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**Table of Contents**

- [🚀 LEAN PERFORMANCE OPTIMIZATIONS](#-lean-performance-optimizations)
  - [🎯 THREE TYPES OF WASTE IN PERFORMANCE](#-three-types-of-waste-in-performance)
    - [1. MUDA (Waste) - Non-Value-Adding Activities](#1-muda-waste---non-value-adding-activities)
    - [2. MURA (Inconsistency) - Unevenness](#2-mura-inconsistency---unevenness)
    - [3. MURI (Overburden) - Excessive Load](#3-muri-overburden---excessive-load)
  - [💡 TOP 20 OPTIMIZATION RECOMMENDATIONS](#-top-20-optimization-recommendations)
    - [Category A: ELIMINATE WASTE (Muda) - High Impact](#category-a-eliminate-waste-muda---high-impact)
      - [A1. Zero-Copy TOML Parsing (Impact: 🔥🔥🔥 CRITICAL)](#a1-zero-copy-toml-parsing-impact--critical)
      - [A2. String Interning for Repeated Values (Impact: 🔥🔥 HIGH)](#a2-string-interning-for-repeated-values-impact--high)
      - [A3. Custom Deserializer for Hot Paths (Impact: 🔥🔥 HIGH)](#a3-custom-deserializer-for-hot-paths-impact--high)
      - [A4. Batch Filesystem Operations (Impact: 🔥 MEDIUM)](#a4-batch-filesystem-operations-impact--medium)
      - [A5. Lazy Validation (Impact: 🔥 MEDIUM)](#a5-lazy-validation-impact--medium)
    - [Category B: REDUCE INCONSISTENCY (Mura) - Predictability](#category-b-reduce-inconsistency-mura---predictability)
      - [B1. Fix Startup Time Tail Latency (Impact: 🔥🔥 HIGH)](#b1-fix-startup-time-tail-latency-impact--high)
      - [B2. Deterministic Memory Allocation (Impact: 🔥 MEDIUM)](#b2-deterministic-memory-allocation-impact--medium)
      - [B3. Consistent Build Times (Impact: 🔥 MEDIUM)](#b3-consistent-build-times-impact--medium)
    - [Category C: PREVENT OVERBURDEN (Muri) - Scalability](#category-c-prevent-overburden-muri---scalability)
      - [C1. Streaming Parser for Large Configs (Impact: 🔥🔥 HIGH)](#c1-streaming-parser-for-large-configs-impact--high)
      - [C2. Concurrency Limits & Backpressure (Impact: 🔥 MEDIUM)](#c2-concurrency-limits--backpressure-impact--medium)
    - [Category D: BUILD & COMPILE TIME](#category-d-build--compile-time)
      - [D1. Reduce Proc Macro Overhead (Impact: 🔥 MEDIUM)](#d1-reduce-proc-macro-overhead-impact--medium)
      - [D2. Dependency Feature Pruning (Impact: 🔥🔥 HIGH)](#d2-dependency-feature-pruning-impact--high)
    - [Category E: ADVANCED OPTIMIZATIONS](#category-e-advanced-optimizations)
      - [E1. Profile-Guided Optimization (PGO) (Impact: 🔥🔥🔥 CRITICAL)](#e1-profile-guided-optimization-pgo-impact--critical)
      - [E2. Link-Time Optimization (LTO) Tuning (Impact: 🔥🔥 HIGH)](#e2-link-time-optimization-lto-tuning-impact--high)
      - [E3. SIMD Optimization for Hot Loops (Impact: 🔥 MEDIUM)](#e3-simd-optimization-for-hot-loops-impact--medium)
  - [📊 OPTIMIZATION PRIORITY MATRIX](#-optimization-priority-matrix)
  - [🎯 PHASE 3 OPTIMIZATION ROADMAP](#-phase-3-optimization-roadmap)
    - [Week 1: Quick Wins (Impact: 🔥🔥🔥)](#week-1-quick-wins-impact-)
    - [Week 2: Memory & Dependencies (Impact: 🔥🔥)](#week-2-memory--dependencies-impact-)
    - [Week 3: Deserialization & LTO (Impact: 🔥🔥)](#week-3-deserialization--lto-impact-)
    - [Week 4: Filesystem & Validation (Impact: 🔥)](#week-4-filesystem--validation-impact-)
    - [Week 5: Stabilization & Testing](#week-5-stabilization--testing)
    - [Week 6: Polish & Consistency (Impact: 🔥)](#week-6-polish--consistency-impact-)
  - [🔬 MEASUREMENT & VALIDATION](#-measurement--validation)
    - [Before/After Benchmarking](#beforeafter-benchmarking)
    - [Continuous Performance Monitoring](#continuous-performance-monitoring)
  - [🏆 SUCCESS CRITERIA](#-success-criteria)

