Cause-effect graphs capture relationships between inputs (causes) and outputs (effects) in black box testing. Causes and effects are represented as nodes in a graph connected by intermediate nodes. An example graphs the causes if the first character is 'A' or 'B' and the second column is a number leading to the effect that the file is updated, or other causes and effects like erroneous characters printing message X12. The methodology involves decomposing the system, identifying causes and effects, establishing the graph of relationships between them, adding constraints, converting the graph to a decision table, and producing a test per line of the simplified table.

1. Cause Effect Graphing Technique

2. Cause-effect graphs in black box
testing
• Captures the relationships between
specific combinations of inputs (causes)
and outputs (effects)
–Deals with specific cases,
–Avoids combinatorial explosion
–Explore combinations of possible inputs
• Causes/effects are represented as nodes
of a cause effect graph
• The graph also includes a number of
intermediate nodes linking causes and
effects

4. Cause effect graph, an example
• File management:
• If the character of the first column is ‘A’ or ‘B’, and the second
column is a number, then the file is considered updated.
• If the first character is erroneous, print message X12
• If the second column is not a number, print message X13
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Proposed by G. J. Mayers

5. Cause effect graph: Decision Table
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Proposed by G. J. Mayers

6. Cause effect graph: Methodology
Test technique based on cause effect graph consists in the following steps:
1.Decompose the unit to be tested, If it has many functionalities
2.Identify the causes
3.Identify the effects
4.Establish the graph of relations between causes and effects
5.Complete the graph by adding constraints between causes and effects
6.Convert the graph to a decision table
7.Produce a test per line after simplification of the table
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Proposed by G. J. Mayers