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+
+ ruDevolution
+
+
+
+ The first decompiler that understands code, proves its work, and learns from every run.
+
+
+
+ ๐ง MinCut Module Detection •
+ ๐ฎ AI Name Recovery •
+ ๐ Cryptographic Witness Chains •
+ ๐ Confidence Scoring •
+ ๐งฌ Self-Learning
+
+
+
+ 
+ 
+ 
+ 
+
+
+---
+
+## ๐ง What is ruDevolution?
+
+**ruDevolution** turns scrambled, minified JavaScript back into readable, organized source code โ then *proves* every step with cryptographic witness chains.
+
+Most decompilers just reformat code. ruDevolution **understands** it:
+
+```
+๐ฆ Input (minified) ๐ Output (reconstructed)
+โโโโโโโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโโโโโโโโโโ
+var a=function(b){ // Module: http-router (92% confidence)
+return b.c("d")}; var createRoute = function(request) {
+var e=class extends f{ return request.method("GET");
+constructor(){this.g="h"}} };
+
+ // Module: base-component (88% confidence)
+ var Component = class extends BaseElement {
+ constructor() {
+ this.tagName = "div";
+ }
+ }
+
+ โ
Witness chain: a3f2c8...โ 7b1e9d...
+ ๐ Source map: output.js.map (V3)
+```
+
+---
+
+## โจ Features
+
+| Feature | ruDevolution | Traditional Decompilers | Why It Matters |
+|---------|:-----------:|:----------------------:|----------------|
+| ๐งฉ **Module detection** | โ
MinCut graph partitioning | โ None | Reconstructs original file structure |
+| ๐ฎ **Name recovery** | โ
AI + 210 patterns | โ ๏ธ Generic (`a`, `b`, `c`) | Makes code actually readable |
+| ๐งฌ **Self-learning** | โ
Gets smarter each run | โ Static rules | Accuracy improves over time |
+| ๐ **Witness chains** | โ
SHA3-256 Merkle proof | โ None | Proves output matches input |
+| ๐บ๏ธ **Source maps** | โ
V3 (DevTools compatible) | โ ๏ธ Some | Debug in Chrome/VS Code |
+| ๐ **Confidence scores** | โ
Per-name scoring | โ None | Know what to trust |
+| ๐ **Cross-version analysis** | โ
Compare releases | โ None | Track changes across versions |
+| ๐๏ธ **Performance** | โ
11MB in ~26s | โ ๏ธ Varies | Production-ready speed |
+| ๐ค **Neural inference** | โ
GPU-trained model | โ None | Predicts original names |
+| ๐ฆ **RVF containers** | โ
Binary cognitive format | โ None | Portable, searchable, provable |
+
+---
+
+## ๐ Quick Start
+
+### As a Rust library
+
+```rust
+use ruvector_decompiler::{decompile, DecompileConfig};
+
+let minified = std::fs::read_to_string("bundle.min.js").unwrap();
+let config = DecompileConfig::default();
+let result = decompile(&minified, &config).unwrap();
+
+println!("๐ฆ {} modules detected", result.modules.len());
+println!("๐ฎ {} names inferred", result.inferred_names.len());
+println!("๐ Witness root: {}", result.witness_chain.chain_root_hex);
+
+for module in &result.modules {
+ println!(" ๐ {} ({} declarations)", module.name, module.declarations.len());
+}
+```
+
+### From the command line
+
+```bash
+# Decompile a minified bundle
+cargo run --release -p ruvector-decompiler --example run_on_cli -- bundle.min.js
+
+# Decompile Claude Code CLI
+cargo run --release -p ruvector-decompiler --example run_on_cli -- \
+ $(npm root -g)/@anthropic-ai/claude-code/cli.js
+```
+
+### With the dashboard UI
+
+```bash
+cd examples/decompiler-dashboard
+npm install && npm run dev
+# Open http://localhost:5173 โ paste any npm package name to decompile
+```
+
+---
+
+## ๐ Performance
+
+Tested on Claude Code `cli.js` (11 MB, 27,477 declarations):
+
+| Phase | Time | What It Does |
+|-------|------|-------------|
+| ๐ Parse | 3.4s | Finds all declarations, strings, references |
+| ๐ธ๏ธ Graph | 375ms | Builds 353K-edge reference graph |
+| โ๏ธ Partition | 929ms | Louvain detects 1,029 modules |
+| ๐ฎ Infer | 13.6s | Names 25,465 identifiers with confidence |
+| ๐ Witness | <100ms | SHA3-256 Merkle chain |
+| **Total** | **~26s** | **Complete pipeline** |
+
+---
+
+## ๐๏ธ How It Works
+
+### The 5-Phase Pipeline
+
+```
+๐ Minified Bundle
+ โ
+ โผ
+โโโโ Phase 1: Parse โโโโ
+โ ๐ Find declarations โ Regex + single-pass scanner
+โ ๐ Extract strings โ memchr SIMD acceleration
+โ ๐ Map references โ Who calls whom?
