The parameter dependencies can be analyzed by making
use of the parameter analysis (see Fig. 6). First, the user
selects the module and the input parameter that has to be
analyzed more detailed. Second, the user triggers the analysis.
The server-side evaluation uses a breadth-first search
algorithm to identify parameters that are affected when the
given input parameter is changed during the planning process.
In each step, the algorithm uses the provided and derived
parameter relations for the identification of changed output
parameters. In the first cycle, these parameters are used to
identify modules whose input parameters are changed. They
define the first set of parameters that is further evaluated in
the next cycle. Each such result set is pruned by parameters
that have been evaluated in a previous cycle. Such a pruned
set defines the next set of parameters that is evaluated. The
evaluation process is stopped when no more changed
parameters can be identified. As the set of input parameters is
limited and within each cycle, at least one parameter is
removed from this set, the algorithm terminates.
The evaluation result is visualized in the parameter
analysis view (see Fig. 7). The view shows the changed input
parameters of each module, whereby the level of dependence
gets lower from left to right meaning that the directly affected
input parameters are shown at the left-most position.
Furthermore, the user can highlight the interrelation between
the parameters (as shown in the figure).