Testing School---Cause-Effect Graphing Techniques

Cause-Effect Graphing Techniques

Cause-effect graphing is a technique that provides a concise representation of logical conditions and corresponding actions.

It is a test case design technique that is performed once requirements have been reviewed for ambiguity, followed by a review for content.

Requirements are reviewed for content to insure that they are correct and complete. The Cause-Effect Graphing technique derives the minimum number of test cases to cover 100% of the functional requirements to improve the quality of test coverage.

There are four steps:
1.Causes (input conditions) and effects (actions) are listed for a module and an identifier is assigned to each.
2.A cause-effect graph is developed.
3.The graph is converted to a decision table.
4.Decision table rules are converted to test cases.
The Cause-Effect Graphing technique was invented by Bill Elmendorf of IBM in 1973. Instead of the test case designer trying to manually determine the right set of test cases, he/she models the problem using a cause-effect graph, and the software that supports the technique, BenderRBT, calculates the right set of test cases to cover 100% of the functionality. The cause-effect graphing technique uses the same algorithms that are used in hardware logic circuit testing. Test case design in hardware insures virtually defect free hardware.

Cause-Effect Graphing also has the ability to detect defects that cancel each other out, and the ability to detect defects hidden by other things going right. These are advanced topics that won’t be discussed in this article.

The starting point for the Cause-Effect Graph is the requirements document. The requirements describe “what” the system is intended to do. The requirements can describe real time systems, events, data driven systems, state transition diagrams, object oriented systems, graphical user interface standards, etc. Any type of logic can be modeled using a Cause-Effect diagram. Each cause (or input) in the requirements is expressed in the cause-effect graph as a condition, which is either true or false. Each effect (or output) is expressed as a condition, which is either true or false