Data validation rules in Testing Fundamentals - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to check if the input is not empty.

Testing Fundamentals

if [1]:

Drag options to blanks, or click blank then click option'

Ainput_value

Bnot input_value

Cinput_value == ''

Dinput_value is None

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'not input_value' which checks for empty instead of non-empty.

Comparing input_value to empty string explicitly.

The condition should check if input_value is truthy, meaning it is not empty or None.

2fill in blank

medium

Complete the code to validate that age is a positive integer.

Testing Fundamentals

if isinstance(age, int) and age [1] 0:

Drag options to blanks, or click blank then click option'

A==

B<=

C>

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<=' which allows zero or negative numbers.

Using '==' which only allows age exactly zero.

The age should be greater than 0 to be a valid positive integer.

3fill in blank

hard

Fix the error in the validation that checks if email contains '@'.

Testing Fundamentals

if [1] email:

Drag options to blanks, or click blank then click option'

Aemail.index

B'@' in

Cemail.contains

Demail.find

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'email.contains' which is not a valid string method in Python.

Using 'email.find' incorrectly as a function call.

To check if '@' is in the email string, use the in keyword.

4fill in blank

hard

Fill both blanks to validate a username: it must be a string and at least 3 characters long.

Testing Fundamentals

if isinstance(username, [1]) and len(username) [2] 3:

Drag options to blanks, or click blank then click option'

Astr

B>=

Cint

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Checking for int type instead of str.

Using '<' which checks for less than 3 characters.

The username must be a string and its length should be greater than or equal to 3.

5fill in blank

hard

Fill all three blanks to create a dictionary of valid scores greater than 50.

Testing Fundamentals

valid_scores = [1]: [2] for [1], [2] in scores if [2] > 50}

Drag options to blanks, or click blank then click option'

Aplayer

Bscore

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up keys and values in the dictionary comprehension.

Using the wrong variable names for filtering.

The dictionary comprehension uses 'player' as key and 'score' as value. The filter checks if score is greater than 50.

Practice

1. What is the main purpose of data validation rules in software testing?

easy

A. To check if input data is correct and useful

B. To improve the speed of the software

C. To change the data format automatically

D. To delete old data from the system

Solution

1. Step 1: Understand the role of data validation

   Data validation rules are designed to check input data for correctness and usefulness before processing.

2. Step 2: Compare options with the definition

   Only To check if input data is correct and useful correctly states this purpose; others describe unrelated tasks.

3. Final Answer:

   To check if input data is correct and useful -> Option A

4. Quick Check:

   Data validation = Check correctness [OK]

Hint: Validation means checking data correctness early [OK]

Common Mistakes:

• Confusing validation with data transformation
• Thinking validation improves software speed
• Assuming validation deletes data

2. Which of the following is a correct example of a data validation rule for an email field?

easy

A. The field must contain only numbers

B. The field must not be empty and must contain '@' symbol

C. The field must be exactly 5 characters long

D. The field must be left blank

Solution

1. Step 1: Identify common email validation rules

   Email fields require non-empty input and must include '@' to be valid.

2. Step 2: Evaluate each option

   The field must not be empty and must contain '@' symbol matches these rules; A, B, and D do not fit email validation.

3. Final Answer:

   The field must not be empty and must contain '@' symbol -> Option B

4. Quick Check:

   Email validation = Non-empty + '@' [OK]

Hint: Emails always need '@' and something before/after [OK]

Common Mistakes:

• Checking length without '@' for emails
• Allowing empty email fields
• Restricting emails to numbers only

3. Consider this validation rule in a test script:

assert age >= 18 and age <= 65

What will happen if age = 70 during test execution?

medium

A. Test will ignore the age value

B. Test will pass because 70 is a valid age

C. Test will raise a syntax error

D. Test will fail because 70 is outside the valid range

Solution

1. Step 1: Understand the validation condition

   The rule requires age to be between 18 and 65 inclusive.

2. Step 2: Check the given age value

   Age 70 is greater than 65, so the condition fails and assertion fails.

3. Final Answer:

   Test will fail because 70 is outside the valid range -> Option D

4. Quick Check:

   Age 70 > 65 = Fail [OK]

Hint: Check if value fits the range in assertion [OK]

Common Mistakes:

• Assuming test passes if value is above max
• Confusing syntax error with assertion failure
• Ignoring assertion conditions

4. A tester wrote this validation rule:

assert len(username) > 0 and len(username) < 15

What is the problem with this rule if the username length is exactly 15?

medium

A. The test will fail because 15 is not less than 15

B. The test will pass because 15 is allowed

C. The test will cause a runtime error

D. The test will ignore the username length

Solution

1. Step 1: Analyze the length condition

   The rule requires username length to be greater than 0 and less than 15.

2. Step 2: Check the boundary value 15

   Length 15 is not less than 15, so assertion fails.

3. Final Answer:

   The test will fail because 15 is not less than 15 -> Option A

4. Quick Check:

   Length 15 < 15? No = Fail [OK]

Hint: Check if boundary values are included or excluded [OK]

Common Mistakes:

• Assuming less than includes the number itself
• Ignoring boundary conditions
• Thinking test causes error instead of fail

5. You need to validate a form field that accepts only positive integers less than 1000 and not empty. Which combined validation rule is correct?

hard

A. assert value.isalpha() and int(value) > 0

B. assert value != '' and int(value) >= 1000

C. assert value.isdigit() and 0 < int(value) < 1000

D. assert value == '' or int(value) < 0

Solution

1. Step 1: Understand the requirements

   Value must be non-empty, only digits, positive, and less than 1000.

2. Step 2: Evaluate each option

   assert value.isdigit() and 0 < int(value) < 1000 checks digits only, converts to int, and tests range correctly. Others fail one or more conditions.

3. Final Answer:

   assert value.isdigit() and 0 < int(value) < 1000 -> Option C

4. Quick Check:

   Digits + positive + <1000 = assert value.isdigit() and 0 < int(value) < 1000 [OK]

Hint: Check digits, non-empty, and range in one assertion [OK]

Common Mistakes:

• Using isalpha() instead of isdigit()
• Allowing empty strings
• Checking wrong numeric ranges