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docs(decompiler): add ruDevolution README with tutorials and feature comparison
Co-Authored-By: claude-flow <ruv@ruv.net>
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crates/ruvector-decompiler/README.md
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<p align="center">
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<strong>ruDevolution</strong>
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</p>
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<p align="center">
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<em>The first decompiler that understands code, proves its work, and learns from every run.</em>
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</p>
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<p align="center">
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🧠 MinCut Module Detection •
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🔮 AI Name Recovery •
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🔗 Cryptographic Witness Chains •
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📊 Confidence Scoring •
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🧬 Self-Learning
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</p>
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<p align="center">
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<img alt="Tests" src="https://img.shields.io/badge/tests-51_passing-brightgreen?style=flat-square" />
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<img alt="Patterns" src="https://img.shields.io/badge/patterns-210-blue?style=flat-square" />
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<img alt="License" src="https://img.shields.io/badge/license-MIT-blue?style=flat-square" />
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<img alt="Rust" src="https://img.shields.io/badge/rust-pure-orange?style=flat-square" />
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</p>
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---
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## 🧠 What is ruDevolution?
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**ruDevolution** turns scrambled, minified JavaScript back into readable, organized source code — then *proves* every step with cryptographic witness chains.
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Most decompilers just reformat code. ruDevolution **understands** it:
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```
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📦 Input (minified) 📖 Output (reconstructed)
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───────────────────── ──────────────────────────
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var a=function(b){ // Module: http-router (92% confidence)
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return b.c("d")}; var createRoute = function(request) {
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var e=class extends f{ return request.method("GET");
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constructor(){this.g="h"}} };
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// Module: base-component (88% confidence)
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var Component = class extends BaseElement {
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constructor() {
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this.tagName = "div";
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}
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}
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✅ Witness chain: a3f2c8...→ 7b1e9d...
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📋 Source map: output.js.map (V3)
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```
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---
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## ✨ Features
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| Feature | ruDevolution | Traditional Decompilers | Why It Matters |
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|---------|:-----------:|:----------------------:|----------------|
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| 🧩 **Module detection** | ✅ MinCut graph partitioning | ❌ None | Reconstructs original file structure |
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| 🔮 **Name recovery** | ✅ AI + 210 patterns | ⚠️ Generic (`a`, `b`, `c`) | Makes code actually readable |
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| 🧬 **Self-learning** | ✅ Gets smarter each run | ❌ Static rules | Accuracy improves over time |
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| 🔗 **Witness chains** | ✅ SHA3-256 Merkle proof | ❌ None | Proves output matches input |
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| 🗺️ **Source maps** | ✅ V3 (DevTools compatible) | ⚠️ Some | Debug in Chrome/VS Code |
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| 📊 **Confidence scores** | ✅ Per-name scoring | ❌ None | Know what to trust |
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| 🔄 **Cross-version analysis** | ✅ Compare releases | ❌ None | Track changes across versions |
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| 🏎️ **Performance** | ✅ 11MB in ~26s | ⚠️ Varies | Production-ready speed |
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| 🤖 **Neural inference** | ✅ GPU-trained model | ❌ None | Predicts original names |
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| 📦 **RVF containers** | ✅ Binary cognitive format | ❌ None | Portable, searchable, provable |
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---
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## 🚀 Quick Start
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### As a Rust library
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```rust
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use ruvector_decompiler::{decompile, DecompileConfig};
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let minified = std::fs::read_to_string("bundle.min.js").unwrap();
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let config = DecompileConfig::default();
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let result = decompile(&minified, &config).unwrap();
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println!("📦 {} modules detected", result.modules.len());
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println!("🔮 {} names inferred", result.inferred_names.len());
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println!("🔗 Witness root: {}", result.witness_chain.chain_root_hex);
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for module in &result.modules {
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println!(" 📁 {} ({} declarations)", module.name, module.declarations.len());
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}
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```
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### From the command line
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```bash
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# Decompile a minified bundle
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cargo run --release -p ruvector-decompiler --example run_on_cli -- bundle.min.js
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# Decompile Claude Code CLI
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cargo run --release -p ruvector-decompiler --example run_on_cli -- \
