fix(wasm-fs): simplify error translation and reorganize polyfills

[xusd320]

Implemented standard Node.js error translation and reorganized polyfills into a dedicated fs directory.

[gemini-code-assist]

Summary of Changes

Hello @xusd320, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request refactors the WebAssembly file system polyfills to enhance error handling and code organization. It introduces a standardized error translation mechanism to align with Node.js error conventions, making the file system interactions more predictable. Concurrently, the file system polyfills have been moved into a dedicated fs directory, improving the overall structure and maintainability of the codebase.

Highlights

• Standardized Error Translation: Implemented a translateError utility to convert internal WebAssembly file system errors into standard Node.js error objects (e.g., ENOENT), improving consistency and debuggability for file operations.
• Polyfill Reorganization: Consolidated all file system (fs) related polyfills into a new, dedicated fs subdirectory (packages/utoo-web/src/webpackLoaders/polyfills/fs/) for better modularity and maintainability.
• WASM Binding Updates: The index.d.ts file was updated to reflect changes in the WebAssembly module's exposed functions, including reordering some InitOutput properties and updating wasm_bindgen closure definitions.

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[gemini-code-assist]

Code Review

This pull request effectively refactors the wasm-fs polyfills by organizing them into a dedicated fs directory and implementing standard Node.js error translation. These changes improve the code's modularity and make error handling more robust and predictable. My review includes a few points to fix a bug in rmSync and to improve maintainability by reducing code duplication.

[github-actions]

📊 Performance Benchmark Report (with-antd)

🚀 Utoopack Performance Report: Async Task Scheduling Overhead Analysis

Report ID: utoopack_performance_report_20260129_151126
Generated: 2026-01-29 15:11:26
Trace File: trace_antd.json (1.5GB, 8.00M events)
Test Project: Unknown Project

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📊 Executive Summary

This report analyzes the performance of Utoopack/Turbopack, covering the full spectrum of the Performance Analysis Protocol (P0-P4).

Key Findings

Metric	Value	Assessment
Total Wall Time	10,018.0 ms	Baseline
Total Thread Work	87,819.5 ms	~8.8x parallelism
Thread Utilization	67.4%	🆗 Average
turbo_tasks::function Invocations	3,881,736	Total count
Meaningful Tasks (≥ 10µs)	1,515,986	(39.1% of total)
Tracing Noise (< 10µs)	2,365,750	(60.9% of total)

Workload Distribution by Tier

Category	Tasks	Total Time (ms)	% of Work
P0: Runtime/Resolution	1,038,443	52,971.7	60.3%
P1: I/O & Heavy Tasks	36,579	3,464.6	3.9%
P3: Asset Pipeline	27,829	4,211.6	4.8%
P4: Bridge/Interop	0	0.0	0.0%
Other	413,135	19,759.8	22.5%

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⚡ Parallelization Analysis (P0-P2)

Thread Utilization

Metric	Value
Number of Threads	13
Total Thread Work	87,819.5 ms
Avg Work per Thread	6,755.3 ms
Theoretical Parallelism	8.77x
Thread Utilization	67.4%

Assessment: With 13 threads available, achieving 8.8x parallelism indicates significant loss of potential parallelism.

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📈 Top 20 Tasks (Global)

These are the most significant tasks by total duration:

Total (ms)	Count	Avg (µs)	% Work	Task Name
43,884.0	865,102	50.7	50.0%	turbo_tasks::function
8,246.9	124,288	66.4	9.4%	task execution completed
6,416.2	80,745	79.5	7.3%	turbo_tasks::resolve_call
2,942.1	31,690	92.8	3.4%	analyze ecmascript module
2,259.0	67,198	33.6	2.6%	precompute code generation
2,140.1	67,692	31.6	2.4%	resolving
1,753.0	20,102	87.2	2.0%	effects processing
1,717.8	35,312	48.6	2.0%	module
1,559.8	11,734	132.9	1.8%	process parse result
1,104.1	31,224	35.4	1.3%	process module
1,068.3	6,340	168.5	1.2%	parse ecmascript
1,031.0	35,586	29.0	1.2%	internal resolving
844.2	28,304	29.8	1.0%	resolve_relative_request
570.0	1,910	298.5	0.6%	analyze variable values
525.4	19,179	27.4	0.6%	handle_after_resolve_plugins
476.8	15,465	30.8	0.5%	resolve_module_request
469.6	10,911	43.0	0.5%	code generation
413.0	17,429	23.7	0.5%	resolved
408.2	1,933	211.2	0.5%	swc_parse
352.5	4,210	83.7	0.4%	read file

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🔍 Deep Dive by Tier

🔴 Tier 1: Runtime & Resolution (P0)

Focus: Task scheduling and dependency resolution.

Metric	Value	Status
Total Scheduling Time	52,971.7 ms	⚠️ High
Resolution Hotspots	9 tasks	🔍 Check Top Tasks

Potential P0 Issues:

• Low thread utilization (67.4%) suggests critical path serialization or lock contention.
• 2,365,750 tasks < 10µs (60.9%) contribute to scheduler pressure.

🟠 Tier 2: Physical & Resource Barriers (P1)

Focus: Hardware utilization, I/O, and heavy monoliths.

Metric	Value	Status
I/O Work (Estimated)	3,464.6 ms	✅ Healthy
Large Tasks (> 100ms)	16	🚨 Critical

Potential P1 Issues:

• 16 tasks exceed 100ms. These "Heavy Monoliths" are prime candidates for splitting.

🟡 Tier 3: Architecture & Asset Pipeline (P2-P3)

Focus: Global state and transformation pipeline.

Metric	Value	Status
Asset Processing (P3)	4,211.6 ms	4.8% of work
Bridge Overhead (P4)	0.0 ms	✅ Low

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💡 Recommendations (Prioritized P0-P2)

🚨 Critical: (P0) Improvement

Problem: 67.4% thread utilization.
Action:

1. Profile lock contention if utilization < 60%.
2. Convert sequential await chains to try_join.

⚠️ High Priority: (P1) Optimization

Problem: 16 heavy tasks detected.
Action:

1. Identify module-level bottlenecks (e.g., barrel files).
2. Optimize I/O batching for metadata.

⚠️ Medium Priority: (P3) Pipeline Efficiency

Action:

1. Review transformation logic for frequently changed assets.
2. Minimize cross-language serialization (P4) if overhead exceeds 10%.

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📐 Diagnostic Signal Summary

Signal	Status	Finding
Tracing Noise (P0)	⚠️ Significant	60.9% of tasks < 10µs
Thread Utilization (P0)	✅ Good	67.4% utilization
Heavy Monoliths (P1)	⚠️ Detected	16 tasks > 100ms
Asset Pipeline (P3)	🔍 Review	4,211.6 ms total
Bridge/Interop (P4)	✅ Low	0.0 ms total

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🎯 Action Items (Comprehensive P0-P4)

1. [P0] Profile lock contention to address 32% lost parallelism
2. [P1] Breakdown heavy monolith tasks (>100ms) to improve granularity
3. [P1] Review I/O patterns for potential batching opportunities
4. [P3] Optimize asset transformation pipeline hot-spots
5. [P4] Reduce "chatty" bridge operations if interop overhead is significant

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Report generated by Utoopack Performance Analysis Agent on 2026-01-29
Following: Utoopack Performance Analysis Agent Protocol