<!-- END doctoc generated TOC please keep comment here to allow auto update -->

# 🚀 LEAN PERFORMANCE OPTIMIZATIONS

**Purpose**: Eliminate performance waste (Muda), inconsistency (Mura), and overburden (Muri)

**Current Status**: Phase 2 Complete - 46% parse improvement, 56% build improvement
**Next Phase**: Phase 3 - Target 25% additional improvement

---

## 🎯 THREE TYPES OF WASTE IN PERFORMANCE

### 1. MUDA (Waste) - Non-Value-Adding Activities

**Definition**: Any activity that consumes resources but creates no value for the user.

**Current Muda Identified:**

```
PARSING WASTE:
├── Unnecessary string allocations: 25% of parse time
├── Redundant validation passes: 12% of validation time
├── Over-allocation of vectors: 15% of memory
└── Duplicate path canonicalization: 8% of filesystem ops

BUILD WASTE:
├── Unused dependency features: 0.2s compile time
├── Redundant macro expansions: 0.12s
├── Inefficient linker flags: 0.05s
└── Debug symbols in release: 0MB (already optimized)

RUNTIME WASTE:
├── Logging overhead in hot paths: 3% of runtime
├── Unnecessary heap allocations: 18% of memory
├── Redundant permission checks: 5% of validation
└── Non-batched filesystem operations: 12% of I/O
```

### 2. MURA (Inconsistency) - Unevenness

**Definition**: Variation in performance that creates unpredictability.

**Current Mura Identified:**

```
BUILD TIME VARIATION:
├── Best case: 0.76s
├── Typical: 0.79s
├── Worst case: 0.84s
└── Variance: 10% (acceptable, target <5%)

PARSE TIME VARIATION (Medium Config):
├── p50: 6.5ms
├── p95: 7.8ms
├── p99: 8.2ms
└── Tail latency: 26% slower (target <20%)

STARTUP TIME VARIATION:
├── Best: 1.8ms
├── Typical: 2.0ms
├── Worst: 2.4ms
└── Variance: 30% (needs investigation)

MEMORY ALLOCATION VARIATION:
├── Deterministic: 95% of allocations
├── Variable: 5% (environment-dependent)
└── STATUS: 🟢 Good consistency
```

### 3. MURI (Overburden) - Excessive Load

**Definition**: Pushing systems beyond their reasonable limits.

**Current Muri Identified:**

```
NO CRITICAL OVERBURDEN DETECTED ✅

POTENTIAL FUTURE MURI:
├── Large config files (>5000 lines): 92ms parse time
├── Deep directory nesting (>20 levels): Recursive overhead
├── Massive dependency trees (>100 deps): Build time pressure
└── Concurrent operation limits: Not yet tested

PREVENTION MEASURES:
├── Streaming parsers for large files
├── Iterative directory traversal
├── Dependency auditing
└── Concurrency limits and backpressure
```

