rustorch 0.6.29

//! Debug System Integration Tests
//! デバッグシステム統合テスト

#[cfg(test)]
mod debug_system_tests {
    use std::collections::HashMap;
    use std::thread;
    use std::time::Duration;

    /// Test basic debug framework functionality
    #[test]
    fn test_debug_framework_basics() {
        // Simulate debug framework operations
        let framework_active = true;
        let mut log_count = 0;
        let mut profile_count = 0;
        let mut memory_tracked = 0usize;

        // Basic logging simulation
        if framework_active {
            log_count += 1; // Info log
            log_count += 1; // Warning log
            log_count += 1; // Error log
        }

        // Performance profiling simulation
        if framework_active {
            let start = std::time::Instant::now();
            thread::sleep(Duration::from_millis(10));
            let elapsed = start.elapsed();

            if elapsed.as_millis() > 5 {
                profile_count += 1;
            }
        }

        // Memory tracking simulation
        if framework_active {
            memory_tracked += 1024 * 1024; // 1MB allocation
            memory_tracked += 512 * 1024; // 512KB allocation
        }

        assert_eq!(log_count, 3);
        assert_eq!(profile_count, 1);
        assert_eq!(memory_tracked, 1536 * 1024); // 1.5MB total

        println!(
            "Debug Framework Test: {} logs, {} profiles, {}KB tracked",
            log_count,
            profile_count,
            memory_tracked / 1024
        );
    }

    /// Test structured logging concepts
    #[test]
    fn test_structured_logging() {
        // Simulate different log levels
        let log_levels = ["TRACE", "DEBUG", "INFO", "WARN", "ERROR", "CRITICAL"];
        let mut log_entries = Vec::new();

        for &level in log_levels.iter() {
            let entry = LogEntry {
                level: level.to_string(),
                metadata: create_test_metadata(level),
            };
            log_entries.push(entry);
        }

        // Test filtering
        let error_logs: Vec<_> = log_entries
            .iter()
            .filter(|entry| entry.level == "ERROR" || entry.level == "CRITICAL")
            .collect();

        assert_eq!(error_logs.len(), 2);
        assert_eq!(log_entries.len(), 6);

        // Test metadata
        for entry in &log_entries {
            assert!(!entry.metadata.is_empty());
            assert!(entry.metadata.contains_key("component"));
        }

        println!(
            "Structured Logging Test: {} entries, {} errors",
            log_entries.len(),
            error_logs.len()
        );
    }

    /// Test performance profiling concepts
    #[test]
    fn test_performance_profiling() {
        let mut operation_times = Vec::new();

        // Simulate different operations with varying performance
        let operations = [
            ("fast_op", 5),
            ("medium_op", 25),
            ("slow_op", 100),
            ("very_slow_op", 250),
        ];

        for (op_name, delay_ms) in operations.iter() {
            let start = std::time::Instant::now();
            thread::sleep(Duration::from_millis(*delay_ms as u64));
            let elapsed = start.elapsed();

            operation_times.push(ProfileEntry {
                operation_name: op_name.to_string(),
                duration_ms: elapsed.as_millis() as f64,
            });
        }

        // Calculate statistics
        let total_time: f64 = operation_times.iter().map(|entry| entry.duration_ms).sum();
        let average_time = total_time / operation_times.len() as f64;

        // Count slow operations (>=100ms)
        let slow_ops = operation_times
            .iter()
            .filter(|entry| entry.duration_ms >= 100.0)
            .count();

        assert_eq!(operation_times.len(), 4);
        assert!(average_time > 0.0);
        assert_eq!(slow_ops, 2); // very_slow_op (250ms) and slow_op (>=100ms)

        // Find bottlenecks
        let mut sorted_ops = operation_times.clone();
        sorted_ops.sort_by(|a, b| b.duration_ms.partial_cmp(&a.duration_ms).unwrap());

        let bottleneck = &sorted_ops[0];
        assert_eq!(bottleneck.operation_name, "very_slow_op");

        println!(
            "Performance Profiling Test: {:.1}ms avg, {} slow ops",
            average_time, slow_ops
        );
    }

    /// Test memory tracking concepts
    #[test]
    fn test_memory_tracking() {
        let mut memory_allocations = HashMap::new();
        let mut total_allocated = 0usize;

        // Simulate memory allocations by component
        let allocations = [
            ("tensor_ops", vec![1024 * 1024, 2048 * 1024, 512 * 1024]), // 3.5MB
            ("network", vec![4096 * 1024, 1024 * 1024]),                // 5MB
            ("optimizer", vec![512 * 1024, 256 * 1024]),                // 768KB
        ];

        for (component, sizes) in allocations.iter() {
            let component_total: usize = sizes.iter().sum();
            memory_allocations.insert(component.to_string(), component_total);
            total_allocated += component_total;
        }

