[xusd320]

Summary

SWC can emit @swc/helpers/_/_wrap_reg_exp when lowering regular expressions with named capture groups. Pack pins helpers 0.5.15, which does not export this helper, so affected modules fail to bundle with Module not found.

Changes

• Upgrade Pack's pinned @swc/helpers dependency from 0.5.15 to 0.5.23, which includes _wrap_reg_exp.

Validation

• biome check packages/pack/package.json: passed.
• Runtime smoke checks using helpers 0.5.23: named capture groups from exec() and named replacement groups both passed.
• Compared package exports: all 110 exports from helpers 0.5.15 are retained in 0.5.23.
• Production application build with published @utoo/pack@1.5.35 and the same helpers override: passed.
• Full Rust and Pack test suites: Not run; this change only updates the helper dependency.

Risk / rollout

Generated bundles use the updated helper implementations. No configuration or data migration is required.

Reviewer notes

The helper dependency remains pinned to an exact version. The repository ignores package-lock.json, so no lockfile is added.

[github-actions]

📊 Performance Benchmark Report (with-antd)

Utoopack Performance Report

Report ID: utoopack_performance_report_20261030_091835
Generated: 2026-10-30 09:18:35
Trace File: trace_antd.json (0.3GB, 0.85M spans)
Test Project: examples/with-antd

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Executive Summary

Metric	Value	Assessment
Total Wall Time	7,273.4 ms	Baseline
Total Thread Work (de-duped)	21,883.7 ms	Non-overlapping busy time
Effective Parallelism	3.0x	thread_work / wall_time
Working Threads	9	Threads with actual spans
Thread Utilization	33.4%	⚠️ Suboptimal
Total Spans	845,440	All B/E + X events
Meaningful Spans (>= 10us)	225,720	(26.7% of total)
Tracing Noise (< 10us)	619,720	(73.3% of total)

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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	49,272	7,022.0	1,951.2	3,453.5
Parse	8,196	1,559.5	1,175.6	6,532.1
Analyze	148,114	47,876.4	9,830.5	6,440.2
Chunk	5,336	6,406.5	1,073.8	2,685.2
Codegen	11,623	2,572.8	1,658.2	2,333.0
Emit	32	47.5	23.8	9.2
Other	3,147	7,987.0	4,526.6	7,273.4

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Workload Distribution by Diagnostic Tier

Category	Spans	Inclusive (ms)	% Work	Self-Time (ms)	% Self
P0: Scheduling & Resolution	197,816	55,590.8	254.0%	12,089.3	55.2%
P1: I/O & Heavy Tasks	2,893	138.0	0.6%	114.3	0.5%
P2: Architecture (Locks/Memory)	0	0.0	0.0%	0.0	0.0%
P3: Asset Pipeline	23,684	10,548.1	48.2%	3,902.8	17.8%
P4: Bridge/Interop	0	0.0	0.0%	0.0	0.0%
Other	1,327	7,194.8	32.9%	4,133.1	18.9%

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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
4,823.2	27,835.9	100,675	47.9	0.1	10.6	22.0%	module	module (61%)
2,750.0	2,940.8	18	152777.1	359.4	537.3	12.6%	save snapshot	persist (6%)
2,460.7	2,616.1	2,622	938.5	3.2	253.9	11.2%	analyze ecmascript module	module (68%)
1,656.7	16,296.4	35,212	47.1	0.1	5.3	7.6%	process module	process module (83%)
1,244.4	3,409.5	26,234	47.4	0.1	4.7	5.7%	internal resolving	internal resolving (76%)
1,101.4	1,485.3	6,018	183.0	0.7	48.0	5.0%	parse ecmascript	parse ecmascript (66%)
933.5	1,016.4	9,353	99.8	0.4	11.8	4.3%	precompute code generation	generate merged code (48%)
895.8	6,127.7	4,014	223.2	0.2	122.5	4.1%	chunking	chunking (56%)
764.7	896.2	7,009	109.1	0.4	147.6	3.5%	compute async module info	compute async module info (57%)
734.8	2,439.7	1,053	697.8	1.7	238.8	3.4%	generate merged code	chunking (43%)
690.5	3,596.2	22,355	30.9	0.0	4.8	3.2%	resolving	module (57%)
496.6	496.6	329	1509.6	1.2	299.8	2.3%	generate source map	code generation (83%)
433.4	896.9	132	3283.1	4.5	265.1	2.0%	emit code	generate merged code (42%)
365.3	652.1	1,380	264.7	0.1	213.6	1.7%	write all entrypoints to disk	write all entrypoints to disk (15%)
228.0	1,059.7	1,941	117.5	0.2	63.7	1.0%	code generation	code generation (84%)
192.3	192.3	7	27473.4	121.2	160.2	0.9%	blocking	save snapshot (43%)
173.4	273.9	1,233	140.6	0.1	34.9	0.8%	compute async chunks	compute async chunks (39%)
74.2	74.2	2,176	34.1	0.0	2.6	0.3%	read file	parse ecmascript (91%)
69.5	83.5	707	98.4	0.0	41.8	0.3%	compute binding usage info	compute binding usage info (53%)
38.8	70.7	1,869	20.8	0.0	12.6	0.2%	collect mergeable modules	collect mergeable modules (100%)

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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	697.5	3	persist → save snapshot → blocking
2	504.9	6	chunking → generate merged code → emit code → emit code → emit code → read file
3	350.6	4	chunking → generate merged code → emit code → generate source map
4	332.5	2	save snapshot → blocking
5	254.3	8	module → module → process module → process module → process module → process module → process module → analyze ecmascript module

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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	35,212	process module (83%)	47.1 us	0.07 ms	1,656.7 ms
internal resolving	26,234	internal resolving (76%)	47.4 us	0.09 ms	1,244.4 ms

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Duration Distribution

Range	Count	Percentage
<10us	619,720	73.3%
10us-100us	146,382	17.3%
100us-1ms	66,431	7.9%
1ms-10ms	12,645	1.5%
10ms-100ms	214	0.0%
>100ms	48	0.0%

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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