Lecture Notes in Computer Science 3472

fitness
13 Real-Time and Hybrid Systems Testing 383
y
fitness
x x
(a) unimodal function (b) multimodal function
Fig. 13.15. Examples of fitness functions with different difficulty
the population for a new cycle of the evolutionary algorithm. This proceeding is
explained in more detail by Goldberg [Gol89].
Initial Population
Insert new
Population
Fitness
Evaluation
Generation by Variation
Exit
Test
Selection
Final Solution
Fig. 13.16. Operational cycle of evolutionary algorithms
With respect to testing, the test case generator must be able to derive test
cases. Furthermore, it has to be able to evaluate the fitness of each individual
and to perform exit tests. This may require to collect and merge values of several
observations into one fitness value.
Testing the Worst-Case Execution Time: To demonstrate the application of
evolutionary testing, we describe its application to measurement-based timing
analysis of real-time systems. Testing real-time systems means ensuring the correctness
in the value and time domain. In contrast to other methods that test
both properties in combination, the aim of the test method described in this section
[PN98, Weg01, AHP99, GW98] is testing only the time domain. The value
domain can be tested separately by other test methods. The property p1 of the
end state of a real-time system we are interested in is the tuple 〈BCET, WCET〉
where the BCET means the best-case execution time and WCET the
worst-case execution time. In the following we will just describe test case
generation for WCET as BCET can be handled similar. The application of evo-
y