2.1 Reactis TesterFigure 2 shows that Reactis Tester offers automatic
test generation from Simulink models. The generated test suites provide
comprehensive coverage of different test coverage metrics - including the
Modified Condition/Decision Coverage (MC/DC) test coverage measure
mandated by the US Federal Aviation Administration (FAA) in its DO-178/B
guidelines - while at the same time minimizing redundancy in tests. Each test case
in a test suite consists of a sequence of inputs fed into the model as well as
the responses to those inputs generated by the model. The automatically generated test data may then be used for a variety of
purposes, including the following:
- Implementation conformance.
- The tests may be applied to source-code
implementations of models to ensure conformance with model behavior.
- Model testing and debugging.
- The tests may be run on the models
themselves to detect run-time errors and to study and revise model behavior.
- Reverse engineering of models from source.
- Tests may be generated from
models derived from legacy code in order to check conformance between model and
code.
Reactis Tester enables engineers to maximize the effectiveness of testing while
reducing the time actually spent on testing.
| Figure 2: Reactis Tester automatically generates
comprehensive yet compact test suites. |
The structure of a Tester-generated test is shown in
Figure 3. A test may be viewed as a matrix in which each row
corresponds to either an inport or outport and each column represents a
simulation step. As shown in Figure 4, a test suite consists
of a set of tests. When running a test suite, the model is reset to its initial
state after one test completes and before the next test begins.
| Figure 3: Structure of a Reactis-generated test. |
| Figure 4: Structure of a Reactis-generated test suite. |
Test suites are constructed by simulating a model and recording the input and
output values at each step. The model computes the outputs at each step, but
several approaches are possible for selecting the input values to drive
simulation. The input data could be captured during field testing or constructed
manually by an engineer, but these are expensive tasks. Alternatively, the
inputs could be generated randomly; however, this approach yields tests with
poor coverage. Reactis Tester employs a novel approach called guided simulation to generate
quality input data automatically. The idea behind this approach is to use
algorithms and heuristics to automatically generate inputs that cause coverage
targets (i.e. model elements that the user wants to ensure are executed at least
once) that have not yet been covered to be executed. Reactis currently allows
users to track several different classes of coverage targets (also called
coverage criteria or coverage metrics). Three of the test coverage metrics
supported by Reactis involve only Simulink, three are specific to Stateflow, and
the remaining are generic in the sense that they include targets within the
Simulink, Stateflow, or C code portions of a model. - Simulink-specific:
- Conditional subsystems. Branches of the following
blocks: Dead Zone, Logical Operator, MinMax, Multiport Switch, Relational
Operator, Saturation, Switch. Lookup tables.
- Stateflow-specific:
- States. Condition actions. Transition actions.
- Generic:
- Decisions from logic blocks in Simulink, transition segments in
Stateflow, or in C code a boolean-valued expression used to determine which
execution path to follow. Conditions (the atomic predicates that are the
building blocks of decisions). Modified Condition/Decision Coverage (MC/DC)
targets. Boundary Values of top-level
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