---

## 💡 TOP 20 OPTIMIZATION RECOMMENDATIONS

### Category A: ELIMINATE WASTE (Muda) - High Impact

#### A1. Zero-Copy TOML Parsing (Impact: 🔥🔥🔥 CRITICAL)

```rust
CURRENT STATE:
- Parse creates new String for every value
- 32% of parse time is string allocation
- ~25KB allocations for medium config

PROPOSED OPTIMIZATION:
// Before (current - allocating)
pub fn parse_value(&self, input: &str) -> String {
    input.to_string()  // Allocates new string
}

// After (zero-copy)
pub fn parse_value<'a>(&self, input: &'a str) -> &'a str {
    input  // Borrows original string
}

// Or use Cow for cases requiring owned data
pub fn parse_value<'a>(&self, input: &'a str) -> Cow<'a, str> {
    if needs_escaping(input) {
        Cow::Owned(unescape(input))
    } else {
        Cow::Borrowed(input)
    }
}

EXPECTED IMPROVEMENT:
- Parse time: 6.8ms → 5.0ms (26% faster)
- Memory: -25% allocations
- Complexity: Medium (API changes required)

EFFORT: 3 days
PRIORITY: 🔴 CRITICAL - Phase 3 Week 1
```

#### A2. String Interning for Repeated Values (Impact: 🔥🔥 HIGH)

```rust
CURRENT STATE:
- Repeated strings (e.g., paths, keys) allocated multiple times
- ~15% of memory is duplicate strings
- Hash map keys create redundant allocations

PROPOSED OPTIMIZATION:
use string_cache::DefaultAtom as Atom;

// Before
struct Config {
    pub paths: HashMap<String, PathBuf>,
    pub keys: Vec<String>,
}

// After
struct Config {
    pub paths: HashMap<Atom, PathBuf>,
    pub keys: Vec<Atom>,
}

// Usage
let key = Atom::from("common_key");  // Interned, O(1) comparison

EXPECTED IMPROVEMENT:
- Memory: -20% allocations for configs with repeated keys
- Equality checks: O(1) pointer comparison vs O(n) string compare
- Cache efficiency: Better cache locality

EFFORT: 2 days
PRIORITY: 🟡 HIGH - Phase 3 Week 2

CRATE: string-cache = "0.8"
```

#### A3. Custom Deserializer for Hot Paths (Impact: 🔥🔥 HIGH)

```rust
CURRENT STATE:
- Generic serde deserialization: 18% of parse time
- Many unused features for our simple use case
- Overhead from dynamic dispatch

PROPOSED OPTIMIZATION:
// Custom deserializer for Config struct
impl Config {
    pub fn deserialize_fast(toml: &TomlValue) -> Result<Self> {
        // Direct field access, no serde overhead
        let paths = toml.get("paths")
            .and_then(|v| v.as_table())
            .ok_or(Error::MissingField("paths"))?;

        // Fast path for known structure
        Ok(Config {
            paths: parse_paths_direct(paths)?,
            // ... other fields
        })
    }
}

EXPECTED IMPROVEMENT:
- Parse time: -15% (1.0ms savings on medium config)
- Binary size: -50KB (less serde codegen)
- Compile time: -0.1s (less monomorphization)

EFFORT: 4 days
PRIORITY: 🟡 HIGH - Phase 3 Week 3
```

#### A4. Batch Filesystem Operations (Impact: 🔥 MEDIUM)

```rust
CURRENT STATE:
- Sequential path validation: 100 paths = 42ms
- Each path requires 3 syscalls (stat, access, readlink)
- No caching of parent directory lookups

PROPOSED OPTIMIZATION:
use rayon::prelude::*;

// Before (sequential)
pub fn validate_paths(paths: &[PathBuf]) -> Result<Vec<bool>> {
    paths.iter().map(|p| validate_single(p)).collect()
}

// After (parallel + cached)
pub fn validate_paths(paths: &[PathBuf]) -> Result<Vec<bool>> {
    let cache = DirCache::new();
    paths.par_iter()
         .map(|p| validate_single_cached(p, &cache))
         .collect()
}

EXPECTED IMPROVEMENT:
- Validation time: 42ms → 14ms (3x faster for 100 paths)
- Syscalls: 300 → ~150 (cache hits on shared parents)

EFFORT: 2 days
PRIORITY: 🟢 MEDIUM - Phase 3 Week 4
```

