[fireairforce]

Summary

Production builds targeting older browsers can fail with Can't resolve '@swc/helpers/_/_wrap_reg_exp' when SWC lowers named RegExp capture groups. Pack still pins helpers to 0.5.15, which does not export the helper emitted by its compiler.

Pin @swc/helpers to 0.5.23 and add a real production-build regression covering named groups, backreferences, and named replacements. The test checks that the helper is emitted and executes the generated bundle.

Test Plan

• Reproduced the missing-helper failure with 0.5.15; the new regression passes with 0.5.23, using the published Pack 1.5.35 native binding for both runs.
• npm run build:js --workspace @utoo/pack
• npm test --workspace @utoo/pack-shared (6 tests passed)
• cargo fmt --check, npx tombi format --check, npx biome ci, typos, and git diff --check

[chatgpt-codex-connector]

Codex Review Summary

This comment shows the latest Codex review activity on this pull request.

Review	Status	Commit	Review trigger
📝 Code Review	✅ Completed 2026-10-30T08:54:48.055889Z	e927f9c	PR opened

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[github-actions]

📊 Performance Benchmark Report (with-antd)

Utoopack Performance Report

Report ID: utoopack_performance_report_20261030_091330
Generated: 2026-10-30 09:13:30
Trace File: trace_antd.json (0.3GB, 0.84M spans)
Test Project: examples/with-antd

---

Executive Summary

Metric	Value	Assessment
Total Wall Time	8,439.1 ms	Baseline
Total Thread Work (de-duped)	26,999.4 ms	Non-overlapping busy time
Effective Parallelism	3.2x	thread_work / wall_time
Working Threads	10	Threads with actual spans
Thread Utilization	32.0%	⚠️ Suboptimal
Total Spans	843,911	All B/E + X events
Meaningful Spans (>= 10us)	239,075	(28.3% of total)
Tracing Noise (< 10us)	604,836	(71.7% of total)

---

Build Phase Timeline

Shows when each build phase is active and how much CPU it consumes.
Self-Time is the time spent exclusively in that phase (excluding children).

Phase	Spans	Inclusive (ms)	Self-Time (ms)	Wall Range (ms)
Resolve	51,372	9,423.8	2,776.8	4,616.5
Parse	8,184	1,721.3	1,278.4	7,724.8
Analyze	154,181	61,811.4	13,900.0	7,636.7
Chunk	5,422	7,610.3	1,219.1	2,776.5
Codegen	16,074	2,944.4	1,865.8	2,346.2
Emit	29	44.7	22.4	9.8
Other	3,813	7,756.9	4,329.5	8,439.0

---

Workload Distribution by Diagnostic Tier

Category	Spans	Inclusive (ms)	% Work	Self-Time (ms)	% Self
P0: Scheduling & Resolution	206,401	71,860.9	266.2%	16,919.4	62.7%
P1: I/O & Heavy Tasks	2,889	132.6	0.5%	110.2	0.4%
P2: Architecture (Locks/Memory)	0	0.0	0.0%	0.0	0.0%
P3: Asset Pipeline	28,287	12,306.0	45.6%	4,369.0	16.2%
P4: Bridge/Interop	0	0.0	0.0%	0.0	0.0%
Other	1,498	7,013.5	26.0%	3,993.3	14.8%

---

Top 20 Tasks by Self-Time

Self-time is the exclusive duration: time spent in the task itself, not in sub-tasks.
This is the most accurate indicator of where CPU cycles are actually spent.

