test: migrate math/base/special/acotf to ULP-based testing

[Planeshifter]

Resolves a part of #11352.

Description

What is the purpose of this pull request?

This pull request:

• migrates math/base/special/acotf test cases from relative-tolerance-based assertions (EPS/abs/tol idiom) to ULP-based assertions using @stdlib/number/float32/base/assert/is-almost-same-value in both test/test.js and test/test.native.js.
• uses measured minimum ULP bounds per fixture set: 3 for medium_positive/medium_negative, 2 for large_positive/large_negative/larger_positive/larger_negative, and 1 for huge_positive/huge_negative. Each bound is the smallest integer for which the full fixture set passes (verified by lowering to N-1 and confirming at least one failure in every group).
• test suite was run twice at the final ULP bounds for both test.js and the native binding (test.native.js, built locally via node-gyp rebuild) to confirm deterministic results (no FMA/arch flakiness).

Related Issues

Does this pull request have any related issues?

This pull request has the following related issues:

• [RFC]: Migrate math/base/special packages from relative tolerance testing to ULP difference testing (tracking issue) #11352

Questions

Any questions for reviewers of this pull request?

No.

Other

Any other information relevant to this pull request? This may include screenshots, references, and/or implementation notes.

Final ULP constants: 3 (medium), 2 (large/larger), 1 (huge).

Checklist

Please ensure the following tasks are completed before submitting this pull request.

• Read, understood, and followed the contributing guidelines.

AI Assistance

When authoring the changes proposed in this PR, did you use any kind of AI assistance?

• Yes
• No

If you answered "yes" above, how did you use AI assistance?

• Code generation (e.g., when writing an implementation or fixing a bug)
• Test/benchmark generation
• Documentation (including examples)
• Research and understanding

Disclosure

If you answered "yes" to using AI assistance, please provide a short disclosure indicating how you used AI assistance. This helps reviewers determine how much scrutiny to apply when reviewing your contribution. Example disclosures: "This PR was written primarily by Claude Code." or "I consulted ChatGPT to understand the codebase, but the proposed changes were fully authored manually by myself.".

This PR was written primarily by Claude Code, running as an automated scheduled task: it discovered the candidate package, studied prior art from already-converted packages, performed the conversion, measured the tightest ULP bounds agentically, and verified the result.

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@stdlib-js/reviewers

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Generated by Claude Code

[stdlib-bot]

Coverage Report

Package	Statements	Branches	Functions	Lines
math/base/special/acotf	$\\color{green}193/193$ $\\color{green}+100.00\\%$	$\\color{green}5/5$ $\\color{green}+100.00\\%$	$\\color{green}2/2$ $\\color{green}+100.00\\%$	$\\color{green}193/193$ $\\color{green}+100.00\\%$

The above coverage report was generated for the changes in this PR.