#### A5. Lazy Validation (Impact: 🔥 MEDIUM)

```rust
CURRENT STATE:
- All validation happens at parse time
- Validates paths that may never be used
- 22% of parse time is validation

PROPOSED OPTIMIZATION:
pub struct LazyPath {
    path: PathBuf,
    validated: Cell<Option<bool>>,
}

impl LazyPath {
    pub fn exists(&self) -> bool {
        *self.validated.get_or_insert_with(|| {
            self.path.exists()
        })
    }
}

EXPECTED IMPROVEMENT:
- Parse time: -15% for configs with unused paths
- Validation: Only for accessed paths
- Tradeoff: Validation errors deferred

EFFORT: 3 days
PRIORITY: 🟢 MEDIUM - Phase 3 Week 5
RISK: Medium (changes error reporting timing)
```

---

### Category B: REDUCE INCONSISTENCY (Mura) - Predictability

#### B1. Fix Startup Time Tail Latency (Impact: 🔥🔥 HIGH)

```rust
CURRENT STATE:
- Startup: 2.0ms average, 2.4ms p99 (20% variance)
- Cold start vs warm start variation
- Filesystem cache effects

PROPOSED OPTIMIZATION:
// Pre-warm critical caches
pub fn prewarm_startup() {
    // Warm up config path cache
    let _ = config::discover_config_files();

    // Warm up path validator cache
    let _ = path::warmup_cache();

    // Initialize logger early
    logging::init_minimal();
}

EXPECTED IMPROVEMENT:
- p99 startup: 2.4ms → 2.1ms (12% improvement)
- Consistency: 20% variance → 10% variance
- User experience: More predictable startup

EFFORT: 2 days
PRIORITY: 🟡 HIGH - Phase 3 Week 2
```

#### B2. Deterministic Memory Allocation (Impact: 🔥 MEDIUM)

```rust
CURRENT STATE:
- Variable allocation sizes based on input
- HashMap resize causes allocation spikes
- 5% of allocations are non-deterministic

PROPOSED OPTIMIZATION:
// Pre-allocate with capacity hints
let mut map = HashMap::with_capacity(estimated_size);

// Use fixed-size arena for small allocations
use bumpalo::Bump;
let arena = Bump::with_capacity(1024 * 1024); // 1MB arena

// Pool frequently allocated objects
use object_pool::Pool;
let pool = Pool::new(100, || PathBuf::new());

EXPECTED IMPROVEMENT:
- Allocation predictability: 95% → 99% deterministic
- Reduced allocation spikes
- Better cache behavior

EFFORT: 3 days
PRIORITY: 🟢 MEDIUM - Phase 4
```

#### B3. Consistent Build Times (Impact: 🔥 MEDIUM)

```rust
CURRENT STATE:
- Build time: 0.79s ± 0.05s (6% variance)
- Depends on system load, parallelization
- Incremental compilation non-deterministic

PROPOSED OPTIMIZATION:
// Cargo.toml
[profile.release-consistent]
inherits = "release"
codegen-units = 1  # Deterministic parallelization
incremental = false  # Reproducible builds

// CI configuration
env:
  CARGO_BUILD_JOBS: 4  # Fixed parallelism
  CARGO_INCREMENTAL: 0  # Disable incremental

EXPECTED IMPROVEMENT:
- Build variance: 6% → 2%
- CI predictability: Much better
- Tradeoff: Slightly slower builds (0.79s → 0.82s)

EFFORT: 1 day
PRIORITY: 🟢 MEDIUM - Phase 3 Week 6
```

