Answer Posted / neellohit

Boundary value analysis:
It’s widely recognized that input values at the extreme
ends of input domain cause more errors in system. More
application errors occur at the boundaries of input domain.
‘Boundary value analysis’ testing technique is used to
identify errors at boundaries rather than finding those
exist in center of input domain.
Boundary value analysis is a next part of Equivalence
partitioning for designing test cases where test cases are
selected at the edges of the equivalence classes.

Test cases for input box accepting numbers between 1 and
1000 using Boundary value analysis:
1) Test cases with test data exactly as the input
boundaries of input domain i.e. values 1 and 1000 in our
case.

2) Test data with values just below the extreme edges of
input domains i.e. values 0 and 999.

3) Test data with values just above the extreme edges of
input domain i.e. values 2 and 1001.
Boundary value analysis is often called as a part of stress
and negative testing.

Note: There is no hard-and-fast rule to test only one value
from each equivalence class you created for input domains.
You can select multiple valid and invalid values from each
equivalence class according to your needs and previous
judgments.
E.g. if you divided 1 to 1000 input values in valid data
equivalence class, then you can select test case values
like: 1, 11, 100, 950 etc. Same case for other test cases
having invalid data classes.


Equivalence Partitioning:
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.

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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