use clap::Parser;
use colored::*;
use console::Term;
use rand::prelude::*;
use rand::rng;
use std::{
    sync::{
        atomic::{AtomicBool, Ordering},
        Arc,
    },
    thread,
    time::{Duration, Instant},
};

mod activities;
mod config;
mod display;
mod generators;
mod types;
use types::{Complexity, DevelopmentType, JargonLevel};

/// A CLI tool that generates impressive-looking terminal output when stakeholders walk by
#[derive(Parser, Debug)]
#[command(author, version, about, long_about = None)]
struct Args {
    /// Type of development activity to simulate
    #[arg(short, long, value_enum, default_value_t = DevelopmentType::Backend)]
    dev_type: DevelopmentType,

    /// Level of technical jargon in output
    #[arg(short, long, value_enum, default_value_t = JargonLevel::Medium)]
    jargon: JargonLevel,

    /// How busy and complex the output should appear
    #[arg(short, long, value_enum, default_value_t = Complexity::Medium)]
    complexity: Complexity,

    /// Duration in seconds to run (0 = run until interrupted)
    #[arg(short = 'T', long, default_value_t = 0)]
    duration: u64,

    /// Show critical system alerts or issues
    #[arg(short, long, default_value_t = false)]
    alerts: bool,

    /// Simulate a specific project
    #[arg(short, long, default_value = "distributed-cluster")]
    project: String,

    /// Use less colorful output
    #[arg(long, default_value_t = false)]
    minimal: bool,

    /// Show team collaboration activity
    #[arg(short, long, default_value_t = false)]
    team: bool,

    /// Simulate a specific framework usage
    #[arg(short = 'F', long, default_value = "")]
    framework: String,
}

fn main() {
    let args = Args::parse();
    let config = config::SessionConfig {
        dev_type: args.dev_type,
        jargon_level: args.jargon,
        complexity: args.complexity,
        alerts_enabled: args.alerts,
        project_name: args.project,
        minimal_output: args.minimal,
        team_activity: args.team,
        framework: args.framework,
    };
    let running = Arc::new(AtomicBool::new(true));
    let r = running.clone();
    ctrlc::set_handler(move || {
        r.store(false, Ordering::SeqCst);
    })
    .expect("Error setting Ctrl-C handler");
    let term = Term::stdout();
    let _ = term.clear_screen();
    display::display_boot_sequence(&config);
    let start_time = Instant::now();
    let target_duration = if args.duration > 0 {
        Some(Duration::from_secs(args.duration))
    } else {
        None
    };
    while running.load(Ordering::SeqCst) {
        if let Some(duration) = target_duration {
            if start_time.elapsed() >= duration {
                break;
            }
        }
        let activities_count = match config.complexity {
            Complexity::Low => 1,
            Complexity::Medium => 2,
            Complexity::High => 3,
            Complexity::Extreme => 4,
        };
        let mut activities: Vec<fn(&config::SessionConfig)> = vec![
            activities::run_code_analysis,
            activities::run_performance_metrics,
            activities::run_system_monitoring,
            activities::run_data_processing,
            activities::run_network_activity,
        ];
        activities.shuffle(&mut rng());
        for activity in activities.iter().take(activities_count) {
            activity(&config);
            let pause_time = rng().random_range(100..500);
            thread::sleep(Duration::from_millis(pause_time));
            if !running.load(Ordering::SeqCst)
                || (target_duration.is_some() && start_time.elapsed() >= target_duration.unwrap())
            {
                break;
            }
        }
        if config.alerts_enabled && rng().random_ratio(1, 10) {
            display::display_random_alert(&config);
        }
        if config.team_activity && rng().random_ratio(1, 5) {
            display::display_team_activity(&config);
        }
    }
    let _ = term.clear_screen();
    println!("{}", "Session terminated.".bright_green());
}

use crate::config::SessionConfig;
use crate::generators::{
    code_analyzer, data_processing, jargon, metrics, network_activity, system_monitoring,
};
use crate::types::{DevelopmentType, JargonLevel};
use colored::*;
use indicatif::{ProgressBar, ProgressStyle};
use rand::{prelude::*, rng};
use std::{thread, time::Duration};

pub fn run_code_analysis(config: &SessionConfig) {
    let files_to_analyze = rng().random_range(5..25);
    let total_lines = rng().random_range(1000..10000);

