What is the difference between equivalence partitioning and boundary value analysis?
An example of an AI chatbot conversation about testing techniques in software quality assurance.
What is the difference between equivalence partitioning and boundary value analysis?
Equivalence partitioning divides input data into valid and invalid partitions, while boundary value analysis focuses on values at the edges of these partitions.
Can you give me an example of each technique?
Sure! For equivalence partitioning, if a field accepts ages 18-65, valid partitions could be 18-65 and invalid could be <18 or >65. For boundary value analysis, you'd test the values 17, 18, 65, and 66.
When should I use each technique?
Use equivalence partitioning when you want to reduce the number of test cases by grouping inputs, and boundary value analysis when you want to ensure edge cases are tested.
Are there any limitations to these techniques?
Yes, equivalence partitioning may miss errors within partitions, and boundary value analysis might not cover all scenarios outside the boundaries.
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