use std::time::{Duration, Instant, SystemTime, UNIX_EPOCH};
use crate::analysis::bottleneck_detector::{
Bottleneck, BottleneckType, BottleneckDetector, BottleneckSeverity
};
use crate::performance_analyzer::PerformanceReport;
use serde::{Deserialize, Serialize};
use std::hash::Hash;
#[derive(Debug, Clone, PartialEq, PartialOrd, Serialize, Deserialize)]
pub enum OptimizationPriority {
Critical,
High,
Medium,
Low,
}
#[derive(Debug, Clone, PartialEq, Eq, Hash, Serialize, Deserialize)]
pub enum OptimizationCategory {
CodeOptimization,
MemoryOptimization,
CachingStrategy,
JITOptimization,
IOOptimization,
ArchitectureChange,
ConfigurationTuning,
}
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct OptimizationSuggestion {
pub id: String,
pub title: String,
pub description: String,
pub category: OptimizationCategory,
pub priority: OptimizationPriority,
pub estimated_improvement: String,
pub implementation_effort: String,
pub steps: Vec<String>,
pub code_examples: Vec<String>,
pub related_bottlenecks: Vec<String>,
pub references: Vec<String>,
}
pub struct PerformanceOptimizer {
bottleneck_detector: BottleneckDetector,
}
impl PerformanceOptimizer {
pub fn new() -> Self {
Self {
bottleneck_detector: BottleneckDetector::new(),
}
}
pub fn generate_suggestions(&self, bottlenecks: &[Bottleneck]) -> Vec<OptimizationSuggestion> {
let mut suggestions = Vec::new();
for bottleneck in bottlenecks {
let mut bottleneck_suggestions = self.suggest_for_bottleneck(bottleneck);
suggestions.append(&mut bottleneck_suggestions);
}
suggestions.sort_by(|a, b| {
let a_val: _ = self.priority_to_value(&a.priority);
let b_val: _ = self.priority_to_value(&b.priority);
b_val.cmp(&a_val)
});
suggestions
}
fn suggest_for_bottleneck(&self, bottleneck: &Bottleneck) -> Vec<OptimizationSuggestion> {
match &bottleneck.bottleneck_type {
BottleneckType::SlowExecution => self.suggest_for_slow_execution(bottleneck),
BottleneckType::LowCacheHitRate => self.suggest_for_low_cache_hit_rate(bottleneck),
BottleneckType::HighMemoryUsage => self.suggest_for_high_memory_usage(bottleneck),
BottleneckType::CPUIntensive => self.suggest_for_cpu_intensive(bottleneck),
BottleneckType::IOBlocking => self.suggest_for_io_blocking(bottleneck),
BottleneckType::HeapPressure => self.suggest_for_heap_pressure(bottleneck),
BottleneckType::FrequentGC => self.suggest_for_frequent_gc(bottleneck),
BottleneckType::EventLoopLag => self.suggest_for_event_loop_lag(bottleneck),
BottleneckType::Other(_) => self.suggest_for_other(bottleneck),
}
}
fn suggest_for_slow_execution(&self, bottleneck: &Bottleneck) -> Vec<OptimizationSuggestion> {
vec![
OptimizationSuggestion {
id: "opt-001".to_string(),
title: "Enable V8 JIT Compilation".to_string(),
description: "Enable V8's Just-In-Time (JIT) compilation to optimize hot code paths".to_string(),
category: OptimizationCategory::JITOptimization,
priority: OptimizationPriority::Critical,
estimated_improvement: "20-50% performance improvement".to_string(),
implementation_effort: "Low (configuration change)".to_string(),
steps: vec![
"Configure V8 flags: --jit-enable-optimization".to_string(),
"Set optimization threshold: --jit-opt-level=3".to_string(),
"Enable inline caching: --jit-inline-cache".to_string(),
],
code_examples: vec![
"amber --optimize-speed --jit-enable --jit-opt-level 3 script.js".to_string(),
],
related_bottlenecks: vec![format!("{:?}", bottleneck.bottleneck_type)],
references: vec![
"V8 JIT Documentation".to_string(),
"V8 Optimization Flags Guide".to_string(),
],
},
OptimizationSuggestion {
id: "opt-002".to_string(),
title: "Implement Code Caching".to_string(),
description: "Cache compiled JavaScript code to avoid re-parsing and re-compilation".to_string(),
