Regression testing in Testing Fundamentals - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is regression testing?

Regression testing is a type of software testing that checks if recent code changes have broken existing features or caused new bugs.

beginner

Why is regression testing important in data science projects?

It ensures that updates or new models do not break existing data pipelines, analyses, or reports, keeping results reliable.

beginner

When should regression testing be performed?

After any change in code, such as bug fixes, new features, or updates, to confirm old functions still work correctly.

intermediate

What is a common method to automate regression testing?

Using automated test scripts that run predefined tests quickly and repeatedly to catch errors early.

intermediate

How does regression testing differ from unit testing?

Unit testing checks individual parts of code for correctness, while regression testing checks that changes don’t break existing overall functionality.

What is the main goal of regression testing?

A To check if recent changes broke existing functionality

B To write new code

C To test the speed of the software

D To verify new features work correctly

Regression testing focuses on ensuring that recent code changes do not break existing features.

When should regression testing be done?

A After every code change

B Only before the first release

C Only when bugs are found

D Once a year

Regression testing is done after every code change to catch any new issues early.

Which of these is a benefit of automating regression tests?

A Slower testing process

B More manual work

C Less reliable results

D Faster and repeatable tests

Automation makes regression tests faster and easy to repeat whenever needed.

Regression testing is mainly used to:

A Design new software

B Test new features only

C Check if old features still work after changes

D Improve user interface

It ensures that existing features continue to work after updates.

Which testing type focuses on individual code parts rather than overall system behavior?

A Regression testing

B Unit testing

C Integration testing

D System testing

Unit testing checks small parts of code separately.

Explain in your own words what regression testing is and why it matters in data science projects.

Think about how changes in code might affect your data analysis or models.

Describe when and how you would perform regression testing during a project update.

Consider the steps after you add or fix something in your code.

Practice

1.

What is the main purpose of regression testing in data science projects?

easy

A. To check that new changes do not break existing results

B. To create new models from scratch

C. To collect new data for training

D. To visualize data trends

Solution

1. Step 1: Understand regression testing goal

   Regression testing is about verifying that recent changes do not cause errors in existing functionality.

2. Step 2: Match purpose with options

   Only To check that new changes do not break existing results describes this goal correctly, others describe unrelated tasks.

3. Final Answer:

   To check that new changes do not break existing results -> Option A

4. Quick Check:

   Regression testing = check no breakage [OK]

Hint: Regression testing ensures old results still work after changes [OK]

Common Mistakes:

• Confusing regression testing with model building
• Thinking it collects new data
• Assuming it is for data visualization

2.

Which of the following is the correct way to describe regression testing?

Regression testing:

def regression_test(old_output, new_output):
    return old_output == new_output

easy

A. It compares old and new outputs to detect changes

B. It trains a new model using old and new data

C. It visualizes differences between datasets

D. It deletes old test results before running new tests

Solution

1. Step 1: Analyze the function code

   The function returns True if old_output equals new_output, meaning it compares outputs.

2. Step 2: Match function behavior to options

   It compares old and new outputs to detect changes correctly states it compares outputs to detect changes; others describe unrelated actions.

3. Final Answer:

   It compares old and new outputs to detect changes -> Option A

4. Quick Check:

   Function compares outputs = It compares old and new outputs to detect changes [OK]

Hint: Regression test checks if old and new outputs match exactly [OK]

Common Mistakes:

• Thinking regression testing retrains models
• Assuming it creates visualizations
• Believing it deletes old results

3.

Given the following Python code for regression testing outputs, what will be the printed result?

old_results = [10, 20, 30]
new_results = [10, 20, 25]

if old_results == new_results:
    print("Test Passed")
else:
    print("Test Failed")

medium

A. Test Passed

B. SyntaxError

C. Test Failed

D. No output

Solution

1. Step 1: Compare the two lists element-wise

   old_results has [10, 20, 30], new_results has [10, 20, 25]. The last elements differ (30 vs 25).

2. Step 2: Evaluate the if condition

   Since the lists are not equal, the else block runs, printing "Test Failed".

3. Final Answer:

   Test Failed -> Option C

4. Quick Check:

   Lists differ, so output = Test Failed [OK]

Hint: Lists must match exactly for test to pass [OK]

Common Mistakes:

• Assuming partial match passes test
• Confusing list equality with set equality
• Expecting syntax errors from correct code

4.

Identify the error in this regression testing code snippet:

def regression_test(old, new):
    if old = new:
        return True
    else:
        return False

medium

A. Missing return statement

B. Using assignment operator '=' instead of comparison '==' in if condition

C. Function should print results, not return

D. Incorrect function name

Solution

1. Step 1: Check the if condition syntax

   The condition uses '=' which is assignment, not comparison. Python requires '==' for comparison.

2. Step 2: Identify correct syntax for comparison

   Replacing '=' with '==' fixes the syntax error and allows proper comparison.

3. Final Answer:

   Using assignment operator '=' instead of comparison '==' in if condition -> Option B

4. Quick Check:

   Use '==' to compare, not '=' [OK]

Hint: Use '==' for comparison, '=' is assignment [OK]

Common Mistakes:

• Confusing '=' and '==' in conditions
• Thinking return is missing
• Believing function name matters for syntax

5.

You have a data science model that outputs predictions as a list. You want to automate regression testing to check if new code changes break the model's output. Which approach below best applies regression testing?

hard

A. Delete old predictions and start fresh after every change

B. Train a new model with updated data and ignore old predictions

C. Visualize new predictions only to check for differences

D. Save previous predictions and compare them with new predictions after changes

Solution

1. Step 1: Understand regression testing in model outputs

   Regression testing means re-running tests and comparing new outputs to old outputs to detect unintended changes.

2. Step 2: Evaluate options for best fit

   Save previous predictions and compare them with new predictions after changes saves old predictions and compares them to new ones, matching regression testing. Others ignore old outputs or delete them, which is not regression testing.

3. Final Answer:

   Save previous predictions and compare them with new predictions after changes -> Option D

4. Quick Check:

   Regression testing = compare old and new outputs [OK]

Hint: Keep old outputs to compare with new after changes [OK]

Common Mistakes:

• Ignoring old outputs in testing
• Assuming visualization replaces regression tests
• Deleting old results before testing