pmat 3.11.0

impl PerformanceMonitor {
    /// Create new performance monitor
    #[must_use]
    pub fn new(config: PerformanceConfig) -> Self {
        Self {
            benchmarks: HashMap::new(),
            metrics: PerformanceMetrics::new(),
            optimizer: PerformanceOptimizer::new(config.optimization.clone()),
            config,
        }
    }

    /// Start continuous performance monitoring
    pub async fn start_monitoring(&mut self) -> Result<()> {
        if !self.config.continuous_monitoring {
            return Ok(());
        }

        let mut interval = interval(self.config.benchmark_interval);

        loop {
            interval.tick().await;

            // Collect performance metrics
            self.collect_metrics().await?;

            // Check for performance regressions
            self.check_regressions().await?;

            // Apply optimizations if configured
            if self.config.optimization.auto_optimize {
                self.auto_optimize().await?;
            }

            // Cleanup old data
            if self.config.retention.auto_cleanup {
                self.cleanup_old_data().await?;
            }
        }
    }

    /// Run comprehensive performance benchmark
    pub async fn run_benchmark(&mut self, suite_name: &str) -> Result<BenchmarkReport> {
        let suite = self
            .benchmarks
            .get(suite_name)
            .ok_or_else(|| anyhow::anyhow!("Benchmark suite not found: {suite_name}"))?;

        let mut results = Vec::new();

        for benchmark in &suite.benchmarks {
            let result = self.run_single_benchmark(benchmark).await?;
            results.push((benchmark.name.clone(), result));
        }

        // Calculate summary statistics
        let summary = self.calculate_summary_stats(&results);

        // Check for regressions
        let regressions = self.detect_regressions(&results).await?;

        let report = BenchmarkReport {
            suite_name: suite_name.to_string(),
            executed_at: SystemTime::now(),
            results,
            summary: summary.clone(),
            regressions,
            recommendations: self.generate_recommendations(&summary),
        };

        // Store results for trend analysis
        self.store_benchmark_results(&report).await?;

        Ok(report)
    }

    /// Establish performance baseline
    pub async fn establish_baseline(&mut self, baseline_id: String) -> Result<Baseline> {
        // Collect current system information
        let system_info = self.collect_system_info().await?;
        let codebase_info = self.collect_codebase_info().await?;

        // Run comprehensive measurements
        let measurements = self.collect_baseline_measurements().await?;

        let baseline = Baseline {
            id: baseline_id.clone(),
            measurements,
            measured_at: SystemTime::now(),
            context: BaselineContext {
                system_info,
                codebase_info,
                config_hash: self.calculate_config_hash(),
            },
        };

        self.metrics.baselines.insert(baseline_id, baseline.clone());

        Ok(baseline)
    }

    /// Apply performance optimization
    pub async fn apply_optimization(
        &mut self,
        strategy: OptimizationStrategy,
    ) -> Result<OptimizationResult> {
        // Measure baseline performance
        let baseline = self.collect_baseline_measurements().await?;

        // Apply optimization strategy
        match strategy {
            OptimizationStrategy::CacheOptimization => {
                self.optimize_caching().await?;
            }
            OptimizationStrategy::ParallelProcessing => {
                self.optimize_parallel_processing().await?;
            }
            OptimizationStrategy::MemoryPooling => {
                self.optimize_memory_pooling().await?;
            }
            OptimizationStrategy::IncrementalParsing => {
                self.optimize_incremental_parsing().await?;
            }
            OptimizationStrategy::IoOptimization => {
                self.optimize_io().await?;
            }
            OptimizationStrategy::AstReuse => {
                self.optimize_ast_reuse().await?;
            }
        }

        // Measure performance after optimization
        tokio::time::sleep(Duration::from_secs(1)).await; // Allow system to stabilize
        let optimized = self.collect_baseline_measurements().await?;

        // Calculate improvement
        let improvement = self.calculate_improvement(&baseline, &optimized);

        let result = OptimizationResult {
            strategy,
            improvement_percent: improvement,
            metrics_changed: self.calculate_metrics_delta(&baseline, &optimized),
            applied_at: SystemTime::now(),
            success: improvement > self.config.optimization.min_improvement_percent,
        };

        self.optimizer.history.push(result.clone());

        Ok(result)
    }

    /// Generate performance report
    #[must_use]
    pub fn generate_performance_report(&self) -> PerformanceReport {
        PerformanceReport {
            generated_at: SystemTime::now(),
            current_statistics: self.metrics.statistics.clone(),
            recent_benchmarks: self.get_recent_benchmark_results(10),
            optimization_history: self.optimizer.history.clone(),
            recommendations: self.generate_system_recommendations(),
            alerts: self.generate_performance_alerts(),
        }
    }