category: OptimizationCategory::CachingStrategy,
priority: OptimizationPriority::High,
estimated_improvement: "30-60% startup time improvement".to_string(),
implementation_effort: "Medium (code changes)".to_string(),
steps: vec![
"Enable persistent code cache".to_string(),
"Implement LRU cache for frequently used modules".to_string(),
"Add cache invalidation strategy".to_string(),
],
code_examples: vec![
"amber --cache --cache-size 100 script.js".to_string(),
],
related_bottlenecks: vec![format!("{:?}", bottleneck.bottleneck_type)],
references: vec![
"V8 Code Cache Documentation".to_string(),
"JavaScript Module Caching Patterns".to_string(),
],
},
OptimizationSuggestion {
id: "opt-003".to_string(),
title: "Optimize Hot Code Paths".to_string(),
description: "Refactor frequently executed code for better performance".to_string(),
category: OptimizationCategory::CodeOptimization,
priority: OptimizationPriority::High,
estimated_improvement: "10-40% performance improvement".to_string(),
implementation_effort: "High (refactoring required)".to_string(),
steps: vec![
"Identify hot code paths using profiling".to_string(),
"Minimize function call overhead".to_string(),
"Use inline functions where appropriate".to_string(),
"Optimize loop structures".to_string(),
],
code_examples: vec![
"// Before: Multiple function calls\nfunction calculate(a, b) {\n return process(a) + process(b);\n}\n\n// After: Inline for better performance\nfunction calculate(a, b) {\n return a * 2 + b * 2;\n}".to_string(),
],
related_bottlenecks: vec![format!("{:?}", bottleneck.bottleneck_type)],
references: vec![
"JavaScript Performance Optimization Guide".to_string(),
"V8 Optimization Tips".to_string(),
],
},
]
}
fn suggest_for_low_cache_hit_rate(&self, bottleneck: &Bottleneck) -> Vec<OptimizationSuggestion> {
vec![
OptimizationSuggestion {
id: "opt-004".to_string(),
title: "Increase Cache Size".to_string(),
description: "Increase the code cache size to store more compiled code".to_string(),
category: OptimizationCategory::CachingStrategy,
priority: OptimizationPriority::High,
estimated_improvement: "15-30% cache hit rate improvement".to_string(),
implementation_effort: "Low (configuration change)".to_string(),
steps: vec![
"Increase cache size limit".to_string(),
"Implement cache eviction policy".to_string(),
"Monitor cache metrics".to_string(),
],
code_examples: vec![
"amber --cache-size 256 script.js".to_string(),
],
related_bottlenecks: vec![format!("{:?}", bottleneck.bottleneck_type)],
references: vec![
"V8 Code Cache Configuration".to_string(),
],
},
OptimizationSuggestion {
id: "opt-005".to_string(),
title: "Enable V8 Snapshot".to_string(),
description: "Use V8 snapshots to pre-compile and cache code at startup".to_string(),
category: OptimizationCategory::CachingStrategy,
priority: OptimizationPriority::Medium,
estimated_improvement: "40-70% startup time improvement".to_string(),
implementation_effort: "Medium (setup required)".to_string(),
steps: vec![
"Generate V8 snapshot".to_string(),
"Enable snapshot loading".to_string(),
"Verify snapshot integrity".to_string(),
],
code_examples: vec![
"amber --snapshot script.js".to_string(),
],
related_bottlenecks: vec![format!("{:?}", bottleneck.bottleneck_type)],
references: vec![
"V8 Snapshot Documentation".to_string(),
],
},
]
}
fn suggest_for_high_memory_usage(&self, bottleneck: &Bottleneck) -> Vec<OptimizationSuggestion> {
vec![
OptimizationSuggestion {
id: "opt-006".to_string(),
title: "Implement Memory Pool".to_string(),
description: "Use memory pools to reduce allocation overhead and fragmentation".to_string(),
category: OptimizationCategory::MemoryOptimization,
priority: OptimizationPriority::High,
estimated_improvement: "20-40% memory usage reduction".to_string(),