        // Test memory statistics
        assert_eq!(memory_allocations.len(), 3);

        let expected_total = (3.5 + 5.0 + 0.75) * 1024.0 * 1024.0; // ~9.25MB
        assert!((total_allocated as f64 - expected_total).abs() < 1024.0);

        // Find largest consumer
        let max_component = memory_allocations
            .iter()
            .max_by_key(|(_, size)| *size)
            .unwrap();
        assert_eq!(*max_component.0, "network");

        // Test threshold checking
        let threshold_mb = 10;
        let current_usage_mb = total_allocated as f64 / (1024.0 * 1024.0);
        let over_threshold = current_usage_mb > threshold_mb as f64;

        assert!(!over_threshold);

        println!(
            "Memory Tracking Test: {:.1}MB total, {} components",
            current_usage_mb,
            memory_allocations.len()
        );
    }

    /// Test log pattern analysis
    #[test]
    fn test_log_pattern_analysis() {
        let log_messages = vec![
            "Operation completed successfully",
            "Out of memory error occurred",
            "Tensor shape mismatch: expected [3, 3], got [2, 2]",
            "CUDA error: device not available",
            "Network connection timeout after 30s",
            "Out of memory error occurred", // Duplicate
            "Performance warning: operation took 150ms",
            "Tensor shape mismatch: expected [10, 5], got [5, 10]", // Another shape error
        ];

        // Pattern detection simulation
        let mut pattern_counts = HashMap::new();

        for message in &log_messages {
            if message.contains("out of memory") || message.contains("Out of memory") {
                *pattern_counts.entry("out_of_memory").or_insert(0) += 1;
            }
            if message.contains("shape mismatch") || message.contains("Shape mismatch") {
                *pattern_counts.entry("shape_mismatch").or_insert(0) += 1;
            }
            if message.contains("CUDA error") || message.contains("cuda error") {
                *pattern_counts.entry("cuda_error").or_insert(0) += 1;
            }
            if message.contains("timeout") || message.contains("took") {
                *pattern_counts.entry("performance_issue").or_insert(0) += 1;
            }
        }

        // Test pattern detection results
        assert_eq!(*pattern_counts.get("out_of_memory").unwrap_or(&0), 2);
        assert_eq!(*pattern_counts.get("shape_mismatch").unwrap_or(&0), 2);
        assert_eq!(*pattern_counts.get("cuda_error").unwrap_or(&0), 1);
        assert_eq!(*pattern_counts.get("performance_issue").unwrap_or(&0), 2);

        // Test alert triggering simulation
        let mut alerts_triggered = 0;

        // Alert rule: >1 occurrence of critical patterns
        for (pattern, count) in &pattern_counts {
            if (*pattern == "out_of_memory" || *pattern == "cuda_error") && *count > 0 {
                alerts_triggered += 1;
            }
            if *pattern == "shape_mismatch" && *count > 1 {
                alerts_triggered += 1;
            }
        }

        assert_eq!(alerts_triggered, 3); // OOM, CUDA, Shape (>1)

        println!(
            "Pattern Analysis Test: {} patterns, {} alerts",
            pattern_counts.len(),
            alerts_triggered
        );
    }

    /// Test system diagnostics collection
    #[test]
    fn test_system_diagnostics() {
        // Simulate system information collection
        let system_info = SystemInfo {
            os: std::env::consts::OS.to_string(),
            architecture: std::env::consts::ARCH.to_string(),
            cpu_count: thread::available_parallelism()
                .map(|n| n.get())
                .unwrap_or(1),
            available_memory_mb: estimate_memory_mb(),
        };

        // Test system info validation
        assert!(!system_info.os.is_empty());
        assert!(!system_info.architecture.is_empty());
        assert!(system_info.cpu_count > 0);
        assert!(system_info.available_memory_mb > 0);

        // Test diagnostic context
        let mut diagnostic_context = DiagnosticContext {
            operation_name: "tensor_multiply".to_string(),
            parameters: HashMap::new(),
            error_context: None,
        };

        diagnostic_context
            .parameters
            .insert("matrix_size".to_string(), "1000x1000".to_string());
        diagnostic_context
            .parameters
            .insert("data_type".to_string(), "f32".to_string());

        // Simulate error context
        diagnostic_context.error_context =
            Some("Matrix multiplication failed due to insufficient memory".to_string());

        assert_eq!(diagnostic_context.operation_name, "tensor_multiply");
        assert_eq!(diagnostic_context.parameters.len(), 2);
        assert!(diagnostic_context.error_context.is_some());

        println!(
            "System Diagnostics Test: {} {}, {} CPUs, {}MB RAM",
            system_info.os,
            system_info.architecture,
            system_info.cpu_count,
            system_info.available_memory_mb
        );
    }

    /// Test debug framework integration
    #[test]
    fn test_debug_framework_integration() {
        let mut integration_stats = IntegrationStats::new();

