[UtkarshUsername]

Problem

Changed-file cards repeatedly configure locale comparison while sorting file and directory names. Large changed-file lists spend most of their tree-building time in these comparisons.

Change

Create a collator on the first comparison and reuse it. Preserve the default locale, numeric sorting, base sensitivity, and stable ties. Lazy initialization keeps ICU setup off module import.

Scope and approval

Small, focused performance fix for redundant collation setup in the existing tree builder. The separate diff-review sorter already uses this approach (#18420).

Verification

Files	Before, ms/build	After, ms/build	Speedup
10	0.110	0.023	4.8x
200	2.967	0.315	9.4x
1,000	26.373	2.380	11.1x

• Node 26.12.1 function benchmarks on Windows: five isolated trials per arm, alternating order, two baseline controls per trial. Maximum A/A difference: 20.3%. These measure tree construction, excluding rendering.
• Tradeoff: sampled JS allocations increased 5.2% at 200 files and decreased 23.8% at 1,000. Profiled GC time per 300 builds fell from 29.6 to 12.1 ms and 220.0 to 33.5 ms, respectively. One collator is retained after use; native ICU memory was not sized. Module import stayed around 1 ms in fresh-process probes.
• Four focused tests passed, covering numeric ordering, stable case/accent ties, directory compaction, and aggregated statistics. An additional 7,530 differential cases matched the baseline across five explicit locale probes, including path normalization and Unicode names.
• vp run check:changed upstream/main: passed format, lint, knip, affected-package typechecks, and adjacent tests.

Implemented with GPT-6.1 Sol (high) through Codex in T3 Code.

[macroscopeapp]

Approvability

Verdict: Approved at 3a23614

Macroscope's review found this PR approvable — This is a small, self-contained performance improvement that reuses a lazily initialized collator for existing changed-file tree sorting. Sorting semantics and existing application paths remain unchanged, with focused tests added for ordering behavior.

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ℹ️ Recent review info

⚙️ Run configuration

• Source mode: Auto
• Repository: pingdotgg/t3code
• Branch: main
• File: .coderabbit.config.ts
• Commit: 4eae8ae
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• Review profile: CHILL
• Plan: Advanced
• Run ID: ddad0e6a-9e3f-4ed5-9bcf-13afd3f1d8ef

📥 Commits

Reviewing files that changed from the base of the PR and between 4eae8ae and 3a23614.

📒 Files selected for processing: 2

• apps/web/src/lib/turnDiffTree.test.ts
• apps/web/src/lib/turnDiffTree.ts

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📝 Walkthrough

Name sorting now reuses a lazily initialized Intl.Collator configured for numeric sorting and base sensitivity. Tests cover directory and file ordering, nested children, and input order for names tied by case- and accent-insensitive comparison.

Changes: Turn diff tree sorting

Layer / File(s)	Summary
Cached collator and sorting tests apps/web/src/lib/turnDiffTree.ts, apps/web/src/lib/turnDiffTree.test.ts	compareByName lazily initializes and reuses an Intl.Collator. Tests check numeric sorting with directories before files, plus input order for tied names at the root and nested-directory levels.

Priority: ⬇️ Low

Estimated code review effort: 2 (Simple) | ~5 minutes

Change: Refactor

Merge Risk: ⚪ Minimal · up to 3a236

This performance-focused change is mergeable with no identified correctness, availability, or data-integrity risk.

Pre-merge checks: 4

Check name	Status	Explanation
Title check		The title clearly and concisely describes the main performance change: reusing a collator when sorting changed-file trees.
Description check		The description includes all required sections and provides clear problem context, implementation details, scope rationale, focused verification results, benchmark methodology, tradeoffs, and agent at…
Linked Issues check		Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check		Check skipped because no linked issues were found for this pull request.

Full details: Description check

Explanation

The description includes all required sections and provides clear problem context, implementation details, scope rationale, focused verification results, benchmark methodology, tradeoffs, and agent attribution.

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