    // Private implementation methods

    async fn collect_metrics(&mut self) -> Result<()> {
        // Implementation would collect various performance metrics
        Ok(())
    }

    async fn check_regressions(&self) -> Result<()> {
        // Implementation would check for performance regressions
        Ok(())
    }

    async fn auto_optimize(&mut self) -> Result<()> {
        // Implementation would apply automatic optimizations
        Ok(())
    }

    async fn cleanup_old_data(&mut self) -> Result<()> {
        // Implementation would clean up old performance data
        Ok(())
    }

    async fn run_single_benchmark(&self, _benchmark: &Benchmark) -> Result<BenchmarkResult> {
        // Implementation would run individual benchmark
        Ok(BenchmarkResult {
            execution_time: Duration::from_millis(100),
            memory_used: 1024 * 1024, // 1MB
            cpu_time: Duration::from_millis(90),
            throughput: 100.0,
            success: true,
            metrics: HashMap::new(),
        })
    }

    fn calculate_summary_stats(&self, _results: &[(String, BenchmarkResult)]) -> BenchmarkSummary {
        BenchmarkSummary {
            total_benchmarks: 10,
            passed_benchmarks: 10,
            failed_benchmarks: 0,
            avg_execution_time: Duration::from_millis(100),
            total_memory_used: 10 * 1024 * 1024, // 10MB
            avg_throughput: 100.0,
        }
    }

    async fn detect_regressions(
        &self,
        _results: &[(String, BenchmarkResult)],
    ) -> Result<Vec<PerformanceRegression>> {
        Ok(Vec::new())
    }

    fn generate_recommendations(&self, _summary: &BenchmarkSummary) -> Vec<String> {
        vec!["Consider enabling cache optimization".to_string()]
    }

    async fn store_benchmark_results(&mut self, _report: &BenchmarkReport) -> Result<()> {
        Ok(())
    }

    async fn collect_system_info(&self) -> Result<SystemInfo> {
        Ok(SystemInfo {
            cpu_model: "Unknown".to_string(),
            total_memory_mb: 8192,
            os: std::env::consts::OS.to_string(),
            rust_version: "1.70.0".to_string(),
        })
    }

    async fn collect_codebase_info(&self) -> Result<CodebaseInfo> {
        Ok(CodebaseInfo {
            total_loc: 100000,
            file_count: 1000,
            avg_complexity: 5.2,
            primary_language: "rust".to_string(),
        })
    }

    async fn collect_baseline_measurements(&self) -> Result<HashMap<String, f64>> {
        let mut measurements = HashMap::new();
        measurements.insert("analysis_time_ms".to_string(), 150.0);
        measurements.insert("memory_mb".to_string(), 256.0);
        measurements.insert("throughput_fps".to_string(), 50.0);
        Ok(measurements)
    }

    fn calculate_config_hash(&self) -> String {
        // Would calculate hash of current configuration
        "config_hash_placeholder".to_string()
    }

    // Optimization implementations
    async fn optimize_caching(&mut self) -> Result<()> {
        Ok(())
    }
    async fn optimize_parallel_processing(&mut self) -> Result<()> {
        Ok(())
    }
    async fn optimize_memory_pooling(&mut self) -> Result<()> {
        Ok(())
    }
    async fn optimize_incremental_parsing(&mut self) -> Result<()> {
        Ok(())
    }
    async fn optimize_io(&mut self) -> Result<()> {
        Ok(())
    }
    async fn optimize_ast_reuse(&mut self) -> Result<()> {
        Ok(())
    }

    fn calculate_improvement(
        &self,
        baseline: &HashMap<String, f64>,
        optimized: &HashMap<String, f64>,
    ) -> f64 {
        // Calculate average improvement across all metrics
        let mut total_improvement = 0.0;
        let mut count = 0;

        for (key, baseline_value) in baseline {
            if let Some(optimized_value) = optimized.get(key) {
                let improvement = (baseline_value - optimized_value) / baseline_value * 100.0;
                total_improvement += improvement;
                count += 1;
            }
        }

        if count > 0 {
            total_improvement / f64::from(count)
        } else {
            0.0
        }
    }

    fn calculate_metrics_delta(
        &self,
        baseline: &HashMap<String, f64>,
        optimized: &HashMap<String, f64>,
    ) -> HashMap<String, f64> {
        let mut delta = HashMap::new();

        for (key, baseline_value) in baseline {
            if let Some(optimized_value) = optimized.get(key) {
                delta.insert(key.clone(), optimized_value - baseline_value);
            }
        }

        delta
    }

    fn get_recent_benchmark_results(&self, _count: usize) -> Vec<BenchmarkReport> {
        Vec::new() // Would return recent benchmark results
    }

    fn generate_system_recommendations(&self) -> Vec<String> {
        vec!["System appears to be performing well".to_string()]
    }

    fn generate_performance_alerts(&self) -> Vec<PerformanceAlert> {
        Vec::new() // Would generate performance alerts
    }
}