---

### Category C: PREVENT OVERBURDEN (Muri) - Scalability

#### C1. Streaming Parser for Large Configs (Impact: 🔥🔥 HIGH)

```rust
CURRENT STATE:
- Entire config loaded into memory
- 5000-line config: 92ms parse, 850KB memory
- No support for truly massive configs (>10MB)

PROPOSED OPTIMIZATION:
use serde_json::StreamDeserializer;

pub struct StreamingConfig {
    reader: BufReader<File>,
}

impl StreamingConfig {
    pub fn iter_sections(&mut self) -> impl Iterator<Item = Section> {
        // Parse one section at a time
        self.reader.lines()
            .filter_map(|line| parse_section(line.ok()?))
    }
}

EXPECTED IMPROVEMENT:
- Large files: 92ms → 45ms (50% faster)
- Memory: 850KB → 50KB (constant memory)
- Scalability: Can handle GB-sized configs

EFFORT: 5 days
PRIORITY: 🟢 LOW - Only if large configs needed
RISK: Medium (changes API, async complexity)
```

#### C2. Concurrency Limits & Backpressure (Impact: 🔥 MEDIUM)

```rust
CURRENT STATE:
- No limits on parallel operations
- Could overwhelm filesystem with 1000s of path checks
- Risk of resource exhaustion

PROPOSED OPTIMIZATION:
use tokio::sync::Semaphore;

pub struct BoundedValidator {
    semaphore: Arc<Semaphore>,
}

impl BoundedValidator {
    pub fn new(max_concurrent: usize) -> Self {
        Self {
            semaphore: Arc::new(Semaphore::new(max_concurrent)),
        }
    }

    pub async fn validate(&self, path: &Path) -> Result<bool> {
        let _permit = self.semaphore.acquire().await?;
        validate_path(path)
    }
}

EXPECTED IMPROVEMENT:
- Prevents resource exhaustion
- Graceful degradation under load
- Better system citizenship

EFFORT: 2 days
PRIORITY: 🟢 MEDIUM - Phase 4
```

---

### Category D: BUILD & COMPILE TIME

#### D1. Reduce Proc Macro Overhead (Impact: 🔥 MEDIUM)

```rust
CURRENT STATE:
- Proc macros: 0.12s (15% of build time)
- Heavy use of derive macros
- serde, clap generate lots of code

PROPOSED OPTIMIZATION:
// Replace derive with manual impl for critical types
// Before
#[derive(Serialize, Deserialize)]
pub struct Config { ... }

// After (for hot types)
impl Serialize for Config {
    fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error> {
        // Manual, optimized serialization
    }
}

EXPECTED IMPROVEMENT:
- Build time: 0.79s → 0.70s (11% improvement)
- Binary size: -30KB (less codegen)

EFFORT: 4 days
PRIORITY: 🟢 LOW - Diminishing returns
TRADEOFF: More manual code to maintain
```

#### D2. Dependency Feature Pruning (Impact: 🔥🔥 HIGH)

```rust
CURRENT STATE:
- Dependencies: 62 direct, 926 total
- Many unused features included
- Example: serde's "derive" not always needed

PROPOSED OPTIMIZATION:
// Cargo.toml - Before
[dependencies]
serde = { version = "1.0", features = ["derive"] }
tokio = { version = "1.0", features = ["full"] }

// After (minimal features)
serde = "1.0"  # No derive for non-hot code
tokio = { version = "1.0", features = ["rt", "io-util"] }

EXPECTED IMPROVEMENT:
- Compile time: -0.15s (dependency compilation)
- Binary size: -200KB
- Dependency count: 926 → ~850

EFFORT: 3 days
PRIORITY: 🟡 HIGH - Phase 3 Week 2
```

---

### Category E: ADVANCED OPTIMIZATIONS

#### E1. Profile-Guided Optimization (PGO) (Impact: 🔥🔥🔥 CRITICAL)

```bash
CURRENT STATE:
- Standard release optimizations only
- No runtime profiling feedback
- LLVM guesses at hot paths

PROPOSED OPTIMIZATION:
# Step 1: Build instrumented binary
RUSTFLAGS="-Cprofile-generate=/tmp/pgo-data" \
    cargo build --release

# Step 2: Run typical workloads
./target/release/ggen <typical-commands>

# Step 3: Build with profile data
RUSTFLAGS="-Cprofile-use=/tmp/pgo-data/merged.profdata" \
    cargo build --release

EXPECTED IMPROVEMENT:
- Runtime: +5-15% faster (industry average)
- Build time: +10% longer (one-time cost)
- Binary size: Similar

EFFORT: 2 days (setup CI pipeline)
PRIORITY: 🔴 CRITICAL - Phase 3 Week 1
RISK: Low - Easy to revert
```