+โโโโโโโโโโโโโฌโโโโโโโโโโโโ
+ โผ
+โโโโ Phase 2: Graph โโโโ
+โ ๐ธ๏ธ Build ref graph โ Nodes = declarations
+โ โ๏ธ Weight edges โ Edges = reference frequency
+โโโโโโโโโโโโโฌโโโโโโโโโโโโ
+ โผ
+โโโโ Phase 3: Partition โโ
+โ โ๏ธ MinCut / Louvain โ <5K nodes: exact MinCut
+โ ๐ Detect modules โ โฅ5K nodes: Louvain O(n log n)
+โ ๐ท๏ธ Name modules โ Based on dominant strings
+โโโโโโโโโโโโโฌโโโโโโโโโโโโโ
+ โผ
+โโโโ Phase 4: Infer โโโโโ
+โ ๐ค Neural model โ GPU-trained transformer
+โ ๐ Training corpus โ 210 domain patterns
+โ ๐ค Pattern matching โ String context + properties
+โ ๐ Confidence scoring โ HIGH / MEDIUM / LOW
+โโโโโโโโโโโโโฌโโโโโโโโโโโโโ
+ โผ
+โโโโ Phase 5: Witness โโโ
+โ ๐ SHA3-256 hashing โ Hash every module
+โ ๐ณ Merkle tree โ Chain all hashes
+โ โ
Verify: output โ input โ Cryptographic proof
+โโโโโโโโโโโโโฌโโโโโโโโโโโโโ
+ โผ
+ ๐ Readable Source Code
+ ๐บ๏ธ V3 Source Map
+ ๐ Witness Chain
+ ๐ Confidence Report
+```
+
+---
+
+## ๐ Confidence Levels
+
+Every inferred name gets a confidence score:
+
+| Level | Range | Meaning | Example |
+|-------|-------|---------|---------|
+| ๐ข **HIGH** | >90% | Direct string evidence | `"Bash"` in context โ `bash_tool` |
+| ๐ก **MEDIUM** | 60-90% | Property/structural match | `.method`, `.path` โ `route_handler` |
+| ๐ด **LOW** | <60% | Positional/generic | Near error patterns โ `error_handler` |
+
+---
+
+
+๐ Tutorial: Decompile an npm Package
+
+### Step 1: Get the minified bundle
+
+```bash
+npm pack express --pack-destination /tmp/
+tar xzf /tmp/express-*.tgz -C /tmp/
+```
+
+### Step 2: Run the decompiler
+
+```rust
+use ruvector_decompiler::{decompile, DecompileConfig};
+
+let source = std::fs::read_to_string("/tmp/package/index.js")?;
+let result = decompile(&source, &DecompileConfig::default())?;
+```
+
+### Step 3: Check the results
+
+```rust
+// How many modules were detected?
+println!("Modules: {}", result.modules.len());
+
+// What names were recovered?
