![](bg6.png)
Figure 6: Sub-Usage scenario for ESP push button.
Table 2: Computations for Case Study ESP Switch with
Time Augmented MCUM.
State Mean Expected number Expected
ID residence time of visits residence time
S9998 0.00000 1.00000 0.00000
S1 9.00000 1.00000 9.00000
S234 10.0000 0.37538 3.75380
S4 0.01000 2.00000 0.02000
S9999 0.00000 1.00000 0.00000
Now have a look at the computations for a Time
Augmented MCUM, depicted in Table 2. All mea-
sures for the time are given in seconds. Now we can
see that for the given usage profile we would expect
to be in state S1 9 seconds in a typical test case and
3.75 seconds in state S234. Next we see that states
S9998, S9999 and S4 have less impact on the testing
time, though they are visited once or twice in each
test case. This information is valuable for the person
engaged to decide when to test and what to test and
to assess, if the usage profile is suitable to derive test
cases that meet the testing goals within time limits.
6 FUTURE WORK
The future work will focus on computations for the
test planing, integrating coverage aspects, and test
case generation strategies. The elaboration of timing
coverage criteria for functional requirements is neces-
sary. So test case generation strategies are developed
that should optimize the usage of the test benches,
considerung functional-based timing requirements.
7 CONCLUSIONS
In this paper an extension has been presented and
evaluated that integrates usage time in MCUMs. The
case study has been conducted with an example from
the automotive domain. Substantial advantages arised
from the application of our extension, since the inte-
grated time information can be used either for the test
planing or for the test case generation. In the first
case indicators such as test case length are not any
more abstract numbers, but provides the test designer
with information about the expected duration of a test
case. Secondly this information can be used by the
test case generation algorithms for one thing to gen-
erate test cases that are also variant in time and not
only in operations. For another thing test case gener-
ation algorithms can make use of this information to
generate test suites that meet test requirements within
time constraints in an optimal manner. In this way the
whole testing process can be supported by the pre-
sented approach.
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