Self (ms)	Inclusive (ms)	Count	Avg Self (us)	P95 Self (ms)	Max Self (ms)	% Work	Task Name	Top Caller
7,306.3	38,320.9	104,992	69.6	0.1	16.2	27.1%	module	module (64%)
3,060.0	3,253.3	2,604	1175.1	4.2	336.1	11.3%	analyze ecmascript module	module (67%)
2,654.6	2,811.8	17	156154.0	374.2	514.9	9.8%	save snapshot	persist (6%)
2,264.8	18,611.2	36,504	62.0	0.1	8.8	8.4%	process module	process module (82%)
1,757.9	4,425.6	28,048	62.7	0.1	6.1	6.5%	internal resolving	internal resolving (77%)
1,207.2	1,650.1	6,014	200.7	0.8	46.2	4.5%	parse ecmascript	parse ecmascript (65%)
1,115.0	1,233.9	13,732	81.2	0.4	9.8	4.1%	precompute code generation	generate merged code (39%)
1,105.7	1,291.1	7,416	149.1	0.7	122.2	4.1%	compute async module info	compute async module info (57%)
1,071.3	7,339.9	4,085	262.3	0.6	109.3	4.0%	chunking	chunking (52%)
1,002.3	4,981.6	22,634	44.3	0.0	6.0	3.7%	resolving	module (56%)
771.6	2,488.0	1,237	623.7	1.4	206.1	2.9%	generate merged code	chunking (35%)
482.8	482.8	329	1467.5	1.5	283.1	1.8%	generate source map	code generation (83%)
386.0	854.9	134	2880.4	5.0	216.0	1.4%	emit code	emit code (43%)
313.6	670.0	1,828	171.5	0.1	160.4	1.2%	write all entrypoints to disk	write all entrypoints to disk (17%)
268.0	1,227.7	2,013	133.1	0.3	56.2	1.0%	code generation	code generation (83%)
157.3	157.3	5	31453.3	121.4	150.3	0.6%	blocking	save snapshot (80%)
143.3	265.3	1,278	112.1	0.1	13.5	0.5%	compute async chunks	compute async chunks (39%)
76.9	101.2	777	99.0	0.1	35.4	0.3%	compute binding usage info	compute binding usage info (51%)
72.8	124.2	1,871	38.9	0.0	26.5	0.3%	collect mergeable modules	collect mergeable modules (100%)
71.1	71.1	2,168	32.8	0.0	3.1	0.3%	read file	parse ecmascript (91%)

---

Critical Path Analysis

The longest sequential dependency chains that determine wall-clock time.
Focus on reducing the depth of these chains to improve parallelism.

Rank	Self-Time (ms)	Depth	Path
1	665.3	3	persist → save snapshot → blocking
2	423.3	6	chunking → generate merged code → emit code → emit code → emit code → read file
3	339.3	10	module → module → module → ... → process module → analyze ecmascript module → analyze ecmascript module
4	325.5	4	chunking → generate merged code → emit code → generate source map
5	241.5	4	process module → process module → analyze ecmascript module → analyze ecmascript module

---

Batching Candidates

High-volume tasks dominated by a single parent. If the parent can batch them,
it drastically reduces scheduler overhead.

Task Name	Count	Top Caller (Attribution)	Avg Self	P95 Self	Total Self
process module	36,504	process module (82%)	62.0 us	0.08 ms	2,264.8 ms
internal resolving	28,048	internal resolving (77%)	62.7 us	0.10 ms	1,757.9 ms

---

Duration Distribution

Range	Count	Percentage
<10us	604,836	71.7%
10us-100us	155,424	18.4%
100us-1ms	66,142	7.8%
1ms-10ms	17,121	2.0%
10ms-100ms	342	0.0%
>100ms	46	0.0%

---

Action Items

1. [P0] Focus on tasks with the highest Self-Time — these are where CPU cycles are actually spent.
2. [P0] Use Batching Candidates to identify callers that should use try_join or reduce #[turbo_tasks::function] granularity.
3. [P1] Check Build Phase Timeline for phases with disproportionate wall range vs. self-time (= serialization).
4. [P1] Inspect P95 Self (ms) for heavy monolith tasks. Focus on long-tail outliers, not averages.
5. [P1] Review Critical Paths — reducing the longest chain depth directly improves wall-clock time.
6. [P2] If Thread Utilization < 60%, investigate scheduling gaps (lock contention or deep dependency chains).

Report generated by Utoopack Performance Analysis Agent