    let framework_specific = if !config.framework.is_empty() {
        format!(" ({} specific)", config.framework)
    } else {
        String::new()
    };

    let title = match config.dev_type {
        DevelopmentType::Backend => format!(
            "🔍 Running Code Analysis on API Components{}",
            framework_specific
        ),
        DevelopmentType::Frontend => format!("🔍 Analyzing UI Components{}", framework_specific),
        DevelopmentType::Fullstack => "🔍 Analyzing Full-Stack Integration Points".to_string(),
        DevelopmentType::DataScience => "🔍 Analyzing Data Pipeline Components".to_string(),
        DevelopmentType::DevOps => "🔍 Analyzing Infrastructure Configuration".to_string(),
        DevelopmentType::Blockchain => "🔍 Analyzing Smart Contract Security".to_string(),
        DevelopmentType::MachineLearning => "🔍 Analyzing Model Prediction Accuracy".to_string(),
        DevelopmentType::SystemsProgramming => "🔍 Analyzing Memory Safety Patterns".to_string(),
        DevelopmentType::GameDevelopment => "🔍 Analyzing Game Physics Components".to_string(),
        DevelopmentType::Security => "🔍 Running Security Vulnerability Scan".to_string(),
    };

    println!(
        "{}",
        if config.minimal_output {
            title.clone()
        } else {
            title.bold().bright_blue().to_string()
        }
    );

    let pb = ProgressBar::new(files_to_analyze);
    pb.set_style(ProgressStyle::default_bar()
        .template("{spinner:.green} [{elapsed_precise}] [{bar:40.cyan/blue}] {pos}/{len} files ({eta})")
        .unwrap()
        .progress_chars("▰▰▱"));

    for i in 0..files_to_analyze {
        pb.set_position(i);

        if rng().random_ratio(1, 3) {
            let file_name = code_analyzer::generate_filename(config.dev_type);
            let issue_type = code_analyzer::generate_code_issue(config.dev_type);
            let complexity = code_analyzer::generate_complexity_metric();

            let message = if rng().random_ratio(1, 4) {
                format!("  ⚠ {} - {}: {}", file_name, issue_type, complexity)
            } else {
                format!("  ✓ {} - {}", file_name, complexity)
            };

            pb.println(message);
        }

        thread::sleep(Duration::from_millis(rng().random_range(100..300)));
    }

    pb.finish();

    // Final analysis summary
    let issues_found = rng().random_range(0..5);
    let code_quality = rng().random_range(85..99);
    let tech_debt = rng().random_range(1..15);

    println!(
        "📊 Analysis Complete: {} files, {} lines of code",
        files_to_analyze, total_lines
    );
    println!("  - Issues found: {}", issues_found);
    println!("  - Code quality score: {}%", code_quality);
    println!("  - Technical debt: {}%", tech_debt);

    if config.jargon_level >= JargonLevel::Medium {
        println!(
            "  - {}",
            jargon::generate_code_jargon(config.dev_type, config.jargon_level)
        );
    }

    println!();
}

pub fn run_performance_metrics(config: &SessionConfig) {
    let title = match config.dev_type {
        DevelopmentType::Backend => "⚡ Analyzing API Response Time".to_string(),
        DevelopmentType::Frontend => "⚡ Measuring UI Rendering Performance".to_string(),
        DevelopmentType::Fullstack => "⚡ Evaluating End-to-End Performance".to_string(),
        DevelopmentType::DataScience => "⚡ Benchmarking Data Processing Pipeline".to_string(),
        DevelopmentType::DevOps => "⚡ Evaluating Infrastructure Scalability".to_string(),
        DevelopmentType::Blockchain => "⚡ Measuring Transaction Throughput".to_string(),
        DevelopmentType::MachineLearning => "⚡ Benchmarking Model Training Speed".to_string(),
        DevelopmentType::SystemsProgramming => {
            "⚡ Measuring Memory Allocation Efficiency".to_string()
        }
        DevelopmentType::GameDevelopment => "⚡ Analyzing Frame Rate Optimization".to_string(),
        DevelopmentType::Security => "⚡ Benchmarking Encryption Performance".to_string(),
    };

    println!(
        "{}",
        if config.minimal_output {
            title.clone()
        } else {
            title.bold().bright_yellow().to_string()
        }
    );

    let iterations = rng().random_range(50..200);
    let pb = ProgressBar::new(iterations);
    pb.set_style(ProgressStyle::default_bar()
        .template("{spinner:.yellow} [{elapsed_precise}] [{bar:40.yellow/blue}] {pos}/{len} samples ({eta})")
        .unwrap()
        .progress_chars("▰▱▱"));

    let mut performance_data: Vec<f64> = Vec::new();

    for i in 0..iterations {
        pb.set_position(i);