implementation_effort: "Medium (code changes)".to_string(),
steps: vec![
"Implement object pooling for frequently allocated objects".to_string(),
"Use arena allocators for temporary allocations".to_string(),
"Monitor memory usage patterns".to_string(),
],
code_examples: vec![
"// Enable memory pooling\nbee --memory-pool script.js".to_string(),
],
related_bottlenecks: vec![format!("{:?}", bottleneck.bottleneck_type)],
references: vec![
"Rust Memory Pool Patterns".to_string(),
"JavaScript Memory Optimization".to_string(),
],
},
OptimizationSuggestion {
id: "opt-007".to_string(),
title: "Optimize Data Structures".to_string(),
description: "Use more memory-efficient data structures".to_string(),
category: OptimizationCategory::MemoryOptimization,
priority: OptimizationPriority::Medium,
estimated_improvement: "10-30% memory usage reduction".to_string(),
implementation_effort: "Medium (code refactoring)".to_string(),
steps: vec![
"Replace objects with Maps for better memory efficiency".to_string(),
"Use typed arrays for numerical data".to_string(),
"Implement lazy loading for large datasets".to_string(),
],
code_examples: vec![
"// Use typed arrays instead of regular arrays\nconst arr = new Float32Array(1000);".to_string(),
],
related_bottlenecks: vec![format!("{:?}", bottleneck.bottleneck_type)],
references: vec![
"JavaScript Memory Efficiency Guide".to_string(),
],
},
]
}
fn suggest_for_cpu_intensive(&self, bottleneck: &Bottleneck) -> Vec<OptimizationSuggestion> {
vec![
OptimizationSuggestion {
id: "opt-008".to_string(),
title: "Use Web Workers".to_string(),
description: "Offload CPU-intensive tasks to Web Workers".to_string(),
category: OptimizationCategory::ArchitectureChange,
priority: OptimizationPriority::High,
estimated_improvement: "50-80% main thread performance improvement".to_string(),
implementation_effort: "High (architectural changes)".to_string(),
steps: vec![
"Identify CPU-intensive operations".to_string(),
"Create Web Worker scripts".to_string(),
"Implement message passing".to_string(),
"Handle worker lifecycle".to_string(),
],
code_examples: vec![
"// main.js\nconst worker = new Worker('worker.js');\nworker.postMessage(data);\n\n// worker.js\nself.onmessage = function(e) {\n const result = heavyComputation(e.data);\n self.postMessage(result);\n};".to_string(),
],
related_bottlenecks: vec![format!("{:?}", bottleneck.bottleneck_type)],
references: vec![
"Web Workers API Documentation".to_string(),
],
},
]
}
fn suggest_for_io_blocking(&self, bottleneck: &Bottleneck) -> Vec<OptimizationSuggestion> {
vec![
OptimizationSuggestion {
id: "opt-009".to_string(),
title: "Implement Async I/O".to_string(),
description: "Replace synchronous I/O operations with asynchronous ones".to_string(),
category: OptimizationCategory::IOOptimization,
priority: OptimizationPriority::Critical,
estimated_improvement: "60-90% I/O performance improvement".to_string(),
implementation_effort: "Medium (code changes)".to_string(),
steps: vec![
"Convert synchronous file operations to async".to_string(),
"Use non-blocking network I/O".to_string(),
"Implement async/await patterns".to_string(),
],
code_examples: vec![
"// Before: Blocking I/O\nconst data = fs.readFileSync('file.txt');\n\n// After: Non-blocking I/O\nconst data = await fs.readFile('file.txt');".to_string(),
],
related_bottlenecks: vec![format!("{:?}", bottleneck.bottleneck_type)],
references: vec![
"Async/Await Best Practices".to_string(),
],
},
]
}
fn suggest_for_heap_pressure(&self, bottleneck: &Bottleneck) -> Vec<OptimizationSuggestion> {
vec![
OptimizationSuggestion {
id: "opt-010".to_string(),
title: "Reduce Heap Allocations".to_string(),
description: "Minimize unnecessary heap allocations".to_string(),
