# Native C++ Libraries

High-performance C++ libraries for critical system components.

## Overview

This directory contains selective C++ optimizations for the highest-impact performance bottlenecks. Not all operations warrant C++ implementation - only those with clear orders-of-magnitude improvements.

## Current Libraries

### queue_index (Priority Queue Index)
- **Purpose**: High-performance task queue with binary heap
- **Performance**: 21,000x faster than JSON-based Go implementation
- **Memory**: 99% allocation reduction
- **Security**: CVE-2024-45339, CVE-2025-47290, CVE-2025-0838 mitigations applied
- **Status**: ✅ Production ready

### dataset_hash (SHA256 Hashing)
- **Purpose**: SIMD-accelerated file hashing (ARMv8 crypto / Intel SHA-NI)
- **Performance**: 78% syscall reduction, batch-first API
- **Memory**: 99% less memory than Go implementation
- **Research**: Deterministic sorted hashing, recursive directory traversal
- **Status**: ✅ Production ready for research use

## Security

### CVE Mitigations Applied

| CVE | Description | Mitigation |
|-----|-------------|------------|
| CVE-2024-45339 | Symlink attack on temp files | `O_EXCL` flag with retry-on-EEXIST |
| CVE-2025-47290 | TOCTOU race in file open | `openat_nofollow()` via path_sanitizer |
| CVE-2025-0838 | Integer overflow in batch ops | `MAX_BATCH_SIZE = 10000` limit |

### Research Trustworthiness

**Critical Design Decisions for Research Use:**

For dataset hashing to be trustworthy in research, it must be **reproducible**. The original `collect_files` used `readdir()` which returns files in filesystem-dependent order — inode order on ext4, creation order on others, essentially random on network filesystems. This meant researchers hashing the same dataset on different machines would get different combined hashes for identical content, breaking cross-collaborator verification.

**The fix:** `std::sort(paths.begin(), paths.end())` after collection ensures lexicographic ordering. The hash is computed over sorted file paths, making it reproducible across machines and time.

**Behavior Summary:**
- **Deterministic ordering**: Files sorted lexicographically before hashing
- **Recursive traversal**: Nested directories fully hashed (max depth 32 with cycle detection)
- **Reproducible**: Same dataset produces identical hash across machines and filesystems

**Documented Exclusions (intentional, not bugs):**
- **Hidden files** (names starting with `.`) are excluded — if your dataset has `.data` files or dotfiles that are part of the data, they will be silently skipped
- **Special files** (symlinks, devices, sockets) are excluded — only regular files (`S_ISREG`) are hashed
- **Non-regular entries** in subdirectories are silently skipped

These exclusions were conscious design choices for security (symlink attack prevention) and predictability. However, researchers must be aware: a dataset directory with only hidden files or non-regular files will produce an empty hash, not an error. Verify your dataset structure matches expectations.

## Build Requirements

- CMake 3.20+
- C++20 compiler (GCC 11+, Clang 14+, or MSVC 2022+)
- Go 1.25+ (for CGo integration)

## Quick Start

```bash
# Build all native libraries
make native-build

# Run with native libraries enabled (using -tags native_libs)
go build -tags native_libs ./...

# Run benchmarks
go test -tags native_libs -bench=. ./tests/benchmarks/
```

## Test Coverage

```bash
make native-test
```

**8/8 tests passing:**
- `storage_smoke` - Basic storage operations
- `dataset_hash_smoke` - Hashing correctness
- `storage_init_new_dir` - Directory creation
- `parallel_hash_large_dir` - 300+ file handling
- `queue_index_compact` - Compaction operations
- `sha256_arm_kat` - ARMv8 SHA256 verification
- `storage_symlink_resistance` - CVE-2024-45339 verification
- `queue_index_batch_limit` - CVE-2025-0838 verification

## Build Options

```bash
# Debug build with AddressSanitizer
cd native/build && cmake .. -DCMAKE_BUILD_TYPE=Debug -DENABLE_ASAN=ON

# Release build (optimized)
cd native/build && cmake .. -DCMAKE_BUILD_TYPE=Release

# Build specific library
cd native/build && make queue_index
```

## Architecture

### Design Principles

1. **Selective optimization**: Only 2 libraries out of 80+ profiled functions
2. **Batch-first APIs**: Minimize CGo overhead (~100ns/call)
3. **Zero-allocation hot paths**: Arena allocators, no malloc in critical sections
4. **C ABI for CGo**: Simple C structs, no C++ exceptions across boundary
5. **Cross-platform**: Runtime SIMD detection (ARMv8 / x86_64 SHA-NI)

### CGo Integration

```go
// #cgo LDFLAGS: -L${SRCDIR}/../../native/build -lqueue_index
// #include "../../native/queue_index/queue_index.h"
import "C"
```

### Error Handling

- C functions return `-1` for errors, positive values for success
- Use `qi_last_error()` / `fh_last_error()` for error messages
- Go code checks `rc < 0` not `rc != 0`

## When to Add New C++ Libraries

**DO implement when:**
- Profile shows >90% syscall overhead
- Batch operations amortize CGo cost
- SIMD can provide 3x+ speedup
- Memory pressure is critical

**DON'T implement when:**
- Speedup <2x (CGo overhead negates gains)
- Single-file operations (per-call overhead too high)
- Team <3 backend engineers (maintenance burden)
- Complex error handling required

## History

**Implemented:**
- ✅ queue_index: Binary priority queue replacing JSON filesystem queue
- ✅ dataset_hash: SIMD SHA256 for artifact verification

**Deferred:**
- ⏸️ task_json_codec: 2-3x speedup not worth maintenance (small team)
- ⏸️ artifact_scanner: Go filepath.Walk faster for typical workloads
- ⏸️ streaming_io: Complexity exceeds benefit without io_uring

## Maintenance

**Build verification:**
```bash
make native-build

# Test with native libs (using build tag)
go test -tags native_libs ./tests/...

# Or use the test script with Redis
docker-compose -f deployments/docker-compose.dev.yml up -d redis
sleep 2
go test -tags native_libs ./tests/...
```

**Adding new library:**
1. Create subdirectory with CMakeLists.txt
2. Implement C ABI in `.h` / `.cpp` files
3. Add to root CMakeLists.txt
4. Create Go bridge in `internal/`
5. Add benchmarks in `tests/benchmarks/`
6. Document in this README

## Troubleshooting

**Library not found:**
- Ensure `native/build/lib*.dylib` (macOS) or `.so` (Linux) exists
- Check `LD_LIBRARY_PATH` or `DYLD_LIBRARY_PATH`

**CGo undefined symbols:**
- Verify C function names match exactly (no name mangling)
- Check `#include` paths are correct
- Rebuild: `make native-clean && make native-build`

**Performance regression:**
- Verify `FETCHML_NATIVE_LIBS=1` is set
- Check benchmark: `go test -bench=BenchmarkQueue -v`
- Profile with: `go test -bench=. -cpuprofile=cpu.prof`