        // Generate realistic-looking performance numbers (time in ms)
        let base_perf = match config.dev_type {
            DevelopmentType::Backend => rng().random_range(20.0..80.0),
            DevelopmentType::Frontend => rng().random_range(5.0..30.0),
            DevelopmentType::DataScience => rng().random_range(100.0..500.0),
            DevelopmentType::Blockchain => rng().random_range(200.0..800.0),
            DevelopmentType::MachineLearning => rng().random_range(300.0..900.0),
            _ => rng().random_range(10.0..100.0),
        };

        // Add some variation but keep it somewhat consistent
        let jitter = rng().random_range(-5.0..5.0);
        let perf_value = f64::max(base_perf + jitter, 1.0);
        performance_data.push(perf_value);

        if i % 10 == 0 && rng().random_ratio(1, 3) {
            let metric_name = metrics::generate_performance_metric(config.dev_type);
            let metric_value = rng().random_range(10..999);
            let metric_unit = metrics::generate_metric_unit(config.dev_type);

            pb.println(format!(
                "  📊 {}: {} {}",
                metric_name, metric_value, metric_unit
            ));
        }

        thread::sleep(Duration::from_millis(rng().random_range(50..100)));
    }

    pb.finish();

    // Calculate and display metrics
    performance_data.sort_by(|a, b| a.partial_cmp(b).unwrap());
    let avg = performance_data.iter().sum::<f64>() / performance_data.len() as f64;
    let median = performance_data[performance_data.len() / 2];
    let p95 = performance_data[(performance_data.len() as f64 * 0.95) as usize];
    let p99 = performance_data[(performance_data.len() as f64 * 0.99) as usize];

    let unit = match config.dev_type {
        DevelopmentType::DataScience | DevelopmentType::MachineLearning => "seconds",
        _ => "milliseconds",
    };

    println!("📈 Performance Results:");
    println!("  - Average: {:.2} {}", avg, unit);
    println!("  - Median: {:.2} {}", median, unit);
    println!("  - P95: {:.2} {}", p95, unit);
    println!("  - P99: {:.2} {}", p99, unit);

    // Add optimization recommendations based on dev type
    let rec = metrics::generate_optimization_recommendation(config.dev_type);
    println!("💡 Recommendation: {}", rec);

    if config.jargon_level >= JargonLevel::Medium {
        println!(
            "  - {}",
            jargon::generate_performance_jargon(config.dev_type, config.jargon_level)
        );
    }

    println!();
}

pub fn run_system_monitoring(config: &SessionConfig) {
    let title = "🖥 System Resource Monitoring".to_string();
    println!(
        "{}",
        if config.minimal_output {
            title.clone()
        } else {
            title.bold().bright_green().to_string()
        }
    );

    let duration = rng().random_range(5..15);
    let pb = ProgressBar::new(duration);
    pb.set_style(
        ProgressStyle::default_bar()
            .template(
                "{spinner:.green} [{elapsed_precise}] [{bar:40.green/blue}] {pos}/{len} seconds",
            )
            .unwrap()
            .progress_chars("▰▱▱"),
    );

    let cpu_base = rng().random_range(10..60);
    let memory_base = rng().random_range(30..70);
    let network_base = rng().random_range(1..20);
    let disk_base = rng().random_range(5..40);

    for i in 0..duration {
        pb.set_position(i);