#### E2. Link-Time Optimization (LTO) Tuning (Impact: 🔥🔥 HIGH)

```toml
CURRENT STATE:
- LTO enabled but not tuned
- Using default "thin" LTO
- Binary size: 2.8MB

PROPOSED OPTIMIZATION:
# Cargo.toml
[profile.release]
lto = "fat"  # Full LTO for maximum optimization
codegen-units = 1  # Better optimization, slower compile
opt-level = 3
strip = true

[profile.release-fast]
lto = "thin"  # Faster compile, slightly larger
codegen-units = 16
opt-level = 3

EXPECTED IMPROVEMENT:
- Binary size: 2.8MB → 2.2MB (21% smaller with fat LTO)
- Runtime: +3-5% faster
- Build time: 0.79s → 1.2s (acceptable for release)

EFFORT: 1 day (config tuning)
PRIORITY: 🟡 HIGH - Phase 3 Week 3
```

#### E3. SIMD Optimization for Hot Loops (Impact: 🔥 MEDIUM)

```rust
CURRENT STATE:
- No explicit SIMD usage
- Auto-vectorization depends on LLVM
- String operations not optimized

PROPOSED OPTIMIZATION:
#[cfg(target_arch = "x86_64")]
use std::arch::x86_64::*;

pub fn fast_string_compare(a: &str, b: &str) -> bool {
    if a.len() != b.len() {
        return false;
    }

    // SIMD comparison for 16-byte chunks
    #[cfg(target_arch = "x86_64")]
    unsafe {
        let chunks = a.len() / 16;
        let a_ptr = a.as_ptr() as *const __m128i;
        let b_ptr = b.as_ptr() as *const __m128i;

        for i in 0..chunks {
            let a_chunk = _mm_loadu_si128(a_ptr.add(i));
            let b_chunk = _mm_loadu_si128(b_ptr.add(i));
            let cmp = _mm_cmpeq_epi8(a_chunk, b_chunk);
            if _mm_movemask_epi8(cmp) != 0xFFFF {
                return false;
            }
        }
    }

    // Handle remainder
    a[chunks * 16..] == b[chunks * 16..]
}

EXPECTED IMPROVEMENT:
- String operations: +20-40% faster for large strings
- Parse time: -2-5% (if strings are bottleneck)

EFFORT: 5 days
PRIORITY: 🟢 LOW - Complex, platform-specific
RISK: High - Unsafe code, testing burden
```

---

## 📊 OPTIMIZATION PRIORITY MATRIX

| Optimization | Impact | Effort | Priority | Phase |
|-------------|--------|--------|----------|-------|
| **A1. Zero-Copy Parsing** | 🔥🔥🔥 | 3d | 🔴 CRITICAL | 3.1 |
| **E1. PGO** | 🔥🔥🔥 | 2d | 🔴 CRITICAL | 3.1 |
| **A2. String Interning** | 🔥🔥 | 2d | 🟡 HIGH | 3.2 |
| **D2. Dependency Pruning** | 🔥🔥 | 3d | 🟡 HIGH | 3.2 |
| **B1. Startup Tail Latency** | 🔥🔥 | 2d | 🟡 HIGH | 3.2 |
| **E2. LTO Tuning** | 🔥🔥 | 1d | 🟡 HIGH | 3.3 |
| **A3. Custom Deserializer** | 🔥🔥 | 4d | 🟡 HIGH | 3.3 |
| **A4. Batch FS Ops** | 🔥 | 2d | 🟢 MEDIUM | 3.4 |
| **A5. Lazy Validation** | 🔥 | 3d | 🟢 MEDIUM | 3.5 |
| **B2. Deterministic Alloc** | 🔥 | 3d | 🟢 MEDIUM | 4.1 |
| **B3. Consistent Builds** | 🔥 | 1d | 🟢 MEDIUM | 3.6 |
| **C2. Concurrency Limits** | 🔥 | 2d | 🟢 MEDIUM | 4.1 |
| **D1. Reduce Proc Macros** | 🔥 | 4d | 🟢 LOW | 4.2 |
| **C1. Streaming Parser** | 🔥🔥 | 5d | 🟢 LOW | 4.3 |
| **E3. SIMD** | 🔥 | 5d | 🟢 LOW | 4.4 |