+for name in result.inferred_names.iter().filter(|n| n.confidence > 0.8) {
+ println!("{} โ {} ({}%)", name.original, name.inferred,
+ (name.confidence * 100.0) as u32);
+}
+
+// Verify the witness chain
+assert!(result.witness_chain.is_valid);
+```
+
+### Step 4: Use the source map
+
+The output includes a V3 source map compatible with Chrome DevTools:
+
+```javascript
+// In your browser console:
+//# sourceMappingURL=decompiled.js.map
+```
+
+
+
+
+๐ Tutorial: Cross-Version Analysis
+
+### Compare Claude Code versions
+
+```bash
+# Build RVF corpus for all versions
+./scripts/claude-code-rvf-corpus.sh
+
+# Each version gets its own RVF container:
+# versions/v0.2.x/claude-code-v0.2.rvf (300 vectors)
+# versions/v1.0.x/claude-code-v1.0.rvf (482 vectors)
+# versions/v2.0.x/claude-code-v2.0.rvf (785 vectors)
+# versions/v2.1.x/claude-code-v2.1.rvf (2,068 vectors)
+```
+
+### Track what changed
+
+```rust
+// Decompile two versions
+let v1 = decompile(&v1_source, &config)?;
+let v2 = decompile(&v2_source, &config)?;
+
+// Functions with same structure but different minified names
+// = same original function, renamed by the bundler
+// This confirms name inferences across versions
+```
+
+
+
+
+๐งฌ Tutorial: Self-Learning Feedback Loop
+
+### Train from ground truth
+
+If you know the original source for a minified bundle:
+
+```rust
+use ruvector_decompiler::inferrer::NameInferrer;
+
+let mut inferrer = NameInferrer::new();
+
+// Provide known correct mappings
+let ground_truth = vec![
+ ("a$", "createRouter"),
+ ("b$", "handleRequest"),
+ ("c$", "sendResponse"),
+];
+
+// Train the inferrer
+inferrer.learn_from_ground_truth(&ground_truth);
+
+// Future inferences will be more accurate
+// The patterns are stored and reused
+```
+
+### Feed back real-world results
+
+```rust
+// After manual review, tell the inferrer what was correct
+let feedback = vec![
+ Feedback { predicted: "error_handler", actual: "McpErrorHandler", was_correct: false },
+ Feedback { predicted: "route_handler", actual: "routeHandler", was_correct: true },
+];
+inferrer.learn_from_feedback(&feedback);
+```
+
+
+
+
+๐ Tutorial: Witness Chain Verification
+
+### Prove decompilation is faithful
+
+```rust
+let result = decompile(&source, &config)?;
+
+// The witness chain proves every output byte comes from the input
+assert!(result.witness_chain.is_valid);
+println!("Source hash: {}", result.witness_chain.source_hash_hex);
+println!("Chain root: {}", result.witness_chain.chain_root_hex);
+
+// Each module has its own witness
+for witness in &result.witness_chain.module_witnesses {
+ println!(" {} byte_range={}..{} hash={}",
+ witness.module_name,
+ witness.byte_range.0, witness.byte_range.1,
+ witness.content_hash_hex);
+}
+
+// Anyone can verify: reconstruct the Merkle tree and compare roots
+let verified = result.witness_chain.verify(&source);
+assert!(verified);
+```
+
+
+
+
+๐ค Advanced: GPU-Trained Neural Inference
+
+### Train a deobfuscation model
+
+```bash
+# Generate training data (10K+ minifiedโoriginal pairs)
+node scripts/training/generate-deobfuscation-data.mjs
+
+# Launch GPU training on GCloud L4 (~$1.40, ~2 hours)
+./scripts/training/launch-gpu-training.sh --cloud
+
+# Export model to GGUF for RuvLLM
+python scripts/training/export-to-rvf.py
+```
+
+### Use the trained model
+
+```rust
+let config = DecompileConfig {
+ model_path: Some("models/deobfuscator.gguf".into()),
+ ..Default::default()
+};
+
+let result = decompile(&source, &config)?;
+// Neural inference runs first, falls back to patterns
+// Expect 60-80% name accuracy vs 5% without model
+```
+
+### How the model works
+
+```
+Input: minified name "s$" + context ["tools/call", "initialize", ".client"]
+ โ
+ โผ