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$(npm root -g)/@anthropic-ai/claude-code/cli.js
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```
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### With the dashboard UI
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```bash
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cd examples/decompiler-dashboard
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npm install && npm run dev
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# Open http://localhost:5173 — paste any npm package name to decompile
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```
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---
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## 📊 Performance
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Tested on Claude Code `cli.js` (11 MB, 27,477 declarations):
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| Phase | Time | What It Does |
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|-------|------|-------------|
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| 🔍 Parse | 3.4s | Finds all declarations, strings, references |
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| 🕸️ Graph | 375ms | Builds 353K-edge reference graph |
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| ✂️ Partition | 929ms | Louvain detects 1,029 modules |
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| 🔮 Infer | 13.6s | Names 25,465 identifiers with confidence |
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| 🔗 Witness | <100ms | SHA3-256 Merkle chain |
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| **Total** | **~26s** | **Complete pipeline** |
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---
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## 🏗️ How It Works
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### The 5-Phase Pipeline
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```
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📄 Minified Bundle
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│
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▼
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┌─── Phase 1: Parse ───┐
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│ 🔍 Find declarations │ Regex + single-pass scanner
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│ 📝 Extract strings │ memchr SIMD acceleration
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│ 🔗 Map references │ Who calls whom?
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└───────────┬───────────┘
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▼
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┌─── Phase 2: Graph ───┐
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│ 🕸️ Build ref graph │ Nodes = declarations
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│ ⚖️ Weight edges │ Edges = reference frequency
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└───────────┬───────────┘
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▼
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┌─── Phase 3: Partition ─┐
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│ ✂️ MinCut / Louvain │ <5K nodes: exact MinCut
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│ 📁 Detect modules │ ≥5K nodes: Louvain O(n log n)
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│ 🏷️ Name modules │ Based on dominant strings
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└───────────┬────────────┘
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▼
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┌─── Phase 4: Infer ────┐
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│ 🤖 Neural model │ GPU-trained transformer
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│ 📚 Training corpus │ 210 domain patterns
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│ 🔤 Pattern matching │ String context + properties
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│ 📊 Confidence scoring │ HIGH / MEDIUM / LOW
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└───────────┬────────────┘
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▼
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┌─── Phase 5: Witness ──┐
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│ 🔗 SHA3-256 hashing │ Hash every module
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│ 🌳 Merkle tree │ Chain all hashes
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│ ✅ Verify: output ⊆ input │ Cryptographic proof
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└───────────┬────────────┘
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▼
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📖 Readable Source Code
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🗺️ V3 Source Map
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🔗 Witness Chain
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📊 Confidence Report
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```
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---
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## 📐 Confidence Levels
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Every inferred name gets a confidence score:
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| Level | Range | Meaning | Example |
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|-------|-------|---------|---------|
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| 🟢 **HIGH** | >90% | Direct string evidence | `"Bash"` in context → `bash_tool` |
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| 🟡 **MEDIUM** | 60-90% | Property/structural match | `.method`, `.path` → `route_handler` |
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| 🔴 **LOW** | <60% | Positional/generic | Near error patterns → `error_handler` |
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---
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<details>
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<summary><strong>📖 Tutorial: Decompile an npm Package</strong></summary>
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### Step 1: Get the minified bundle
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```bash
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npm pack express --pack-destination /tmp/
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tar xzf /tmp/express-*.tgz -C /tmp/
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```
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### Step 2: Run the decompiler
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```rust
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use ruvector_decompiler::{decompile, DecompileConfig};
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let source = std::fs::read_to_string("/tmp/package/index.js")?;
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let result = decompile(&source, &DecompileConfig::default())?;
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```
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### Step 3: Check the results
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```rust
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// How many modules were detected?
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println!("Modules: {}", result.modules.len());
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// What names were recovered?