        // Generate slightly varied metrics for realistic fluctuation
        let cpu = cpu_base + rng().random_range(-5..10);
        let memory = memory_base + rng().random_range(-3..5);
        let network = network_base + rng().random_range(-1..3);
        let disk = disk_base + rng().random_range(-2..4);

        let processes = rng().random_range(80..200);

        let cpu_str = if cpu > 80 {
            format!("{}% (!)", cpu).red().to_string()
        } else if cpu > 60 {
            format!("{}% (!)", cpu).yellow().to_string()
        } else {
            format!("{}%", cpu).normal().to_string()
        };

        let mem_str = if memory > 85 {
            format!("{}%", memory).red().to_string()
        } else if memory > 70 {
            format!("{}%", memory).yellow().to_string()
        } else {
            format!("{}%", memory).normal().to_string()
        };

        let stats = format!(
            "  CPU: {}  |  RAM: {}  |  Network: {} MB/s  |  Disk I/O: {} MB/s  |  Processes: {}",
            cpu_str, mem_str, network, disk, processes
        );

        pb.println(if config.minimal_output {
            stats.clone()
        } else {
            stats
        });

        if i % 3 == 0 && rng().random_ratio(1, 3) {
            let system_event = system_monitoring::generate_system_event();
            pb.println(format!("  🔄 {}", system_event));
        }

        thread::sleep(Duration::from_millis(rng().random_range(200..500)));
    }

    pb.finish();

    // Display summary
    println!("📊 Resource Utilization Summary:");
    println!("  - Peak CPU: {}%", cpu_base + rng().random_range(5..15));
    println!(
        "  - Peak Memory: {}%",
        memory_base + rng().random_range(5..15)
    );
    println!(
        "  - Network Throughput: {} MB/s",
        network_base + rng().random_range(5..10)
    );
    println!(
        "  - Disk Throughput: {} MB/s",
        disk_base + rng().random_range(2..8)
    );
    println!(
        "  - {}",
        system_monitoring::generate_system_recommendation()
    );
    println!();
}

pub fn run_data_processing(config: &SessionConfig) {
    let operations = rng().random_range(5..20);

    let title = match config.dev_type {
        DevelopmentType::Backend => "🔄 Processing API Data Streams".to_string(),
        DevelopmentType::Frontend => "🔄 Processing User Interaction Data".to_string(),
        DevelopmentType::Fullstack => "🔄 Synchronizing Client-Server Data".to_string(),
        DevelopmentType::DataScience => "🔄 Running Data Transformation Pipeline".to_string(),
        DevelopmentType::DevOps => "🔄 Analyzing System Logs".to_string(),
        DevelopmentType::Blockchain => "🔄 Validating Transaction Blocks".to_string(),
        DevelopmentType::MachineLearning => "🔄 Processing Training Data Batches".to_string(),
        DevelopmentType::SystemsProgramming => "🔄 Optimizing Memory Access Patterns".to_string(),
        DevelopmentType::GameDevelopment => "🔄 Processing Game Asset Pipeline".to_string(),
        DevelopmentType::Security => "🔄 Analyzing Security Event Logs".to_string(),
    };

    println!(
        "{}",
        if config.minimal_output {
            title.clone()
        } else {
            title.bold().bright_cyan().to_string()
        }
    );

    for _ in 0..operations {
        let operation = data_processing::generate_data_operation(config.dev_type);
        let records = rng().random_range(100..10000);
        let size = rng().random_range(1..100);
        let size_unit = if rng().random_ratio(1, 4) { "GB" } else { "MB" };

        println!(
            "  🔄 {} {} records ({} {})",
            operation, records, size, size_unit
        );

        // Sometimes add sub-tasks with progress bars
        if rng().random_ratio(1, 3) {
            let subtasks = rng().random_range(10..30);
            let pb = ProgressBar::new(subtasks);
            pb.set_style(
                ProgressStyle::default_bar()
                    .template(
                        "     {spinner:.blue} [{elapsed_precise}] [{bar:30.cyan/blue}] {pos}/{len}",
                    )
                    .unwrap()
                    .progress_chars("▰▱▱"),
            );

            for i in 0..subtasks {
                pb.set_position(i);
                thread::sleep(Duration::from_millis(rng().random_range(20..100)));

                if rng().random_ratio(1, 8) {
                    let sub_operation =
                        data_processing::generate_data_sub_operation(config.dev_type);
                    pb.println(format!("       - {}", sub_operation));
                }
            }

            pb.finish_and_clear();
        } else {
            thread::sleep(Duration::from_millis(rng().random_range(300..800)));
        }

        // Add some details about the operation
        if rng().random_ratio(1, 2) {
            let details = data_processing::generate_data_details(config.dev_type);
            println!("     ✓ {}", details);
        }
    }