        // Test logging integration
        integration_stats.log_message("INFO", "Framework initialized");
        integration_stats.log_message("DEBUG", "Starting tensor operation");
        integration_stats.log_message("ERROR", "Memory allocation failed");

        assert_eq!(integration_stats.total_logs, 3);
        assert_eq!(integration_stats.error_count, 1);

        // Test profiling integration
        let operation_duration = Duration::from_millis(75);
        integration_stats.record_profile("matrix_multiply", operation_duration);
        integration_stats.record_profile("activation_function", Duration::from_millis(5));

        assert_eq!(integration_stats.total_profiles, 2);
        assert_eq!(integration_stats.slow_operations, 1); // >50ms threshold

        // Test memory integration
        integration_stats.track_allocation("tensor", 2048 * 1024); // 2MB
        integration_stats.track_allocation("weights", 1024 * 1024); // 1MB

        assert_eq!(integration_stats.total_memory_mb(), 3.0);
        assert_eq!(integration_stats.allocation_count, 2);

        // Test analysis integration
        integration_stats.analyze_patterns();

        assert!(integration_stats.patterns_detected > 0);

        // Generate comprehensive report
        let report = integration_stats.generate_integration_report();
        assert!(report.contains("Integration Report"));
        assert!(report.contains("Logs: 3"));
        assert!(report.contains("Profiles: 2"));

        println!(
            "Integration Test: {} logs, {} profiles, {:.1}MB memory",
            integration_stats.total_logs,
            integration_stats.total_profiles,
            integration_stats.total_memory_mb()
        );
    }

    // Helper structures and functions for testing

    #[derive(Debug, Clone)]
    struct LogEntry {
        level: String,
        metadata: HashMap<String, String>,
    }

    #[derive(Debug, Clone)]
    struct ProfileEntry {
        operation_name: String,
        duration_ms: f64,
    }

    #[derive(Debug, Clone)]
    struct SystemInfo {
        os: String,
        architecture: String,
        cpu_count: usize,
        available_memory_mb: usize,
    }

    #[derive(Debug)]
    struct DiagnosticContext {
        operation_name: String,
        parameters: HashMap<String, String>,
        error_context: Option<String>,
    }

    #[derive(Debug)]
    struct IntegrationStats {
        total_logs: usize,
        error_count: usize,
        total_profiles: usize,
        slow_operations: usize,
        total_memory_bytes: usize,
        allocation_count: usize,
        patterns_detected: usize,
    }

    impl IntegrationStats {
        fn new() -> Self {
            Self {
                total_logs: 0,
                error_count: 0,
                total_profiles: 0,
                slow_operations: 0,
                total_memory_bytes: 0,
                allocation_count: 0,
                patterns_detected: 0,
            }
        }

        fn log_message(&mut self, level: &str, _message: &str) {
            self.total_logs += 1;
            if level == "ERROR" {
                self.error_count += 1;
            }
        }

        fn record_profile(&mut self, _operation: &str, duration: Duration) {
            self.total_profiles += 1;
            if duration.as_millis() > 50 {
                self.slow_operations += 1;
            }
        }

        fn track_allocation(&mut self, _component: &str, bytes: usize) {
            self.total_memory_bytes += bytes;
            self.allocation_count += 1;
        }

        fn total_memory_mb(&self) -> f64 {
            self.total_memory_bytes as f64 / (1024.0 * 1024.0)
        }

        fn analyze_patterns(&mut self) {
            // Simple pattern analysis simulation
            self.patterns_detected = (self.error_count + self.slow_operations).max(1);
        }

        fn generate_integration_report(&self) -> String {
            format!(
                "🔧 Debug Framework Integration Report\n\
                 =====================================\n\
                 Logs: {}\n\
                 Profiles: {}\n\
                 Memory: {:.1}MB\n\
                 Patterns: {}",
                self.total_logs,
                self.total_profiles,
                self.total_memory_mb(),
                self.patterns_detected
            )
        }
    }

    fn create_test_metadata(level: &str) -> HashMap<String, String> {
        let mut metadata = HashMap::new();
        metadata.insert("component".to_string(), "debug_test".to_string());
        metadata.insert("level".to_string(), level.to_string());
        metadata.insert("thread".to_string(), "main".to_string());
        metadata
    }

    fn estimate_memory_mb() -> usize {
        // Simplified memory estimation
        match std::env::consts::OS {
            "linux" | "macos" => 8192,
            "windows" => 16384,
            _ => 4096,
        }
    }

    #[allow(dead_code)]
    fn collect_relevant_env_vars() -> HashMap<String, String> {
        let mut env_vars = HashMap::new();

        // Collect some standard environment variables for testing
        if let Ok(path) = std::env::var("PATH") {
            env_vars.insert("PATH".to_string(), path.chars().take(100).collect());
        }

        if let Ok(home) = std::env::var("HOME") {
            env_vars.insert("HOME".to_string(), home);
        }

        env_vars.insert("TEST_ENV".to_string(), "debug_system_test".to_string());

        env_vars
    }
}