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for name in result.inferred_names.iter().filter(|n| n.confidence > 0.8) {
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println!("{} → {} ({}%)", name.original, name.inferred,
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(name.confidence * 100.0) as u32);
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}
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// Verify the witness chain
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assert!(result.witness_chain.is_valid);
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```
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### Step 4: Use the source map
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The output includes a V3 source map compatible with Chrome DevTools:
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```javascript
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// In your browser console:
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//# sourceMappingURL=decompiled.js.map
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```
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</details>
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<details>
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<summary><strong>🔄 Tutorial: Cross-Version Analysis</strong></summary>
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### Compare Claude Code versions
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```bash
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# Build RVF corpus for all versions
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./scripts/claude-code-rvf-corpus.sh
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# Each version gets its own RVF container:
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# versions/v0.2.x/claude-code-v0.2.rvf (300 vectors)
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# versions/v1.0.x/claude-code-v1.0.rvf (482 vectors)
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# versions/v2.0.x/claude-code-v2.0.rvf (785 vectors)
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# versions/v2.1.x/claude-code-v2.1.rvf (2,068 vectors)
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```
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### Track what changed
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```rust
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// Decompile two versions
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let v1 = decompile(&v1_source, &config)?;
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let v2 = decompile(&v2_source, &config)?;
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// Functions with same structure but different minified names
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// = same original function, renamed by the bundler
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// This confirms name inferences across versions
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```
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</details>
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<details>
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<summary><strong>🧬 Tutorial: Self-Learning Feedback Loop</strong></summary>
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### Train from ground truth
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If you know the original source for a minified bundle:
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```rust
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use ruvector_decompiler::inferrer::NameInferrer;
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let mut inferrer = NameInferrer::new();
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// Provide known correct mappings
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let ground_truth = vec![
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("a$", "createRouter"),
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("b$", "handleRequest"),
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("c$", "sendResponse"),
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];
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// Train the inferrer
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inferrer.learn_from_ground_truth(&ground_truth);
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// Future inferences will be more accurate
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// The patterns are stored and reused
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```
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### Feed back real-world results
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```rust
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// After manual review, tell the inferrer what was correct
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let feedback = vec![
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Feedback { predicted: "error_handler", actual: "McpErrorHandler", was_correct: false },
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Feedback { predicted: "route_handler", actual: "routeHandler", was_correct: true },
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];
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inferrer.learn_from_feedback(&feedback);
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```
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</details>
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<details>
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<summary><strong>🔗 Tutorial: Witness Chain Verification</strong></summary>
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### Prove decompilation is faithful
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```rust
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let result = decompile(&source, &config)?;
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// The witness chain proves every output byte comes from the input
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assert!(result.witness_chain.is_valid);
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println!("Source hash: {}", result.witness_chain.source_hash_hex);
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println!("Chain root: {}", result.witness_chain.chain_root_hex);
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// Each module has its own witness
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for witness in &result.witness_chain.module_witnesses {
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println!(" {} byte_range={}..{} hash={}",
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witness.module_name,
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witness.byte_range.0, witness.byte_range.1,
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witness.content_hash_hex);
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}
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// Anyone can verify: reconstruct the Merkle tree and compare roots
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let verified = result.witness_chain.verify(&source);
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assert!(verified);
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```
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</details>
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<details>
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<summary><strong>🤖 Advanced: GPU-Trained Neural Inference</strong></summary>
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### Train a deobfuscation model
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```bash
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# Generate training data (10K+ minified→original pairs)
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node scripts/training/generate-deobfuscation-data.mjs
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# Launch GPU training on GCloud L4 (~$1.40, ~2 hours)
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./scripts/training/launch-gpu-training.sh --cloud
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# Export model to GGUF for RuvLLM
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python scripts/training/export-to-rvf.py
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```
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### Use the trained model
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```rust
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let config = DecompileConfig {
