Collections, files and reliable data: Representations and decisions

≈ 36 min

Collections, files and reliable data: Representations and decisions

Use an array when positions are fixed and an ArrayList when a collection grows or shrinks. A file persists data after a program closes, so every imported record needs a format and range check before it becomes trusted program data.

Learning move. In this lesson, choose a diagram, table, trace or model that makes the decision visible.

Worked example. A club sign-up list suits an ArrayList because learners may join or leave. A blank line or duplicate in an import is an information problem to report, not a reason to silently invent a value.

Which statement best reflects this lesson's data validation?

Validate each imported record before it is added to the collection.

Use a vague rule and trust the first result.

Ignore boundary cases and hidden assumptions.

Choose a tool before stating the problem.

Write the key term for this lesson: data validation.

A school system needs a reliable next step. Which choice is most defensible for this topic?

Reject a malformed record with a clear reason while retaining valid records.

Store an unexplained guess and call it evidence.

Give every account unrestricted access.

Hide the error so the report looks complete.

A learner can repeat a definition from Collections, files and reliable data: Representations and decisions. Which next task gives stronger evidence of mastery?

Apply the idea to an unfamiliar boundary, error or decision and justify the choice.

Repeat the lesson title without using the concept.

Choose the first option before reading the scenario.

Hide an unexpected result so the answer appears tidy.