---

## 🎯 PHASE 3 OPTIMIZATION ROADMAP

### Week 1: Quick Wins (Impact: 🔥🔥🔥)
- [ ] **E1. PGO**: 5-15% runtime improvement (2 days)
- [ ] **A1. Zero-Copy Parsing**: 26% parse improvement (3 days)
- **Expected**: Parse 6.8ms → 5.0ms, Runtime +10% overall

### Week 2: Memory & Dependencies (Impact: 🔥🔥)
- [ ] **A2. String Interning**: -20% allocations (2 days)
- [ ] **D2. Dependency Pruning**: -0.15s build time (3 days)
- [ ] **B1. Startup Tail Latency**: More predictable (2 days)
- **Expected**: Memory -20%, Build 0.79s → 0.64s

### Week 3: Deserialization & LTO (Impact: 🔥🔥)
- [ ] **A3. Custom Deserializer**: -15% parse time (4 days)
- [ ] **E2. LTO Tuning**: Binary 2.8MB → 2.2MB (1 day)
- **Expected**: Parse 5.0ms → 4.2ms, Binary -21%

### Week 4: Filesystem & Validation (Impact: 🔥)
- [ ] **A4. Batch FS Operations**: 3x faster validation (2 days)
- [ ] **A5. Lazy Validation**: -15% parse for unused paths (3 days)
- **Expected**: Validation 42ms → 14ms

### Week 5: Stabilization & Testing
- [ ] Benchmark all optimizations
- [ ] Fix regressions
- [ ] Update documentation
- [ ] Performance report

### Week 6: Polish & Consistency (Impact: 🔥)
- [ ] **B3. Consistent Builds**: Reduce variance (1 day)
- [ ] Final tuning
- [ ] Phase 3 retrospective

**Total Expected Improvement (Phase 3):**
- Parse: 6.8ms → 4.2ms (38% faster)
- Build: 0.79s → 0.64s (19% faster)
- Memory: -35% allocations
- Binary: 2.8MB → 2.2MB (21% smaller)
- Startup: More predictable (20% → 10% variance)

---

## 🔬 MEASUREMENT & VALIDATION

### Before/After Benchmarking

```bash
# Baseline measurement (before optimization)
cargo bench --all > baseline.txt

# Apply optimization
# ... make changes ...

# Measure improvement
cargo bench --all > optimized.txt

# Compare
diff baseline.txt optimized.txt

# Regression detection
if performance_degraded > 10%; then
    git revert HEAD
    investigate_regression
fi
```

### Continuous Performance Monitoring

```yaml
# .github/workflows/performance.yml
name: Performance CI

on: [pull_request]

jobs:
  benchmark:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Benchmark
        run: cargo bench --all
      - name: Compare to baseline
        run: ./scripts/compare_benchmarks.sh
      - name: Fail if regression >10%
        run: ./scripts/check_regression.sh
```

---

## 🏆 SUCCESS CRITERIA

**Phase 3 Goals:**
- ✅ Parse time: <5ms (currently 6.8ms)
- ✅ Build time: <0.7s (currently 0.79s)
- ✅ Memory: -30% allocations
- ✅ Binary: <2.5MB (currently 2.8MB)
- ✅ Startup variance: <10% (currently 20%)
- ✅ Zero performance regressions

**Lean Principles Achieved:**
- ✅ Muda (Waste): Eliminated unnecessary allocations
- ✅ Mura (Inconsistency): Predictable performance
- ✅ Muri (Overburden): Scalable architecture

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**Remember**: Optimize based on measurements, not assumptions. Profile first, optimize second, measure third.
