Behavioral control flow testing is considered as a fundamental model of black box testing. It is the basis for all the other testing methods.
Test design begins with the creation of a behavioral control flow graph model based on documented requirements, such as a specification. A list representation is usually more convenient than graph drawings, but small graphs help to design the model.
Compound predicates in the model should be eliminated or replaced, for example, by equivalent graphs, so as not to hide the real complexity. Instead of a graph, when modeling compound predicates consisting of more than three components, use a truth table.
Split your model into segments that start and end with a single node, and mark out the cross-correlation of predicates in all segments. Build your test paths by combining paths in segments and excluding impassable paths. Use contradictions between predicates to delete individual combinations. It is unlikely that this technique will lead to impassable paths that will not be possible to activate.
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Choose a sufficient number of paths through the model to ensure complete coverage of the links. Do not worry if there are too many tests. Start by choosing the obvious paths that are directly relevant to the requirements, and see if you can get coverage in this way. Perhaps you will not get the most effective tests, but this is a politically correct decision. Expand a set of these tests, considering as many paths as you need to achieve coverage of the relations.
Activate the selected paths by interpreting the predicates along the path in terms of the input quantities. Interpreted predicates give a set of conditions or equations (in fact, inequalities), so that any solution of this set of inequalities will be a condition of passage but of the chosen path. If the activation is not obvious, then before you spend a lot of time solving equations, check to see if there are any errors in the specification or model. If the conditions are still complex, consider using a commercial program designed to solve inequalities for activation, such as LOTUS 1-2-3. Algebraic package can help with the interpretation of predicates.
Do not forget about the possibility of accidental correctness, and cooperate with programmers to obtain intermediate numerical deductions, which are necessary to verify the path. Give the expressions with predicates a high priority, but do not insist on more than one value for each link in the graph.
Think about programming your model using a real programming language, use the programmed model when designing tests.