Suitable Test Data

Suitable Test Data

Suitable Test Data

What is suitable test data?

• Suitable test data is specially chosen to test the functionality of a program or design

• Developers or test-users would pick a selection of test data from the following categories

  • Normal

  • Abnormal

  • Extreme

  • Boundary

• The results would be compared to the expected results to check if the algorithm/program works as intended

• Each category is explained within the context of a simple Python program below, comments have been added to help explain the processes

# Ask for user's name
name = input("What is your name? ")

# Ask for user's age
age = int(input("How old are you? "))

# Check if age is between 12 and 18
if age >= 12 and age <= 18:
    print("Welcome, " + name + "! Your age is accepted.")
else:
    print("Sorry, " + name + ". Your age is not accepted.")

Normal data

• Normal test data is data that should be accepted in the program

• An example would be a user entering their age as 16 into the age field of the program

Abnormal data

• Abnormal test data is data that is the wrong data type

• An example would be a user entering their age as "F" into the age field of the program

Extreme data

• Extreme test data is the maximum and minimum values of normal data that are accepted by the system

• An example would be a user entering their age as 18 or 12 into the age field of the program

Boundary data

• Boundary test data is similar to extreme data except that the values on either side of the maximum and minimum values are tested

• The largest and smallest acceptable value is tested as well as the largest and smallest unacceptable value

• An example would be a user entering their age as 11 or 19 into the age field of the program

Selecting suitable test data