A decision table is a good way to handle different combination inputs with their associated outputs, It’s also called cause-effect table. The reason for this is that there is an associated logic diagramming technique called ’cause-effect graphing’ which was sometimes used to help derive the decision table.
“Decision table testing is black box test design technique to determine the test scenarios for complex business logic“.
This technique provides a systematic way to deal with complex business logics, which is helpful to understand the application.
Decision tables are the test design technique as it helps testers to explore the effects of combinations of different inputs.
For Example :
An evaluation program determines if a candidate passed an exam, based on the number of correct answers given, if correct answers count 26 or more, from a total of 40, then the candidate passed the exam, else the candidates failed the test. The decision table will have the following structure:
The coverage standard commonly used with decision table testing is to have at least one test per column on the table, which typically involves covering all combinations of triggering conditions.
In reality, the number of conditions and actions can be quite large, but usually, the number of combinations producing specific actions is relatively small.
For this reason, we do not enter every possible combination of conditions into our decision table, but restrict it to those combinations that correspond to business rules – this is called a limited entry decision table to distinguish it from a decision table with all combinations of inputs identified.