Casilian StudiosCASILIANMODDING SCHOOL

WillowScript (.ws) is a proposed, not-yet-implemented language. Examples and library integrations here are illustrative design exercises, not verified runnable programs.

WillowScript Professional · Compare absolute and relative error

Separate symbolic and numerical work — Boundary detective

Separate symbolic and numerical work: boundary detective.

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PART I

Warm-up

Reconnect with a useful idea before starting separate symbolic and numerical work. 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

Compare absolute and relative error

Prediction 1001, reference 1000; absolute tolerance is 0.5 and relative tolerance is 0.2 percent.

Absolute error is 1, so the absolute test fails. Relative error is 1/1000=0.001=0.1 percent, so the relative test passes. Neither result contradicts the other because the contracts measure different quantities.

Write the intermediate states explicitly before proposing a code change. The example below remains an illustrative source anchor; this new case changes the inputs or the host requirement. WillowScript and these library services are proposed and unimplemented here. Treat new policies as supplied exercise contracts, and keep hand predictions distinct from native execution evidence.

Worked reasoning and supplied artifact

// PAPER FIXTURE — Compare absolute and relative error
// Manual worked artifact; comments below are not executable source.
// INPUT / CONTRACT: Prediction 1001, reference 1000; absolute tolerance is 0.5 and relative tolerance is
// 0.2 percent.
// DERIVATION / EXPECTED ARTIFACT: Absolute error is 1, so the absolute test fails. Relative error is
// 1/1000=0.001=0.1 percent, so the relative test passes. Neither result contradicts the other because the
// contracts measure different quantities.

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
  1. // PAPER FIXTURE — Compare absolute and relative error

    This comment explains intent for a reader. It is not an operation and should not be counted as an executed result.

  2. // Manual worked artifact; comments below are not executable source.

    This comment explains intent for a reader. It is not an operation and should not be counted as an executed result.

  3. // INPUT / CONTRACT: Prediction 1001, reference 1000; absolute tolerance is 0.5 and relative tolerance is

    This comment explains intent for a reader. It is not an operation and should not be counted as an executed result.

  4. // 0.2 percent.

    This comment explains intent for a reader. It is not an operation and should not be counted as an executed result.

  5. // DERIVATION / EXPECTED ARTIFACT: Absolute error is 1, so the absolute test fails. Relative error is

    This comment explains intent for a reader. It is not an operation and should not be counted as an executed result.

  6. // 1/1000=0.001=0.1 percent, so the relative test passes. Neither result contradicts the other because the

    This comment explains intent for a reader. It is not an operation and should not be counted as an executed result.

  7. // contracts measure different quantities.

    This comment explains intent for a reader. It is not an operation and should not be counted as an executed result.

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.

Your drafts remain here. Continue whenever you are ready.

PART IV

Independent practice

Project context: Estimator specification. Build a small, understandable change around separate symbolic and numerical work.

Compare prediction 10.01 against reference 10 with the same two rules.

What to produce

Compare prediction 10.01 against reference 10 with the same two rules.

  • 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?

Absolute error is 1, so the absolute test fails. Relative error is 1/1000=0.001=0.1 percent, so the relative test passes. Neither result contradicts the other because the contracts measure different quantities.

The tempting answer “No; the tests are identical” does not satisfy this case. Absolute error is 1, so the absolute test fails. Relative error is 1/1000=0.001=0.1 percent, so the relative test passes. Neither result contradicts the other because the contracts measure different quantities.

Original learning-path task and reference

In a research data workstation, demonstrate separate symbolic and numerical work. Add normal, boundary, and invalid-input cases and explain expected behavior. Include .ws source and a host-resource contract; compare at least one normal case and one edge case.

import math;
domain Calculation {
    fnc sample() -> void {
        vary x: i32 = 2;
        vary value = [[ (x * 5) + 20 ]];
    }
}

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.

Can a result fail absolute tolerance yet pass relative tolerance?

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.

  • Compare absolute and relative error
  • Prediction 1001, reference 1000; absolute tolerance is 0.5 and relative tolerance is 0.2 percent.
  • Separate source-backed behavior, host requirements and untested predictions.

One small recap task

Change one input in this case and state which intermediate state or calculation must be recomputed. Explain why “No; the tests are identical” is not justified.

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

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