category: OptimizationCategory::MemoryOptimization,
priority: OptimizationPriority::High,
estimated_improvement: "20-50% heap pressure reduction".to_string(),
implementation_effort: "Medium (code optimization)".to_string(),
steps: vec![
"Identify frequent allocations".to_string(),
"Reuse objects where possible".to_string(),
"Use stack allocation for small objects".to_string(),
],
code_examples: vec![
"// Reuse objects instead of creating new ones\nconst config = { timeout: 5000 };\n// Use config instead of creating new objects".to_string(),
],
related_bottlenecks: vec![format!("{:?}", bottleneck.bottleneck_type)],
references: vec![
"V8 Heap Optimization".to_string(),
],
},
]
}
fn suggest_for_frequent_gc(&self, bottleneck: &Bottleneck) -> Vec<OptimizationSuggestion> {
vec![
OptimizationSuggestion {
id: "opt-011".to_string(),
title: "Tune GC Parameters".to_string(),
description: "Optimize garbage collection parameters for your workload".to_string(),
category: OptimizationCategory::ConfigurationTuning,
priority: OptimizationPriority::Medium,
estimated_improvement: "15-40% GC overhead reduction".to_string(),
implementation_effort: "Low (configuration)".to_string(),
steps: vec![
"Adjust max heap size".to_string(),
"Tune GC thresholds".to_string(),
"Enable incremental GC".to_string(),
],
code_examples: vec![
"amber --max-heap 512 --gc-incremental script.js".to_string(),
],
related_bottlenecks: vec![format!("{:?}", bottleneck.bottleneck_type)],
references: vec![
"V8 GC Tuning Guide".to_string(),
],
},
]
}
fn suggest_for_event_loop_lag(&self, bottleneck: &Bottleneck) -> Vec<OptimizationSuggestion> {
vec![
OptimizationSuggestion {
id: "opt-012".to_string(),
title: "Optimize Event Loop".to_string(),
description: "Reduce event loop lag by optimizing task scheduling".to_string(),
category: OptimizationCategory::ConfigurationTuning,
priority: OptimizationPriority::High,
estimated_improvement: "30-60% event loop latency reduction".to_string(),
implementation_effort: "Medium (configuration + code)".to_string(),
steps: vec![
"Use setImmediate instead of setTimeout where appropriate".to_string(),
"Break up long-running tasks".to_string(),
"Use process.nextTick for immediate callbacks".to_string(),
],
code_examples: vec![
"// Use setImmediate for I/O callbacks\nfs.readFile('file.txt', (err, data) => {\n setImmediate(() => processData(data));\n});".to_string(),
],
related_bottlenecks: vec![format!("{:?}", bottleneck.bottleneck_type)],
references: vec![
"Node.js Event Loop Guide".to_string(),
],
},
]
}
fn suggest_for_other(&self, bottleneck: &Bottleneck) -> Vec<OptimizationSuggestion> {
vec![
OptimizationSuggestion {
id: "opt-013".to_string(),
title: "Profile and Analyze".to_string(),
description: "Use profiling tools to identify the root cause of the bottleneck".to_string(),
category: OptimizationCategory::CodeOptimization,
priority: OptimizationPriority::Medium,
estimated_improvement: "Varies (diagnostic step)".to_string(),
implementation_effort: "Low (tool usage)".to_string(),
steps: vec![
"Enable performance profiling".to_string(),
"Run performance benchmarks".to_string(),
"Analyze profiling results".to_string(),
"Implement targeted optimizations".to_string(),
],
code_examples: vec![
"amber --profile script.js".to_string(),
],
related_bottlenecks: vec![format!("{:?}", bottleneck.bottleneck_type)],
references: vec![
"JavaScript Profiling Guide".to_string(),
],
},
]
}
fn priority_to_value(&self, priority: &OptimizationPriority) -> i32 {
match priority {
OptimizationPriority::Critical => 5,
OptimizationPriority::High => 4,
OptimizationPriority::Medium => 3,
OptimizationPriority::Low => 2,
}
}
pub fn generate_optimization_report(
&self,
report: &PerformanceReport,
