Lecture Notes in Computer Science 3472

15 Case Studies 451
reached, the test is output. If the randomly chosen coverage task cannot reach a
final state then no test is generated. GOTCHA outputs abstract test cases, each
consists of a sequence of states.
Abstract Test Case Generation with Constraint Logic Programming In the case
study of model-based test case generation for smart cards described in [PPS + 03],
Constraint Logic Programming (CLP) was used to compute the set of all possible
execution traces of finite length. First, the test model developed in AutoFocus is
translated into a CLP program. Second, the test specification is also translated
into the CLP language and added to the CLP program of the model. Finally,
a logic programming engine solves the program using depth-first search with
backtracking and computes the set of all possible execution traces of the model
up to a certain length. These traces are the abstract test cases. More details
on the use of CLP for test case generation in this case study [PPS + 03] were
presented in Sec. 12.3.2. More details on AutoFocus are available in Sec. 14.2.4.
Abstract Test Case Generation Using Genesys In [FKL99], Genesys was used to
generate an architecture validation suite for PowerPC architecture to be used
for testing PowerPC implementations. Genesys is specifically designed for testing
processor architectures.
The inputs to Genesys are a test model and a behavioral simulator for the
SUT and a test specification. The test specification allows the incorporation of
complex heuristic testing knowledge in the form of generation and validation
functions coded in C by test engineers. These functions serve many purposes,
e.g., they enable adjusting the probability distribution of the targeted test space.
As a simple example, the result of zero for an ADD instruction is typically of
special importance while its relative probability to occur randomly is practically
inexistent. A generation and validation function can be implemented to inform
the test generator that the result of zero is important, and should thus be generated
with a reasonable probability. More generally, these functions can be used
to give adequate weights to corner cases which otherwise would be occurring
with negligible probability.
Genesys directly generates executable test cases by combining abstract test
generation and concretization. Genesys outputs a test file, which consists of a
sequence of instructions starting from a given initial state, and a section of expected
results describing the expected values of the various processor resources.
Test case generation is done using depth-first search with backtracking and
checking against validation functions. First, the test model has the PowerPC
instructions modeled as trees at the semantic level of the processor architecture.
An instruction tree includes the instruction’s format and a semantic procedure
at the root, operands and sub-operands as internal nodes and length, address
and data types of each operand as leaves of the intermediate node representing
this operand. Second, generation of an instruction instance is done by traversing
the instruction tree in a depth-first order. Traversing a node involves invoking
all the generation and validation functions associated with it.