PART I
Warm-up
Reconnect with a useful idea before starting choose a pressure eviction policy. 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 policy evidence rather than labels
An eviction ranking applies only after eligibility is established. Least-recent-use, largest-first and expiry-first policies optimize different goals and can choose different victims. Make the objective explicit, calculate the effect and keep active or recovery-critical resources outside the candidate list.
Exercise cache ledger under a 100 MiB budget: A30 last used 1 minute ago, expires in 20; B20 last used 10 minutes ago, expires in 2; C25 last used 4 minutes ago, expires in 5; D15 active/retained. Usage 90. A/B/C are regenerable and eligible; D is never eligible while its owner is active. Rebuild costs are A60 s, B5 s, C20 s.
Supplied case: Implementation claims LRU but audit records only final usage and no eligible-candidate ages.
Worked reasoning: Capture decision-time eligibility and last-use data, selected victims and cumulative reclaim. Then the observer can reconstruct whether the stated ranking was followed. Also verify D was never selected.
Contrast and diagnosis: A correct final total could result from an entirely different or unsafe policy.
Worked reasoning and supplied artifact
// Disposable exercise fixture / host-contract notes; not executable API syntax.
// Supplied input: Implementation claims LRU but audit records only final usage and no eligible-candidate ages.
// Worked prediction: Capture decision-time eligibility and last-use data, selected victims and cumulative reclaim. Then the observer can reconstruct whether the stated ranking was followed. Also verify D was never selected.
// Rejected alternative: A correct final total could result from an entirely different or unsafe policy.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.
Walk through the example, one line at a time
Supplied caseImplementation claims LRU but audit records only final usage and no eligible-candidate ages.
State / decision traceCapture decision-time eligibility and last-use data, selected victims and cumulative reclaim. Then the observer can reconstruct whether the stated ranking was followed. Also verify D was never selected.
Contrasting failureA correct final total could result from an entirely different or unsafe policy.
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: Resource budget dashboard. Build a small, understandable change around choose a pressure eviction policy.
Write two audit fixtures: one correct LRU decision and one largest-first decision mislabeled LRU. Explain the evidence that distinguishes them.
What to produce
Write two audit fixtures: one correct LRU decision and one largest-first decision mislabeled LRU. Explain the evidence that distinguishes them. Include input → intermediate decision/state → predicted outcome, with any required host rule stated explicitly.
- 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.
Need a hint?
Start with this case’s decisive boundary: Eligible candidates’ last-use ages and selected victims. Apply the same rule to the new inputs rather than copying the old outcome.
A correct final total could result from an entirely different or unsafe policy.
Original learning-path task and reference
In a racing checkpoint editor, demonstrate choose a pressure eviction policy. Submit source, acceptance cases, and an explanation proving the section objective. Include .ws source and a host-resource contract; compare at least one normal case and one edge case.
import tmp;
const cache = tmp.create({
name: "report-cache",
storage: "ssd",
maxSize: "2GB",
lifetime: { duration: "30m", refreshOnAccess: true },
cleanup: { automatic: true, onCrashRecovery: true }
});Where the original task needs a host API that is not supplied here, write the contract and predictions. Do not invent a runtime result.
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 policy evidence rather than labels
- Explain the decision for the supplied case, then independently work the changed fixture.
- Separate source-backed behavior, host requirements and untested predictions.
One small recap task
In one or two sentences, name the decisive rule in “Review policy evidence rather than labels” and predict the outcome of one changed input from your independent fixture. State which host behavior still needs real verification.
This marks your personal practice record only. It is not a certification or an official workspace assessment.
