Equivalence partitioning (also called Equivalence Class
Partitioning or ECP is a software testing technique that divides the input
data of a software unit into partitions of data from which test cases can be
derived. In principle, test cases are designed to cover each partition at least
once. This technique tries to define test cases that uncover classes of errors,
thereby reducing the total number of test cases that must be developed.
Equivalence partitioning is typically applied to the inputs
of a tested component, but may be applied to the outputs in rare cases. The
equivalence partitions are usually derived from the requirements specification
for input attributes that influence the processing of the test object.
In this method the
input domain data is divided into different equivalence data classes. This
method is typically used to reduce the total number of test cases
to a finite set of testable test cases, still covering maximum requirements.
In short it is the
process of taking all possible test cases and placing them into classes. One
test value is picked from each class while testing.
E.g.: If you are testing
for an input box accepting numbers from 1 to 1000 then there is no use in
writing thousand test cases for all 1000 valid input numbers plus other test
cases for invalid data.
Using
equivalence partitioning method above test cases can be divided into three sets
of input data called as classes. Each test case is a representative of
respective class.
So
in above example we can divide our test cases into three equivalence classes of
some valid and invalid inputs.
Test cases for
input box accepting numbers between 1 and 1000 using Equivalence Partitioning:
1) One input data class with all valid inputs. Pick a single value from range 1 to 1000 as a valid test case. If you select other values between 1 and 1000 then result is going to be same. So one test case for valid input data should be sufficient.
1) One input data class with all valid inputs. Pick a single value from range 1 to 1000 as a valid test case. If you select other values between 1 and 1000 then result is going to be same. So one test case for valid input data should be sufficient.
2) Input data class
with all values below lower limit. I.e. any value below 1, as a invalid input
data test case.
3) Input data with any
value greater than 1000 to represent third invalid input class.
So
using equivalence partitioning you have categorized all possible test cases
into three classes. Test cases with other values from any class should give you
the same result.
We
have selected one representative from every input class to design our test
cases. Test case values are selected in such a way that largest number of
attributes of equivalence class can be exercised.
Equivalence
partitioning uses fewest test cases to cover maximum requirements.
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Er Ratnesh Porwal
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