Equivalence Partitioning and Boundary Value Analysis for Designing Test Cases

Equivalence Partitioning and Boundary Value Analysis are test case design strategies in black-box testing. As with any mildly complex piece of software, it is impossible to test it exhaustively, so we must ensure that the tests we do perform are as efficient and effective as possible - the combination of Equivalence Partitioning and Boundary Value Analysis makes this possible. Let's see them in action with an example, take this validation rule around ID numbers:

An ID number must be between 12 and 24 characters long, inclusive.

First, we will use Equivalence Partitioning, then Boundary Value Analysis to generate our validation test cases.

Equivalence Partitioning

Equivalence Partitioning is a software testing technique that divides input data into logical groups or partitions where the system is expected to behave similarly. Instead of testing every possible input, you test one representative value from each group - because if one passes, the rest are likely to pass too.

Why it's useful:

1. Reduces test cases while maintaining coverage.
2. Helps identify missing validation logic.

From the above rule, we have three logical groups:

Group	Range
Valid	12...24
Invalid (Too Low)	< 12
Invalid (Too High)	> 24

Boundary Value Analysis

Boundary Value Analysis is a software testing technique that focuses on the edges or boundaries of input domains where errors are most likely to occur. Instead of testing every possible input, Boundary Value Analysis targets the values just inside, on, and just outside the boundaries - because that's where systems often break.

Why it's useful:

1. Reveals off-by-one errors.
2. Exposes incorrect assumptions about inclusive/exclusive ranges.

Typically, Boundary Value Analysis takes two forms:

1. Two-point - take the valid boundary as the first point and just outside of that valid boundary as the second point
2. Three-point - take just inside the valid boundary as the first point, the valid boundary as the second point and just outside of that valid boundary as the third point

Whether you choose the two-point or three-point approach depends on your context - balance thoroughness against the cost of additional test cases.

Here I'm going to use the three-point form as it also shows the two-point form as well.

For the above rule, after Equivalence Partitioning was applied, we identified three logical groups; the boundaries of each group are:

Boundaries	Value
Just outside valid minimum	11
Valid minimum	12
Just inside valid minimum	13
Just inside valid maximum	23
Valid maximum	24
Just outside valid maximum	25

If Equivalence Partitioning had shown more than one valid group, this table would be larger, as the boundary of each group would need to be shown.

As each boundary generates 3 boundary checks, we have to write 6 test cases to cover the above validation rule fully.

Working as a team

Equivalence Partitioning and Boundary Value Analysis are most potent when used together. Equivalence Partitioning identifies the logical groups of input data, while Boundary Value Analysis determines exactly which values to test within and around those groups.

This systematic approach transforms test case design from guesswork into a methodical process. Instead of wondering "what should I test?", you have a clear framework: partition your inputs logically, then focus your testing effort where bugs are most likely to hide - at the boundaries.