What Is Cause & Effect Graph ?

 A Cause and Effect Graph is a graphical representation used in black box testing to identify and organize the input conditions and their corresponding outputs for a system. It helps testers generate test cases based on different combinations of input conditions. Here's an elaborative explanation of the Cause and Effect Graph:

1. Purpose of Cause and Effect Graph:

• Identification of Inputs and Outputs: It helps identify the input conditions that affect the system and the corresponding outputs that result from these conditions.
• Test Case Generation: It facilitates the creation of test cases that cover different combinations of input conditions.

2. Components of Cause and Effect Graph:

• Inputs (Causes): These are the various factors or conditions that can influence the behavior of the system.
• Outputs (Effects): These represent the expected results or behaviors of the system based on the input conditions.
• Rules (Logic): The rules define the relationships between the inputs and outputs, indicating how changes in inputs affect the outputs.

3. Steps to Create a Cause and Effect Graph:

• Identify Inputs and Outputs:

  • Inputs: Determine the variables that can affect the system.
  • Outputs: Define the expected results or system behavior based on different input conditions.

• Create a Graph:

  • Represent inputs as nodes (circles) and outputs as nodes or rectangles.
  • Draw arrows (edges) to connect inputs to outputs based on the rules or logic that govern their relationships.

• Add Logic Rules:

  • Specify the rules that dictate how the inputs interact to produce the desired outputs.
  • Use conditions such as AND, OR, or exclusive relationships to model the system behavior accurately.

4. Example:

• Inputs:

  • Temperature
  • Humidity
  • Wind speed

• Outputs:

  • Rain
  • Snow
  • Clear sky

• Rules:

  • IF (High Temperature AND High Humidity) THEN Rain
  • IF (Low Temperature AND High Wind Speed) THEN Snow
  • IF (Moderate Temperature AND Low Humidity) THEN Clear Sky

5. Test Case Generation:

• Based on the Cause and Effect Graph, create test cases covering various combinations of input conditions.
• Ensure that each unique path in the graph is covered to validate different scenarios.

6. Execution and Analysis:

• Execute the generated test cases and observe the actual system behavior.
• Compare the observed outputs with the expected results defined in the Cause and Effect Graph.

By following these steps, testers can systematically generate test cases that provide thorough coverage of the input conditions, helping ensure the reliability and robustness of the system under test.