What you will learn
- Build the module-specific task for Dependencies and Test Doubles and verify the expected artifact with a concrete result.
- Produce or inspect a working dependencies and test doubles exercise with a documented technical result.
- Verify the result with the module-specific command, output, test, rendered state, query result, log, or measurement that proves the exercise worked.
What you need
- Open a small local project or disposable lab environment.
- Confirm the runtime, toolchain, or service needed for the module.
- Prepare one valid input and one invalid or boundary input.
Define the build target
For Dependencies and Test Doubles, test a component with one controlled dependency, then remove a flaky source such as real time, network, or shared mutable state and confirm the test stays deterministic. Build the boundary case using this implementation lens: Use explicit behavior contracts, test cases, fixtures, doubles, integration boundaries, failure messages, reliability signals, and delivery feedback loops.
Keep the Dependencies and Test Doubles build centered on these technical constraints: Test double purpose and boundary. Deterministic time/randomness/data. Apply them through this path lens: Use explicit behavior contracts, test cases, fixtures, doubles, integration boundaries, failure messages, reliability signals, and delivery feedback loops. Use explicit behavior contracts, test cases, fixtures, doubles, integration boundaries, failure messages, reliability signals, and delivery feedback loops.
Implement the core behavior
Implement Dependencies and Test Doubles around the module artifact—a working dependencies and test doubles exercise with a documented technical result—and keep the implementation specific to this path context: Use explicit behavior contracts, test cases, fixtures, doubles, integration boundaries, failure messages, reliability signals, and delivery feedback loops.
def total_with_tax(subtotal, rate):
if subtotal < 0:
raise ValueError('subtotal must be non-negative')
return round(subtotal * (1 + rate), 2)
def test_total_with_tax():
assert total_with_tax(100, 0.08) == 108.00
def test_negative_subtotal_is_rejected():
import pytest
with pytest.raises(ValueError):
total_with_tax(-1, 0.08)
pytest -qThe success case passes and the invalid input is rejected by an explicit test.
practice/\n├── README.md\n├── dependencies-and-test-doubles-build.py\n└── evidence/\n └── expected-result.txtApply Dependencies and Test Doubles
Build the module-specific task for Dependencies and Test Doubles and verify the expected artifact with a concrete result.
- Use the lesson-specific technical example as a reference, not a copy.
- Change one condition that matters to Dependencies and Test Doubles.
- Verify the result with the module-specific command, output, test, rendered state, query result, log, or measurement that proves the exercise worked.
Run the complete path
Run one realistic Dependencies and Test Doubles case end to end and record the required evidence: the module-specific command, output, test, rendered state, query result, log, or measurement that proves the exercise worked. Interpret the result through this path context: Use explicit behavior contracts, test cases, fixtures, doubles, integration boundaries, failure messages, reliability signals, and delivery feedback loops.
Change one meaningful condition
Modify one condition central to Dependencies and Test Doubles using this path context: Use explicit behavior contracts, test cases, fixtures, doubles, integration boundaries, failure messages, reliability signals, and delivery feedback loops. Predict the new result before rerunning the same workflow.
Verify the artifact
Your deliverable is a working dependencies and test doubles exercise with a documented technical result.
- The primary case works.
- One boundary or failure case is handled intentionally.
- The result is verified with the module-specific command, output, test, rendered state, query result, log, or measurement that proves the exercise worked.
- You can explain why the implementation behaves as observed.
Practice Dependencies and Test Doubles
For Dependencies and Test Doubles, test a component with one controlled dependency, then remove a flaky source such as real time, network, or shared mutable state and confirm the test stays deterministic. Build the boundary case using this implementation lens: Use explicit behavior contracts, test cases, fixtures, doubles, integration boundaries, failure messages, reliability signals, and delivery feedback loops.
- 1
Write the expected result before starting.
- 2
For Dependencies and Test Doubles, test a component with one controlled dependency, then remove a flaky source such as real time, network, or shared mutable state and confirm the test stays deterministic. Build the boundary case using this implementation lens: Use explicit behavior contracts, test cases, fixtures, doubles, integration boundaries, failure messages, reliability signals, and delivery feedback loops.
- 3
Record the module-specific command, output, test, rendered state, query result, log, or measurement that proves the exercise worked and explain whether it matches the expectation.
