Lecture Notes in Computer Science 3472

14 Tools for Test Case Generation 397
constraints to guide the test sequence generation. The environment description
computes a predicate which indicates whether the test sequence is relevant or
not. The test sequence generator inverts this predicate, i.e., it computes the set
of inputs for the SUT which satisfy the environment description. In every step,
the oracle is provided with the last input/output pair of the SUT to compute a
pass or fail verdict for the sequence tested so far.
Random Testing The behavior of the environment is restricted by a set of
constraints which must be satisfied unconditionally by the whole test sequence.
For example, an environment description for a telephone-system will allow a
test sequence such as oni, diali , offi, oni, diali , offi ...,whereoni is the event of
picking up the phone i, diali is the event of dialing a number, and offi is the
event of hanging up. A sequence starting with oni, oni,... would not be allowed
by the environment description, since it is physically impossible to pick up the
same phone twice.
Random testing is the most basic mode of operation, where Lutess generates
test sequences which respect the environment constraints based on a uniform
distribution.
Operational Profile-Based Testing Although random test sequences are
possible interactions between the SUT and the environment, the arising test sequences
lack realism, i.e., most sequences which occur in the target environment
are not generated since they unlikely happen at random. To obtain more realistic
test sequences, Lutess allows to add operational profiles to the environment
description. An operational profile CP(e) = 〈(p1, c1),...,(pn, cn)〉 associates
conditional probabilities (pi , ci) with an input e. If the condition ci evaluates to
true, then the input e of the SUT will be set to true with probability pi in the
next step. Therefore, operational profiles do not rule out unexpected cases, but
they are emphasizing more common sequences of events.
Property-Guided Testing Next, Lutess provides property guided testing. In
this case, Lutess will try to generate test sequences which test safety properties.
For example, if a property of the form a ⇒ b should be an invariance, then
Lutess will set a to true if such a setting is consistent with the basic environment
constraints. However, Lutess is only able to provide this feature for expressions
that do not involve references into the past. For example pre(a) ⇒ b cannot
be used for property guided testing, since pre(a) is refers to the value of the
expression a in the last step.
Pattern-Based Testing Finally, Lutess provides pattern-based testing. A pattern
BP =[true]cond0[inter1]cond1 ...[intern]condn is a sequence of conditions
cond0,...,
condn with associated interval conditions inter1,...,intern. Lutess probabilistically
generates test sequences which match the pattern, i.e., if the environment