Regression testing in Testing Fundamentals - Full Explanation

Introduction

Imagine you fixed a problem in a software but want to be sure that your fix didn't break anything else. This is the challenge regression testing solves by checking that existing features still work after changes.

Explanation

Purpose of Regression Testing

Regression testing is done to confirm that recent code changes have not negatively affected existing functionality. It helps maintain software quality by catching unexpected bugs introduced by updates or fixes.

Regression testing ensures new changes do not break existing features.

When Regression Testing is Performed

It is usually performed after any code modification such as bug fixes, enhancements, or configuration changes. This testing is repeated frequently during the software development lifecycle to keep the software stable.

Regression testing is done after every change to verify stability.

Types of Regression Testing

There are different types including full regression, where all tests are run, and partial regression, where only affected parts are tested. Choosing the right type depends on the extent of changes and available resources.

Regression testing can be full or partial depending on the change scope.

Automation in Regression Testing

Automating regression tests saves time and effort since tests are run repeatedly. Automated tests quickly check many features and help detect problems early, making them ideal for regression testing.

Automation makes regression testing faster and more reliable.

Real World Analogy

Think of a car mechanic who fixes the brakes but then tests the whole car to make sure the steering, lights, and engine still work fine. This careful check after a fix is like regression testing in software.

Purpose of Regression Testing → Mechanic checking all car functions after fixing brakes to ensure nothing else broke

When Regression Testing is Performed → Testing the car every time a repair or upgrade is done

Types of Regression Testing → Sometimes testing the whole car, sometimes only the parts related to the repair

Automation in Regression Testing → Using diagnostic machines to quickly test many car systems repeatedly

Diagram

Diagram

┌───────────────────────────────┐
│        Code Change             │
└──────────────┬────────────────┘
               │
               ▼
┌───────────────────────────────┐
│    Regression Testing Run      │
│ ┌───────────────┐  ┌─────────┐│
│ │ Full Tests    │  │ Partial ││
│ │ (All features)│  │ Tests   ││
│ └───────────────┘  └─────────┘│
└──────────────┬────────────────┘
               │
               ▼
┌───────────────────────────────┐
│  Confirm No Existing Features  │
│  Are Broken After Changes      │
└───────────────────────────────┘

This diagram shows how regression testing runs after code changes, using full or partial tests to confirm existing features still work.

Key Facts

Regression Testing → Testing to verify that recent code changes have not broken existing software functionality.

Full Regression Testing → Running all test cases to check the entire software after changes.

Partial Regression Testing → Running only selected tests related to the recent changes.

Test Automation → Using software tools to run tests automatically and repeatedly.

Regression Test Suite → A collection of test cases used specifically for regression testing.

Code Example

Testing Fundamentals

import unittest

class Calculator:
    def add(self, a, b):
        return a + b

class TestCalculator(unittest.TestCase):
    def test_add(self):
        calc = Calculator()
        self.assertEqual(calc.add(2, 3), 5)

    def test_add_negative(self):
        calc = Calculator()
        self.assertEqual(calc.add(-1, -1), -2)

if __name__ == '__main__':
    unittest.main()

Common Confusions

Regression testing is the same as retesting.

Regression testing is the same as retesting. Retesting checks if a specific bug fix works, while regression testing checks if other parts of the software still work after any change.

Regression testing only needs to be done once after a big change.

Regression testing only needs to be done once after a big change. Regression testing should be done after every change, no matter how small, to ensure ongoing stability.

Summary

Regression testing checks that software changes do not break existing features.

It is performed after every code change and can be full or partial depending on the situation.

Automating regression tests helps run them quickly and often to keep software stable.

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