    // Add a summary
    let processed_records = rng().random_range(10000..1000000);
    let processing_rate = rng().random_range(1000..10000);
    let total_size = rng().random_range(10..500);
    let time_saved = rng().random_range(10..60);

    println!("📊 Data Processing Summary:");
    println!("  - Records processed: {}", processed_records);
    println!("  - Processing rate: {} records/sec", processing_rate);
    println!("  - Total data size: {} GB", total_size);
    println!("  - Estimated time saved: {} minutes", time_saved);

    if config.jargon_level >= JargonLevel::Medium {
        println!(
            "  - {}",
            jargon::generate_data_jargon(config.dev_type, config.jargon_level)
        );
    }

    println!();
}

pub fn run_network_activity(config: &SessionConfig) {
    let title = match config.dev_type {
        DevelopmentType::Backend => "🌐 Monitoring API Network Traffic".to_string(),
        DevelopmentType::Frontend => "🌐 Analyzing Client-Side Network Requests".to_string(),
        DevelopmentType::Fullstack => "🌐 Optimizing Client-Server Communication".to_string(),
        DevelopmentType::DataScience => "🌐 Synchronizing Distributed Data Nodes".to_string(),
        DevelopmentType::DevOps => "🌐 Monitoring Infrastructure Network".to_string(),
        DevelopmentType::Blockchain => "🌐 Monitoring Blockchain Network".to_string(),
        DevelopmentType::MachineLearning => "🌐 Distributing Model Training".to_string(),
        DevelopmentType::SystemsProgramming => {
            "🌐 Analyzing Network Protocol Efficiency".to_string()
        }
        DevelopmentType::GameDevelopment => {
            "🌐 Simulating Multiplayer Network Conditions".to_string()
        }
        DevelopmentType::Security => "🌐 Analyzing Network Security Patterns".to_string(),
    };

    println!(
        "{}",
        if config.minimal_output {
            title.clone()
        } else {
            title.bold().bright_magenta().to_string()
        }
    );

    let requests = rng().random_range(5..15);

    for _ in 0..requests {
        let endpoint = network_activity::generate_endpoint(config.dev_type);
        let method = network_activity::generate_method();
        let status = network_activity::generate_status();
        let size = rng().random_range(1..1000);
        let time = rng().random_range(10..500);

        let method_colored = match method.as_str() {
            "GET" => method.green(),
            "POST" => method.blue(),
            "PUT" => method.yellow(),
            "DELETE" => method.red(),
            _ => method.normal(),
        };

        let status_colored = if (200..300).contains(&status) {
            status.to_string().green()
        } else if (300..400).contains(&status) {
            status.to_string().yellow()
        } else {
            status.to_string().red()
        };

        let request_line = format!(
            "  {} {} → {} | {} ms | {} KB",
            if config.minimal_output {
                method.to_string()
            } else {
                method_colored.to_string()
            },
            endpoint,
            if config.minimal_output {
                status.to_string()
            } else {
                status_colored.to_string()
            },
            time,
            size
        );

        println!("{}", request_line);

        // Sometimes add request details
        if rng().random_ratio(1, 3) {
            let details = network_activity::generate_request_details(config.dev_type);
            println!("     ↳ {}", details);
        }

        thread::sleep(Duration::from_millis(rng().random_range(100..400)));
    }

    // Add summary
    let total_requests = rng().random_range(1000..10000);
    let avg_response = rng().random_range(50..200);
    let success_rate = rng().random_range(95..100);
    let bandwidth = rng().random_range(10..100);

    println!("📊 Network Activity Summary:");
    println!("  - Total requests: {}", total_requests);
    println!("  - Average response time: {} ms", avg_response);
    println!("  - Success rate: {}%", success_rate);
    println!("  - Bandwidth utilization: {} MB/s", bandwidth);

    if config.jargon_level >= JargonLevel::Medium {
        println!(
            "  - {}",
            jargon::generate_network_jargon(config.dev_type, config.jargon_level)
        );
    }

    println!();
}

use crate::config::SessionConfig;
use crate::types::DevelopmentType;
use colored::*;
use indicatif::{ProgressBar, ProgressStyle};
use rand::{prelude::*, rng};
use std::{thread, time::Duration};

pub fn display_boot_sequence(config: &SessionConfig) {
    let pb = ProgressBar::new(100);
    pb.set_style(
        ProgressStyle::default_bar()
            .template(
                "{spinner:.green} [{elapsed_precise}] [{bar:40.cyan/blue}] {pos}/{len} ({eta})",
            )
            .unwrap()
            .progress_chars("##-"),
    );

