Lecture Notes in Computer Science 3472

12 Technology of Test-Case Generation 349
tests, i.e. checking whether the transitions between the operations in the test
sequence are possible. If they are not, then that sequence of operations should
not be applicable to the implementation - this type of tests are negative but
also relevant to verify the correctness of the SUT.
The next step in the approach is to define a set of hypotheses that will direct
the symbolic execution of the axiomatized prototype. Unlike other frameworks
described in this section, this one relies on human intuition during test case
selection. Despite the fact that some of the possible automation during this step
is lost, the high-level language used to describe hypotheses about interesting test
cases provides a basis to generate tests which are semantically meaningful.
The test engineer can express two types of hypotheses concerning the tests
that will be generated:
• Regularity hypotheses: this type of hypotheses stipulates that if a test containing
a variable v if valid for a subset of v satisfying an arbitrary complexity
criteria, then it is valid for all of v’s domain of greater complexity. The
notion of variable in a test is very generic, including not only input variables
but also constraints on the shape of the sequence of operations that form the
test. This is however a complex topic and the reader is referred to [Per98]
for details;
• Uniformity hypotheses: the uniformity hypotheses state that if a test containing
a variable v is valid for one value of v, then it is valid for all of v’s
domain.
After introduction in the system of hypotheses by the test engineer, the prolog
adapted engine (the resolution is not pure SLD 7 ) symbolically executes the
uninstantiated tests against the axiomatic definition of the application. The idea
behind the approach is to extract from path condition of a given test the constraints
on the variables corresponding to the input values of the operations
present in that test. Given this knowledge it becomes possible to calculate the
subdomains of the uninstantiated input variables and apply uniformity hypotheses
in a way that the operation behaviors described in the specification are taken
into consideration. This activity is somehow equivalent to what is performed by
Legeard and Peureaux in [LP01] while calculating the P-Domains.
Again, as with the previously described approaches, both theorem proving
and symbolic execution techniques are used in this test case generation framework.
Code-Based Test Case Generation In the last example of this section we
will be describing a framework by Khurshid et al. [KPV03] that generates test
7
SLD is the standard mechanism used in logic programming languages in order to
compute goal solutions