) -> HashMap<String, _> {
let bottlenecks: _ = self.bottleneck_detector.detect_bottlenecks(report);
let suggestions: _ = self.generate_suggestions(&bottlenecks);
let mut categorized_suggestions = HashMap::new();
for suggestion in suggestions {
let category: _ = format!("{:?}", suggestion.category);
categorized_suggestions
.entry(category)
.or_insert_with(Vec::new)
.push(suggestion);
}
categorized_suggestions
}
}
impl Default for PerformanceOptimizer {
fn default() -> Self {
Self::new()
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_optimizer_creation() {
let optimizer: _ = PerformanceOptimizer::new();
let _: _ = optimizer;
}
#[test]
fn test_generate_suggestions_for_slow_execution() {
let optimizer: _ = PerformanceOptimizer::new();
let bottleneck: _ = Bottleneck {
bottleneck_type: BottleneckType::SlowExecution,
severity: BottleneckSeverity::High,
description: "Slow execution detected".to_string(),
affected_metrics: vec!["average_time_ms".to_string()],
suggestion: "Optimize code".to_string(),
code_location: None,
};
let suggestions: _ = optimizer.generate_suggestions(&[bottleneck]);
assert!(!suggestions.is_empty());
assert!(suggestions.iter().any(|s| s.category == OptimizationCategory::JITOptimization));
}
#[test]
fn test_generate_suggestions_for_low_cache_hit_rate() {
let optimizer: _ = PerformanceOptimizer::new();
let bottleneck: _ = Bottleneck {
bottleneck_type: BottleneckType::LowCacheHitRate,
severity: BottleneckSeverity::Medium,
description: "Low cache hit rate".to_string(),
affected_metrics: vec!["cache_hit_rate".to_string()],
suggestion: "Increase cache size".to_string(),
code_location: None,
};
let suggestions: _ = optimizer.generate_suggestions(&[bottleneck]);
assert!(!suggestions.is_empty());
assert!(suggestions.iter().any(|s| s.category == OptimizationCategory::CachingStrategy));
}
#[test]
fn test_generate_optimization_report() {
let optimizer: _ = PerformanceOptimizer::new();
let report: _ = PerformanceReport {
total_executions: 10,
average_time_ms: 15.0,
min_time_ms: 5.0,
max_time_ms: 30.0,
cache_hit_rate: 30.0,
total_code_executed: 1000,
};
let optimization_report: _ = optimizer.generate_optimization_report(&report);
assert!(!optimization_report.is_empty());
}
#[test]
fn test_priority_sorting() {
let optimizer: _ = PerformanceOptimizer::new();
let suggestions: _ = vec![
OptimizationSuggestion {
id: "1".to_string(),
title: "Low Priority".to_string(),
description: "Low priority suggestion".to_string(),
category: OptimizationCategory::CodeOptimization,
priority: OptimizationPriority::Low,
estimated_improvement: "5%".to_string(),
implementation_effort: "Low".to_string(),
steps: vec![],
code_examples: vec![],
related_bottlenecks: vec![],
references: vec![],
},
OptimizationSuggestion {
id: "2".to_string(),
title: "Critical Priority".to_string(),
description: "Critical priority suggestion".to_string(),
category: OptimizationCategory::CodeOptimization,
priority: OptimizationPriority::Critical,
estimated_improvement: "50%".to_string(),
implementation_effort: "High".to_string(),
steps: vec![],
code_examples: vec![],
related_bottlenecks: vec![],
references: vec![],
},
];
let bottlenecks: _ = vec![
Bottleneck {
bottleneck_type: BottleneckType::SlowExecution,
severity: BottleneckSeverity::High,
description: "Test".to_string(),
affected_metrics: vec![],
suggestion: "Test".to_string(),
code_location: None,
}
];
let mut suggestions = optimizer.generate_suggestions(&bottlenecks);
suggestions.sort_by(|a, b| {
let a_val: _ = optimizer.priority_to_value(&a.priority);
let b_val: _ = optimizer.priority_to_value(&b.priority);
b_val.cmp(&a_val)
});
assert!(matches!(suggestions[0].priority, OptimizationPriority::Critical));
}
}
use std::collections::{BTreeMap, HashMap};