PYTHON-05 · Secondary · ENGLISH · PLANNED
Predict the output, trace state, write a small program and debug it.
Study time is an initial activity estimate, excluding extra reading, revision and extended laboratory or project work. Videos and question bodies have not been produced by adding this outline.
Complete these courses or demonstrate equivalent knowledge. These are recommended prerequisites, not enforced enrolment locks.
YouTube playlist: ARK Python | Testing, Debugging and Maintainable Python
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Sign in to save this learning pathPractical outcome: Diagnose three seeded bugs using observed values and hypotheses.
Explain reproducing a bug using a visual and one worked real-world example. Context: Diagnose three seeded bugs using observed values and hypotheses. End with a prediction or check-for-understanding.
Explain minimal examples using a visual and one worked real-world example. Context: Diagnose three seeded bugs using observed values and hypotheses. End with a prediction or check-for-understanding.
Explain reading a traceback using a visual and one worked real-world example. Context: Diagnose three seeded bugs using observed values and hypotheses. End with a prediction or check-for-understanding.
Explain breakpoints using a visual and one worked real-world example. Context: Diagnose three seeded bugs using observed values and hypotheses. End with a prediction or check-for-understanding.
Use the first concepts from this section. Diagnose three seeded bugs using observed values and hypotheses. Produce a labelled diagram, trace or calculation; explain each step and check one changed input.
3–6 questions on the preceding first-half concepts only: recall, visual interpretation, application and one plausible misconception. Explain each answer after submission.
Explain stepping using a visual and one worked real-world example. Context: Diagnose three seeded bugs using observed values and hypotheses. End with a prediction or check-for-understanding.
Explain inspecting variables using a visual and one worked real-world example. Context: Diagnose three seeded bugs using observed values and hypotheses. End with a prediction or check-for-understanding.
Explain assertions using a visual and one worked real-world example. Context: Diagnose three seeded bugs using observed values and hypotheses. End with a prediction or check-for-understanding.
Explain regression tests using a visual and one worked real-world example. Context: Diagnose three seeded bugs using observed values and hypotheses. End with a prediction or check-for-understanding.
Diagnose three seeded bugs using observed values and hypotheses. Work without the example, compare two cases, record assumptions and limitations, then self-review correctness, reasoning and clarity.
6–12 questions covering Reproducing a bug, Minimal examples, Reading a traceback and the remaining section concepts, with cumulative retrieval from earlier sections. Include a new transfer problem; 70% unlocks progression.
Practical outcome: Write expected cases for a small receipt calculator.
Explain unit-test structure using a visual and one worked real-world example. Context: Write expected cases for a small receipt calculator. End with a prediction or check-for-understanding.
Explain arrange act assert using a visual and one worked real-world example. Context: Write expected cases for a small receipt calculator. End with a prediction or check-for-understanding.
Explain edge cases using a visual and one worked real-world example. Context: Write expected cases for a small receipt calculator. End with a prediction or check-for-understanding.
Explain parameterised cases using a visual and one worked real-world example. Context: Write expected cases for a small receipt calculator. End with a prediction or check-for-understanding.
Use the first concepts from this section. Write expected cases for a small receipt calculator. Produce a labelled diagram, trace or calculation; explain each step and check one changed input.
3–6 questions on the preceding first-half concepts only: recall, visual interpretation, application and one plausible misconception. Explain each answer after submission.
Explain test fixtures using a visual and one worked real-world example. Context: Write expected cases for a small receipt calculator. End with a prediction or check-for-understanding.
Explain mocking boundaries using a visual and one worked real-world example. Context: Write expected cases for a small receipt calculator. End with a prediction or check-for-understanding.
Explain integration tests using a visual and one worked real-world example. Context: Write expected cases for a small receipt calculator. End with a prediction or check-for-understanding.
Explain coverage limitations using a visual and one worked real-world example. Context: Write expected cases for a small receipt calculator. End with a prediction or check-for-understanding.
Write expected cases for a small receipt calculator. Work without the example, compare two cases, record assumptions and limitations, then self-review correctness, reasoning and clarity.
6–12 questions covering Unit-test structure, Arrange act assert, Edge cases and the remaining section concepts, with cumulative retrieval from earlier sections. Include a new transfer problem; 70% unlocks progression.
Practical outcome: Organise a small reusable package with repeatable setup.
Explain modules using a visual and one worked real-world example. Context: Organise a small reusable package with repeatable setup. End with a prediction or check-for-understanding.
Explain imports using a visual and one worked real-world example. Context: Organise a small reusable package with repeatable setup. End with a prediction or check-for-understanding.
Explain main guard using a visual and one worked real-world example. Context: Organise a small reusable package with repeatable setup. End with a prediction or check-for-understanding.
Explain packages using a visual and one worked real-world example. Context: Organise a small reusable package with repeatable setup. End with a prediction or check-for-understanding.
Explain virtual environments using a visual and one worked real-world example. Context: Organise a small reusable package with repeatable setup. End with a prediction or check-for-understanding.
Use the first concepts from this section. Organise a small reusable package with repeatable setup. Produce a labelled diagram, trace or calculation; explain each step and check one changed input.
3–6 questions on the preceding first-half concepts only: recall, visual interpretation, application and one plausible misconception. Explain each answer after submission.
Explain dependency installation using a visual and one worked real-world example. Context: Organise a small reusable package with repeatable setup. End with a prediction or check-for-understanding.
Explain version constraints using a visual and one worked real-world example. Context: Organise a small reusable package with repeatable setup. End with a prediction or check-for-understanding.
Explain formatting using a visual and one worked real-world example. Context: Organise a small reusable package with repeatable setup. End with a prediction or check-for-understanding.
Explain naming using a visual and one worked real-world example. Context: Organise a small reusable package with repeatable setup. End with a prediction or check-for-understanding.
Explain readme usage instructions using a visual and one worked real-world example. Context: Organise a small reusable package with repeatable setup. End with a prediction or check-for-understanding.
Organise a small reusable package with repeatable setup. Work without the example, compare two cases, record assumptions and limitations, then self-review correctness, reasoning and clarity.
6–12 questions covering Modules, Imports, Main guard and the remaining section concepts, with cumulative retrieval from earlier sections. Include a new transfer problem; 70% unlocks progression.
Combine all three sections: Organise a small reusable package with repeatable setup. Submit an original worked artifact, evidence or tests, assumptions and a reflection. Rubric: correctness, method, practical usefulness, reproducibility and communication. Self-reviewed, not certified.
6–12 balanced questions sampling every section of Testing, Debugging and Maintainable Python, including interpretation, calculation or reasoning, a misconception and a new application. Passing is 70%; review errors before retrying.
Coding, trace tables, tests and original portfolio projects. Guided work leads to an independent attempt, with a diagram, explanation, trace, calculation or tested artifact. Question bodies are generated when opened in your private learning path. Programming submissions are stored as text; the platform does not execute submitted code.
Use original or appropriately licensed datasets. Practical science activities use models or supplied data unless a qualified supervisor has reviewed a physical experiment.
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