    println!(
        "{}",
        "\nINITIALIZING DEVELOPMENT ENVIRONMENT"
            .bold()
            .bright_cyan()
    );

    let project_display = if config.minimal_output {
        config.project_name.clone()
    } else {
        config
            .project_name
            .to_uppercase()
            .bold()
            .bright_yellow()
            .to_string()
    };

    println!("Project: {}", project_display);

    let dev_type_str = format!("{:?}", config.dev_type).to_string();
    println!(
        "Environment: {} Development",
        if config.minimal_output {
            dev_type_str
        } else {
            dev_type_str.bright_green().to_string()
        }
    );

    if !config.framework.is_empty() {
        let framework_display = if config.minimal_output {
            config.framework.clone()
        } else {
            config.framework.bright_blue().to_string()
        };
        println!("Framework: {}", framework_display);
    }

    println!();

    for i in 0..=100 {
        pb.set_position(i);

        if i % 20 == 0 {
            let message = match i {
                0 => "Loading configuration files...",
                20 => "Establishing secure connections...",
                40 => "Initializing development modules...",
                60 => "Syncing with repository...",
                80 => "Analyzing code dependencies...",
                100 => "Environment ready!",
                _ => "",
            };

            if !message.is_empty() {
                pb.println(format!("  {}", message));
            }
        }

        thread::sleep(Duration::from_millis(rng().random_range(50..100)));
    }

    pb.finish_and_clear();
    println!(
        "\n{}\n",
        "✅ DEVELOPMENT ENVIRONMENT INITIALIZED"
            .bold()
            .bright_green()
    );
    thread::sleep(Duration::from_millis(500));
}

pub fn display_random_alert(config: &SessionConfig) {
    let alert_types = [
        "SECURITY",
        "PERFORMANCE",
        "RESOURCE",
        "DEPLOYMENT",
        "COMPLIANCE",
    ];

    let alert_type = alert_types.choose(&mut rng()).unwrap();
    let severity = if rng().random_ratio(1, 4) {
        "CRITICAL"
    } else if rng().random_ratio(1, 3) {
        "HIGH"
    } else {
        "MEDIUM"
    };

    let alert_message = match *alert_type {
        "SECURITY" => match config.dev_type {
            DevelopmentType::Security => {
                "Potential intrusion attempt detected on production server"
            }
            DevelopmentType::Backend => "API authentication token expiration approaching",
            DevelopmentType::Frontend => {
                "Cross-site scripting vulnerability detected in form input"
            }
            DevelopmentType::Blockchain => {
                "Smart contract privilege escalation vulnerability detected"
            }
            _ => "Unusual login pattern detected in production environment",
        },
        "PERFORMANCE" => match config.dev_type {
            DevelopmentType::Backend => {
                "API response time degradation detected in payment endpoint"
            }
            DevelopmentType::Frontend => "Rendering performance issue detected in main dashboard",
            DevelopmentType::DataScience => "Data processing pipeline throughput reduced by 25%",
            DevelopmentType::MachineLearning => "Model inference latency exceeding threshold",
            _ => "Performance regression detected in latest deployment",
        },
        "RESOURCE" => match config.dev_type {
            DevelopmentType::DevOps => "Kubernetes cluster resource allocation approaching limit",
            DevelopmentType::Backend => "Database connection pool nearing capacity",
            DevelopmentType::DataScience => "Data processing job memory usage exceeding allocation",
            _ => "System resource utilization approaching threshold",
        },
        "DEPLOYMENT" => match config.dev_type {
            DevelopmentType::DevOps => "Canary deployment showing increased error rate",
            DevelopmentType::Backend => "Service deployment incomplete on 3 nodes",
            DevelopmentType::Frontend => "Asset optimization failed in production build",
            _ => "CI/CD pipeline failure detected in release branch",
        },
        "COMPLIANCE" => match config.dev_type {
            DevelopmentType::Security => "Potential data handling policy violation detected",
            DevelopmentType::Backend => "API endpoint missing required audit logging",
            DevelopmentType::Blockchain => "Smart contract failing regulatory compliance check",
            _ => "Code scan detected potential compliance issue",
        },
        _ => "System alert condition detected",
    };

