Testing of controllers with a large number of
inputs and outputs suffers from the curse of dimensionality
in terms of the combinatorial explosion of possible input
combinations. In particular for conformance testing, this results
in unbearable large numbers of test cases. To mitigate
this problem, the plant feature approach has been proposed,
which guarantees full coverage of the nominal behavior of the
controller. This nominal behavior corresponds to the reachable
state space when combining in a closed-loop the controller with
its fault-free plant. Plant features are identified as intuitive
basic knowledge about a system based on its physical behavior.
Considering such physical limitations allows to reduce the scope
of testing to the actual relevant behavior.
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Testing of controllers with a large number of
inputs and outputs suffers from the curse of dimensionality
in terms of the combinatorial explosion of possible input
combinations. In particular for conformance testing, this results
in unbearable large numbers of test cases. To mitigate
this problem, the plant feature approach has been proposed,
which guarantees full coverage of the nominal behavior of the
controller. This nominal behavior corresponds to the reachable
state space when combi...
»