What are equivalence partitioning and decision table testing?

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Equivalence Partitioning and Decision Table Testing are both black-box testing techniques used in software testing to design effective test cases and improve coverage with minimal effort.

Equivalence Partitioning (EP):

Equivalence Partitioning involves dividing input data into partitions or classes where test cases can be derived. The idea is that if one test case from a partition passes, all other values in that partition are assumed to behave the same. These partitions are typically categorized as:

• Valid partitions: Acceptable input values.

• Invalid partitions: Input values that should be rejected.

For example, if a field accepts ages from 18 to 60:

• Valid partition: 18–60

• Invalid partitions: less than 18 and greater than 60

Testing one value from each partition (e.g., 25, 17, 61) is usually enough to validate the behavior.

Decision Table Testing:

Decision Table Testing is used when the system’s behavior is influenced by combinations of inputs or conditions. It represents rules in a tabular format showing all possible conditions and their corresponding actions or outcomes.

Each row defines a condition or an action, and each column represents a rule (combination of conditions). This helps ensure all logical scenarios are considered.

Example: For a loan system with two inputs (income status and credit score), the decision table helps identify which combinations result in loan approval or rejection.

Summary:

• EP simplifies testing by reducing input space.

• Decision Tables ensure comprehensive testing of complex logic.

Both aim to improve efficiency and effectiveness in test design.

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