Practice what you learned
Exercises are optional for lesson completion and contribute to a separate Practice Mastery score.
Core Check: Build a Practical Dependencies and Test Doubles Example in Software Testing Fundamentals
Complete a focused exercise for “Build a Practical Dependencies and Test Doubles Example in Software Testing Fundamentals”. Your task is to Control dependencies only where needed, keep tests deterministic, and make failures point to product behavior rather than unstable clocks, networks, or shared state. Use one concrete example and show evidence that the result is correct.
Verification target: a working dependencies and test doubles exercise with a documented technical result
This exercise has been updated since your saved draft. Your draft was kept. Reset only if you want the latest starter code.
Not completed
Start with Build a Practical Dependencies and Test Doubles Example in Software Testing Fundamentals. Then connect it to the lesson task: Control dependencies only where needed, keep tests deterministic, and make failures point to product behavior rather than unstable clocks, networks, or shared state.
Goal: Control dependencies only where needed, keep tests deterministic, and make failures point to product behavior rather than unstable clocks, networks, or shared state.
Concept: Build a Practical Dependencies and Test Doubles Example in Software Testing Fundamentals
Supporting idea: Test a component with one controlled dependency, then remove a flaky source such as real time, network, or shared mutable state and confirm the test stays deterministic
Expected result: a working dependencies and test doubles exercise with a documented technical result
Verification evidence: a working dependencies and test doubles exercise with a documented technical resultThis reference answer connects the lesson task and technical concepts to observable evidence. Compare the structure and reasoning, not only the exact wording.
Mini Challenge: Build a Practical Dependencies and Test Doubles Example in Software Testing Fundamentals
Extend “Build a Practical Dependencies and Test Doubles Example in Software Testing Fundamentals” into a boundary or failure scenario. Start from this lesson task: Control dependencies only where needed, keep tests deterministic, and make failures point to product behavior rather than unstable clocks, networks, or shared state. Change one condition that matters, predict the outcome first, then show evidence that confirms or disproves the prediction.
Verification target: a working dependencies and test doubles exercise with a documented technical result
This exercise has been updated since your saved draft. Your draft was kept. Reset only if you want the latest starter code.
Not completed
Combine Build a Practical Dependencies and Test Doubles Example in Software Testing Fundamentals with Test a component with one controlled dependency, then remove a flaky source such as real time, network, or shared mutable state and confirm the test stays deterministic. Aim to produce: a working dependencies and test doubles exercise with a documented technical result.
Goal: Control dependencies only where needed, keep tests deterministic, and make failures point to product behavior rather than unstable clocks, networks, or shared state.
Predicted result: a working dependencies and test doubles exercise with a documented technical result
Approach:
1. Build a Practical Dependencies and Test Doubles Example in Software Testing Fundamentals
2. Test a component with one controlled dependency, then remove a flaky source such as real time, network, or shared mutable state and confirm the test stays deterministic
3. Change one boundary or failure condition.
4. Verify with observable evidence.
Evidence: a working dependencies and test doubles exercise with a documented technical resultThis reference answer connects the lesson task and technical concepts to observable evidence. Compare the structure and reasoning, not only the exact wording.
Common mistakes to avoid
- Mocking the unit under test.
- Overspecified call-order assertions.
- Real external network in unit test.
- Shared test data leaks between cases.
Key takeaways
- Build the module-specific task for Dependencies and Test Doubles and verify the expected artifact with a concrete result.
- Keep the exercise small enough to explain the important state and decision.
- Use the module-specific command, output, test, rendered state, query result, log, or measurement that proves the exercise worked rather than successful command completion alone.
Frequently asked questions
What should I be able to do before moving on?
You should be able to explain the purpose of Dependencies and Test Doubles, build a small example without copying the lesson line by line, and diagnose a basic failure using the relevant tool or error output.
How much should I build for practice?
Keep the exercise small enough that you can explain every important input, state change, and output. Add complexity only after the core behavior is reliable.
Sources and further reading
- unittest.mock — mock object libraryPython Software Foundation
- Certified Tester Foundation Level syllabusISTQB
- unittest — Unit testing frameworkPython Software Foundation
Ready to continue?
Mark the lesson complete so your Learning Path progress stays current on this device.