Write data and UI acceptance cases — Review and demonstrate

PART I

Warm-up

Reconnect with a useful idea before starting write data and ui acceptance cases. In one or two sentences, describe the input, output or host boundary from the previous exercise that this lesson builds on. If you are arriving directly, skim the worked example first; there is no locked prerequisite.

A rough note is enough. You can revise it after the example.

PART II

Instruction & guided example

Review data correctness separately from visual correctness

Data and UI acceptance need the same concrete dataset. A report claim is testable only when the supplied rows, filter, projection, ordering and visible state are explicit. WDB’s proposed query design is not this website’s SQLite runtime. Field names and collections come from the exercise host, and tie, missing-value and snapshot rules need their own contracts.

A screenshot shows a readable low-stock table containing A stock=0 and C stock=10. The supplied rule is stock<10 and source also includes B stock=9. Layout and labels are otherwise correct.

Calculate the selected rows by hand, then derive the visible representation from those results. Keep empty success separate from unavailable data. A screenshot can show a layout but cannot prove its underlying query or resource authorization was correct. Worked case: The table has one false inclusion, C, and one false omission, B. A visual review can acknowledge readability while rejecting the data result. Correct data reasoning requires comparison to the supplied predicate and full source.

Compare the tempting alternative: Approving the report because it looks polished leaves operationally wrong rows in place. Rejecting all layout work because the filter is wrong loses useful independent findings.

Worked reasoning and supplied artifact

// Paper trace / supplied exercise-host contract; no execution claimed.
// A screenshot shows a readable low-stock table containing A stock=0 and C stock=10. The supplied rule is stock<10 and source also includes B stock=9. Layout and labels are otherwise correct.
// The table has one false inclusion, C, and one false omission, B. A visual review can acknowledge readability while rejecting the data result. Correct data reasoning requires comparison to the supplied predicate and full source.

Illustrative example from the proposed WillowScript design. The language and WUIX/WMATH/WDB/WAUDIO/WTMP services are not implemented in the supplied source. This site has no interpreter, VM or native host and does not execute or certify the snippet.

Try the guided change

Reconstruct the supplied worked case first: list its inputs, intermediate decisions and final artifact. Compare each row with the explanation and identify exactly where the rejected alternative fails. Then use the changed inputs in Part IV for independent work.

• Write the supplied inputs and initial state before following the example.
• Reconstruct each intermediate calculation or host decision, then compare with the worked artifact.
• Explain why the contrasting alternative fails before attempting the changed inputs in Part IV.

PART III

Take a breather

Step back after the guided example. Look away from the screen, stretch, or reread your prediction. This is an optional learning pause, not a timer or an assessment gate.

When you return, try to name the lesson’s key idea without copying its wording. If that feels difficult, return to Part II and trace one line rather than restarting the entire lesson.

PART IV

Independent practice

Project context: Operations reporting utility. Build a small, understandable change around write data and ui acceptance cases.

Annotate inclusion/omission defects and produce the corrected artifact. State which claim the screenshot supports and which the predicate trace evaluates.

What to produce

A source-to-visible row audit and corrected expected table.

• State the intended behavior in a sentence before editing.
• Use only source-backed syntax and the host services whose contract you have been given.
• Record a normal case and a boundary or unavailable-resource case.
• Label hand predictions separately from anything actually measured in a supplied toolchain.

Syntax colors are a reading aid, not a compiler. The line you are editing stays uncolored until you move to a different line; capitalization is never changed. Drafts stay on this browser and code is not executed.

import wdb;
domain Inventory {
    const lowStock = wdb.query({
        from: products,
        select: [id, name, stock],
        where: [[ stock < 10 ]],
        order: { by: stock, direction: ascending }
    });
}

PART V

Self-check

Use this check to notice what to revisit. It does not award a private course grade, block another page or claim to verify compiled code. Every answer has a learning explanation.

You may keep exploring even if you are unsure. Use the hint, compare the trace, and revise your explanation.

PART VI

Recap & small task

Bring the idea back to the mod feature you are building. A useful recap connects the mechanism to a decision you can make in your own code.

• Review data correctness separately from visual correctness
• Annotate inclusion/omission defects and produce the corrected artifact. State which claim the screenshot supports and which the predicate trace evaluates.
• Separate source-backed behavior, host requirements and untested predictions.

One small recap task

Name the two different defect types in the screenshot.

This marks your personal practice record only. It is not a certification or an official workspace assessment.