9 have had their volatility increased. In particular, C6 0 0 depends indirectly on
C4 2 7 and C4 2 4. The volatility of C4 2 7 has increased from 18.8% to 56%. C6 0 0 is
affected by C4 2 7 because the purpose of the alarm service is to notify the error processing
unit that an error has occured. Tracing backwards, this design is in turn caused by
C4 2 4 where asynchronous acknowledgement mechanism has been chosen. The volatility
of C4 2 4 has increased from 18.0% to 35.6%. The increase in the volatility indicates the
level of dependency between the AE node in question and the nodes in which that AE
node depends on.
Out of the eight AE nodes and six AR nodes that are affected by a change in C6 0 0,
only four AE nodes and three AR nodes are ancestor nodes of C6 0 0. They are circled
in Figure 10.8. The rest of the affected nodes are conditionally dependent on C4 2 4 but
C6 0 0 does not depend on them. When evidence is inserted into C6 0 0, the reasoning
process diagnoses the dependency on its ancestor nodes. This chain of reasoning is performed
in a backward direction. Notice that a change of posterior probabilities in C4 2 4
has triggered an update of its dependent nodes (i.e. AR13, AR16 and their descendant
nodes). This mechanism highlight possible changes in these nodes if C4 2 4 is to change.
As such, the ripple effect of architecture changes can be high-lighted through their dependent
relationships. This is an enhancement to the manual traceability methods described
in the last chapter.
Such diagnostic reasoning is useful because, before any changes are introduced to the
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