[fireairforce]

Fix React is not defined in classic JSX when provider.React is configured, including the equivalent case for custom JSX factories.

Update the next.js submodule to consume the Turbopack free-variable analysis fix. It identifies unbound transformed references during existing AST traversal so providers can resolve them. Add browser and Node regression snapshots using dummy runtimes.

Validation:

• Seven focused analyzer tests, browser/Node snapshots, and 52 execution cases passed; formatting and Clippy passed.
• Full Turbopack library: 599/603 tests passed, with four preexisting snapshot mismatches.
• Synthetic benchmarks (12 interleaved rounds per workload) showed timing and peak RSS differences comparable to measurement variation.

[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 2026-10-30T03:45:33.995557Z	5d79456	PR opened

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[github-actions]

📊 Performance Benchmark Report (with-antd)

Utoopack Performance Report

Report ID: utoopack_performance_report_20261030_062827
Generated: 2026-10-30 06:28:27
Trace File: trace_antd.json (0.3GB, 0.85M spans)
Test Project: examples/with-antd

---

Executive Summary

Metric	Value	Assessment
Total Wall Time	7,473.6 ms	Baseline
Total Thread Work (de-duped)	23,257.3 ms	Non-overlapping busy time
Effective Parallelism	3.1x	thread_work / wall_time
Working Threads	10	Threads with actual spans
Thread Utilization	31.1%	⚠️ Suboptimal
Total Spans	846,370	All B/E + X events
Meaningful Spans (>= 10us)	198,715	(23.5% of total)
Tracing Noise (< 10us)	647,655	(76.5% 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	41,019	5,658.9	1,511.3	2,776.4
Parse	8,179	1,188.3	887.3	5,413.2
Analyze	132,444	36,443.2	7,851.6	5,329.8
Chunk	5,126	5,136.5	785.8	2,285.3
Codegen	9,274	2,120.0	1,354.5	1,948.6
Emit	29	40.5	20.3	8.2
Other	2,644	13,397.9	9,254.1	7,473.5

---

Workload Distribution by Diagnostic Tier

Category	Spans	Inclusive (ms)	% Work	Self-Time (ms)	% Self
P0: Scheduling & Resolution	173,793	42,652.8	183.4%	9,648.6	41.5%
P1: I/O & Heavy Tasks	2,777	104.1	0.4%	83.9	0.4%
P2: Architecture (Locks/Memory)	0	0.0	0.0%	0.0	0.0%
P3: Asset Pipeline	21,041	8,454.9	36.4%	3,025.8	13.0%
P4: Bridge/Interop	0	0.0	0.0%	0.0	0.0%
Other	1,104	12,773.4	54.9%	8,906.6	38.3%

---

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
7,826.5	7,897.0	16	489159.1	1,567.6	1,953.1	33.7%	save snapshot	persist (6%)
3,962.8	21,733.1	89,936	44.1	0.1	25.6	17.0%	module	module (60%)
1,866.0	1,976.8	2,501	746.1	2.5	184.9	8.0%	analyze ecmascript module	module (70%)
1,239.1	11,717.4	31,496	39.3	0.1	6.6	5.3%	process module	process module (80%)
1,001.2	2,733.5	22,120	45.3	0.1	3.5	4.3%	internal resolving	internal resolving (72%)
831.0	1,132.0	6,003	138.4	0.5	40.1	3.6%	parse ecmascript	parse ecmascript (66%)
780.7	847.9	7,193	108.5	0.4	5.9	3.4%	precompute code generation	generate merged code (52%)
685.1	827.4	6,102	112.3	0.4	152.5	2.9%	compute async module info	compute async module info (53%)
648.3	4,845.5	3,969	163.3	0.2	40.5	2.8%	chunking	chunking (60%)
636.8	2,034.2	875	727.7	1.7	239.3	2.7%	generate merged code	chunking (56%)
502.9	2,918.1	18,327	27.4	0.0	3.2	2.2%	resolving	module (64%)
395.2	395.2	329	1201.2	0.9	233.6	1.7%	generate source map	code generation (83%)
353.2	724.7	130	2716.6	4.3	215.0	1.5%	emit code	generate merged code (42%)
325.7	550.7	1,139	286.0	0.1	196.9	1.4%	write all entrypoints to disk	write all entrypoints to disk (9%)
178.6	876.9	1,752	101.9	0.2	51.9	0.8%	code generation	code generation (82%)
134.2	287.4	1,103	121.7	0.1	23.5	0.6%	compute async chunks	compute async chunks (45%)
71.7	71.7	7	10238.5	45.1	61.9	0.3%	blocking	save snapshot (57%)
56.3	56.3	2,173	25.9	0.0	1.0	0.2%	read file	parse ecmascript (91%)
54.5	66.5	638	85.4	0.0	33.1	0.2%	compute binding usage info	compute binding usage info (53%)
31.5	58.3	1,755	18.0	0.0	10.8	0.1%	collect mergeable modules	collect mergeable modules (100%)

---

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	2,015.0	3	persist → save snapshot → blocking
2	454.9	6	chunking → generate merged code → emit code → emit code → emit code → read file
3	278.8	4	chunking → generate merged code → emit code → generate source map
4	185.4	9	module → module → process module → ... → process module → analyze ecmascript module → analyze ecmascript module
5	177.0	3	process module → process 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	31,496	process module (80%)	39.3 us	0.06 ms	1,239.1 ms
internal resolving	22,120	internal resolving (72%)	45.3 us	0.08 ms	1,001.2 ms

---

Duration Distribution

Range	Count	Percentage
<10us	647,655	76.5%
10us-100us	126,245	14.9%
100us-1ms	62,868	7.4%
1ms-10ms	9,393	1.1%
10ms-100ms	173	0.0%
>100ms	36	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