+ โโโโโโโโโโโโโโโโ
+ โ 6M param โ
+ โ Transformer โ Character-level encoder
+ โ (GGUF Q4) โ Trained on 100K+ pairs
+ โโโโโโโโฌโโโโโโโโ
+ โ
+ โผ
+Output: "mcpToolDispatcher" (confidence: 0.87)
+```
+
+
+
+
+๐ฆ Advanced: RVF Container Integration
+
+### Store decompiled code in RVF
+
+RVF (RuVector Format) containers store code as searchable vectors with cryptographic provenance:
+
+```bash
+# Build RVF containers for all Claude Code versions
+./scripts/claude-code-rvf-corpus.sh
+
+# Each .rvf file contains:
+# - HNSW-indexed vectors (semantic search)
+# - Witness chains (provenance)
+# - Manifest (metadata)
+# - Module segments (source code)
+```
+
+### Query the RVF corpus
+
+```javascript
+import { RvfDatabase } from '@ruvector/rvf';
+
+const db = await RvfDatabase.openReadonly('claude-code-v2.1.rvf');
+const results = await db.search('permission system', { limit: 5 });
+
+for (const hit of results) {
+ console.log(`${hit.module} (score: ${hit.score.toFixed(3)})`);
+}
+```
+
+
+
+
+โ๏ธ Advanced: Configuration Options
+
+### DecompileConfig
+
+```rust
+let config = DecompileConfig {
+ // Module detection
+ target_modules: None, // Auto-detect (recommended)
+ min_module_size: Some(3), // Minimum declarations per module
+
+ // Name inference
+ min_confidence: 0.3, // Minimum confidence to include
+ model_path: None, // Path to neural model (optional)
+
+ // Output
+ generate_source_map: true, // V3 source maps
+ beautify: true, // Indent and format output
+};
+```
+
+### Environment variables
+
+| Variable | Default | Description |
+|----------|---------|-------------|
+| `DECOMPILER_THREADS` | CPU count | Rayon thread pool size |
+| `DECOMPILER_MODEL` | none | Path to GGUF model |
+| `DECOMPILER_MIN_CONFIDENCE` | 0.3 | Minimum confidence threshold |
+
+
+
+---
+
+## ๐๏ธ Architecture
+
+```
+crates/ruvector-decompiler/
+โโโ src/
+โ โโโ lib.rs # ๐ฏ Public API: decompile()
+โ โโโ parser.rs # ๐ Single-pass JS scanner (memchr + lookup table)
+โ โโโ graph.rs # ๐ธ๏ธ Reference graph construction
+โ โโโ partitioner.rs # โ๏ธ MinCut + Louvain community detection
+โ โโโ inferrer.rs # ๐ฎ Name inference (neural + patterns + learning)
+โ โโโ training.rs # ๐งฌ Training corpus (210 patterns, JSON-loadable)
+โ โโโ sourcemap.rs # ๐บ๏ธ V3 source map generation (VLQ encoding)
+โ โโโ beautifier.rs # โจ Code formatting and indentation
+โ โโโ witness.rs # ๐ SHA3-256 Merkle witness chains
+โ โโโ types.rs # ๐ Core types and config
+โ โโโ error.rs # โ Error handling
+โโโ data/
+โ โโโ claude-code-patterns.json # ๐ 210 domain-specific patterns
+โโโ tests/
+โ โโโ integration.rs # โ
8 integration tests
+โ โโโ ground_truth.rs # ๐ฏ 5 fixture accuracy tests
+โ โโโ real_world.rs # ๐ 3 OSS comparison tests
+โโโ benches/
+โ โโโ bench_parser.rs # โก Parser benchmarks (1KB-1MB)
+โ โโโ bench_pipeline.rs # โก Full pipeline benchmarks
+โโโ examples/
+ โโโ run_on_cli.rs # ๐ฅ๏ธ CLI runner for real bundles
+```
+
+---
+
+## ๐ Related
+
+- [ADR-133: Claude Code Source Analysis](../../docs/adr/ADR-133-claude-code-source-analysis.md)
+- [ADR-134: RuVector Deep Integration](../../docs/adr/ADR-134-ruvector-claude-code-deep-integration.md)
+- [ADR-135: MinCut Decompiler Architecture](../../docs/adr/ADR-135-mincut-decompiler-with-witness-chains.md)
+- [ADR-136: GPU-Trained Deobfuscation Model](../../docs/adr/ADR-136-gpu-trained-deobfuscation-model.md)
+- [Research: SOTA Decompiler Approaches](../../docs/research/claude-code-rvsource/20-sota-decompiler-research.md)
+- [Research: Model Weight Analysis](../../docs/research/claude-code-rvsource/21-model-weight-analysis.md)
+- [Dashboard: Decompiler Explorer](../../examples/decompiler-dashboard/)
+
+---
+
+
+ ruDevolution โ because code deserves to be understood.
+