[fireairforce]

IE11 UMD builds could emit arrows or require unsupported runtime APIs. Preserve strict for-of behavior with IE-targeted fallbacks and support dynamic CommonJS star re-exports with live getters without Proxy.

Runtime dependency: utooland/next.js#204. Refresh the affected generated snapshots, including content hashes, source maps and stats.

Validation: all 158 Pack snapshot tests and 2 integration tests; full minified UMD ES5 parsing and VM assertions without Symbol, URL, Proxy or includes; format, Biome, Tombi and typos. IE11 browser execution remains untested.

[github-actions]

📊 Performance Benchmark Report (with-antd)

Utoopack Performance Report

Report ID: utoopack_performance_report_20261014_135527
Generated: 2026-10-14 13:55:27
Trace File: trace_antd.json (0.3GB, 0.84M spans)
Test Project: examples/with-antd

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Executive Summary

Metric	Value	Assessment
Total Wall Time	7,278.3 ms	Baseline
Total Thread Work (de-duped)	21,463.9 ms	Non-overlapping busy time
Effective Parallelism	2.9x	thread_work / wall_time
Working Threads	10	Threads with actual spans
Thread Utilization	29.5%	⚠️ Suboptimal
Total Spans	844,913	All B/E + X events
Meaningful Spans (>= 10us)	222,173	(26.3% of total)
Tracing Noise (< 10us)	622,740	(73.7% 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	48,661	6,778.7	1,898.9	3,345.5
Parse	8,169	1,576.7	1,166.4	6,519.1
Analyze	143,629	43,481.9	9,587.9	6,430.7
Chunk	5,553	5,918.8	860.0	2,702.0
Codegen	12,937	2,614.9	1,705.2	2,286.8
Emit	33	41.3	20.7	8.6
Other	3,191	8,303.6	4,591.2	7,278.3

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Workload Distribution by Diagnostic Tier

Category	Spans	Inclusive (ms)	% Work	Self-Time (ms)	% Self
P0: Scheduling & Resolution	192,770	50,896.5	237.1%	11,755.6	54.8%
P1: I/O & Heavy Tasks	2,902	134.9	0.6%	114.2	0.5%
P2: Architecture (Locks/Memory)	0	0.0	0.0%	0.0	0.0%
P3: Asset Pipeline	25,235	10,177.0	47.4%	3,782.4	17.6%
P4: Bridge/Interop	0	0.0	0.0%	0.0	0.0%
Other	1,266	7,507.7	35.0%	4,178.0	19.5%

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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
4,568.2	25,274.3	97,167	47.0	0.1	13.8	21.3%	module	module (60%)
2,575.8	3,006.4	24	107325.0	355.3	456.1	12.0%	save snapshot	persist (4%)
2,467.1	2,587.6	2,410	1023.7	3.1	378.0	11.5%	analyze ecmascript module	module (72%)
1,517.9	14,320.4	34,278	44.3	0.1	6.8	7.1%	process module	process module (81%)
1,224.9	3,271.1	25,921	47.3	0.1	5.1	5.7%	internal resolving	internal resolving (75%)
1,088.2	1,498.6	5,999	181.4	0.7	74.9	5.1%	parse ecmascript	parse ecmascript (66%)
959.1	1,036.8	10,638	90.2	0.4	6.5	4.5%	precompute code generation	generate merged code (48%)
828.1	941.4	7,148	115.8	0.4	178.9	3.9%	compute async module info	compute async module info (57%)
732.9	2,428.1	988	741.8	1.7	291.9	3.4%	generate merged code	chunking (45%)
665.0	5,518.1	4,110	161.8	0.2	42.5	3.1%	chunking	chunking (51%)
658.6	3,492.2	22,041	29.9	0.0	4.4	3.1%	resolving	module (57%)
516.7	516.7	329	1570.6	1.2	278.1	2.4%	generate source map	code generation (83%)
432.6	432.6	9	48063.8	211.9	243.3	2.0%	blocking	save snapshot (67%)
406.6	881.3	129	3152.3	5.0	237.7	1.9%	emit code	generate merged code (41%)
382.3	661.4	1,521	251.3	0.1	230.4	1.8%	write all entrypoints to disk	write all entrypoints to disk (12%)
229.4	1,061.4	1,970	116.4	0.2	56.5	1.1%	code generation	code generation (84%)
190.8	396.0	1,374	138.9	0.2	26.4	0.9%	compute async chunks	compute async chunks (43%)
129.0	144.7	746	172.9	0.0	51.2	0.6%	compute binding usage info	compute binding usage info (51%)
78.1	78.1	2,167	36.0	0.1	2.2	0.4%	read file	parse ecmascript (91%)
60.7	108.9	1,861	32.6	0.0	16.9	0.3%	collect mergeable modules	collect mergeable modules (98%)

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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	699.6	3	persist → save snapshot → blocking
2	533.2	6	chunking → generate merged code → emit code → emit code → emit code → read file
3	378.2	3	process module → process module → analyze ecmascript module
4	366.9	2	save snapshot → blocking
5	325.6	4	chunking → generate merged code → emit code → generate source map

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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	34,278	process module (81%)	44.3 us	0.07 ms	1,517.9 ms
internal resolving	25,921	internal resolving (75%)	47.3 us	0.09 ms	1,224.9 ms

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Duration Distribution

Range	Count	Percentage
<10us	622,740	73.7%
10us-100us	144,320	17.1%
100us-1ms	65,925	7.8%
1ms-10ms	11,688	1.4%
10ms-100ms	201	0.0%
>100ms	39	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