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model_path: Some("models/deobfuscator.gguf".into()),
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..Default::default()
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};
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let result = decompile(&source, &config)?;
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// Neural inference runs first, falls back to patterns
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// Expect 60-80% name accuracy vs 5% without model
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```
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### How the model works
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```
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Input: minified name "s$" + context ["tools/call", "initialize", ".client"]
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│
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▼
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┌──────────────┐
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│ 6M param │
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│ Transformer │ Character-level encoder
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│ (GGUF Q4) │ Trained on 100K+ pairs
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└──────┬───────┘
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│
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▼
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Output: "mcpToolDispatcher" (confidence: 0.87)
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```
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</details>
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<details>
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<summary><strong>📦 Advanced: RVF Container Integration</strong></summary>
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### Store decompiled code in RVF
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RVF (RuVector Format) containers store code as searchable vectors with cryptographic provenance:
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```bash
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# Build RVF containers for all Claude Code versions
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./scripts/claude-code-rvf-corpus.sh
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# Each .rvf file contains:
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# - HNSW-indexed vectors (semantic search)
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# - Witness chains (provenance)
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# - Manifest (metadata)
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# - Module segments (source code)
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```
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### Query the RVF corpus
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```javascript
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import { RvfDatabase } from '@ruvector/rvf';
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const db = await RvfDatabase.openReadonly('claude-code-v2.1.rvf');
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const results = await db.search('permission system', { limit: 5 });
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for (const hit of results) {
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console.log(`${hit.module} (score: ${hit.score.toFixed(3)})`);
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}
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```
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</details>
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<details>
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<summary><strong>⚙️ Advanced: Configuration Options</strong></summary>
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### DecompileConfig
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```rust
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let config = DecompileConfig {
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// Module detection
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target_modules: None, // Auto-detect (recommended)
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min_module_size: Some(3), // Minimum declarations per module
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// Name inference
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min_confidence: 0.3, // Minimum confidence to include
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model_path: None, // Path to neural model (optional)
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// Output
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generate_source_map: true, // V3 source maps
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beautify: true, // Indent and format output
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};
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```
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### Environment variables
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `DECOMPILER_THREADS` | CPU count | Rayon thread pool size |
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| `DECOMPILER_MODEL` | none | Path to GGUF model |
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| `DECOMPILER_MIN_CONFIDENCE` | 0.3 | Minimum confidence threshold |
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</details>
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---
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## 🏛️ Architecture
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```
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crates/ruvector-decompiler/
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├── src/
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│ ├── lib.rs # 🎯 Public API: decompile()
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│ ├── parser.rs # 🔍 Single-pass JS scanner (memchr + lookup table)
|
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│ ├── graph.rs # 🕸️ Reference graph construction
|
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│ ├── partitioner.rs # ✂️ MinCut + Louvain community detection
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│ ├── inferrer.rs # 🔮 Name inference (neural + patterns + learning)
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│ ├── training.rs # 🧬 Training corpus (210 patterns, JSON-loadable)
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│ ├── sourcemap.rs # 🗺️ V3 source map generation (VLQ encoding)
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│ ├── beautifier.rs # ✨ Code formatting and indentation
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│ ├── witness.rs # 🔗 SHA3-256 Merkle witness chains
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│ ├── types.rs # 📐 Core types and config
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│ └── error.rs # ❌ Error handling
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├── data/
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│ └── claude-code-patterns.json # 📚 210 domain-specific patterns
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├── tests/
|
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│ ├── integration.rs # ✅ 8 integration tests
|
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│ ├── ground_truth.rs # 🎯 5 fixture accuracy tests
|
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│ └── real_world.rs # 🌍 3 OSS comparison tests
|
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├── benches/
|
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│ ├── bench_parser.rs # ⚡ Parser benchmarks (1KB-1MB)
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│ └── bench_pipeline.rs # ⚡ Full pipeline benchmarks
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└── examples/
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└── run_on_cli.rs # 🖥️ CLI runner for real bundles
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```
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|
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---
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## 📚 Related
|
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|
||||
- [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/)
|
||||
|
||||
---
|
||||
|
||||
<p align="center">
|
||||
<em>ruDevolution — because code deserves to be understood.</em>
|
||||
</p>
|
||||
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