    let severity_color = match severity {
        "CRITICAL" => "bright_red",
        "HIGH" => "bright_yellow",
        "MEDIUM" => "bright_cyan",
        _ => "normal",
    };

    let alert_display = format!("🚨 {} ALERT [{}]: {}", alert_type, severity, alert_message);

    if config.minimal_output {
        println!("{}", alert_display);
    } else {
        match severity_color {
            "bright_red" => println!("{}", alert_display.bright_red().bold()),
            "bright_yellow" => println!("{}", alert_display.bright_yellow().bold()),
            "bright_cyan" => println!("{}", alert_display.bright_cyan().bold()),
            _ => println!("{}", alert_display),
        }
    }

    // Show automated response action
    let response_action = match *alert_type {
        "SECURITY" => "Initiating security protocol and notifying security team",
        "PERFORMANCE" => "Analyzing performance metrics and scaling resources",
        "RESOURCE" => "Optimizing resource allocation and preparing scaling plan",
        "DEPLOYMENT" => "Running deployment recovery procedure and notifying DevOps",
        "COMPLIANCE" => "Documenting issue and preparing compliance report",
        _ => "Initiating standard recovery procedure",
    };

    println!("  ↳ AUTOMATED RESPONSE: {}", response_action);
    println!();

    // Pause for dramatic effect
    thread::sleep(Duration::from_millis(1000));
}

pub fn display_team_activity(config: &SessionConfig) {
    let team_names = [
        "Alice", "Bob", "Carlos", "Diana", "Eva", "Felix", "Grace", "Hector", "Irene", "Jack",
    ];
    let team_member = team_names.choose(&mut rng()).unwrap();

    let activities = match config.dev_type {
        DevelopmentType::Backend => [
            "pushed new API endpoint implementation",
            "requested code review on service layer refactoring",
            "merged database optimization pull request",
            "commented on your API authentication PR",
            "resolved 3 high-priority backend bugs",
        ],
        DevelopmentType::Frontend => [
            "updated UI component library",
            "pushed new responsive design implementation",
            "fixed cross-browser compatibility issue",
            "requested review on animation performance PR",
            "updated design system documentation",
        ],
        DevelopmentType::Fullstack => [
            "implemented end-to-end feature integration",
            "fixed client-server sync issue",
            "updated full-stack deployment pipeline",
            "refactored shared validation logic",
            "documented API integration patterns",
        ],
        DevelopmentType::DataScience => [
            "updated data transformation pipeline",
            "shared new analysis notebook",
            "optimized data aggregation queries",
            "updated visualization dashboard",
            "documented new data metrics",
        ],
        DevelopmentType::DevOps => [
            "updated Kubernetes configuration",
            "improved CI/CD pipeline performance",
            "added new monitoring alerts",
            "fixed auto-scaling configuration",
            "updated infrastructure documentation",
        ],
        DevelopmentType::Blockchain => [
            "optimized smart contract gas usage",
            "implemented new transaction validation",
            "updated consensus algorithm implementation",
            "fixed wallet integration issue",
            "documented token economics model",
        ],
        DevelopmentType::MachineLearning => [
            "shared improved model accuracy results",
            "optimized model training pipeline",
            "added new feature extraction method",
            "implemented model versioning system",
            "documented model evaluation metrics",
        ],
        DevelopmentType::SystemsProgramming => [
            "optimized memory allocation strategy",
            "reduced thread contention in core module",
            "implemented lock-free data structure",
            "fixed race condition in scheduler",
            "documented concurrency pattern usage",
        ],
        DevelopmentType::GameDevelopment => [
            "optimized rendering pipeline",
            "fixed physics collision detection issue",
            "implemented new particle effect system",
            "reduced loading time by 30%",
            "documented game engine architecture",
        ],
        DevelopmentType::Security => [
            "implemented additional encryption layer",
            "fixed authentication bypass vulnerability",
            "updated security scanning rules",
            "implemented improved access control",
            "documented security compliance requirements",
        ],
    };

    let activity = activities.choose(&mut rng()).unwrap();
    let minutes_ago = rng().random_range(1..30);
    let notification = format!(
        "👥 TEAM: {} {} ({} minutes ago)",
        team_member, activity, minutes_ago
    );

    println!(
        "{}",
        if config.minimal_output {
            notification
        } else {
            notification.bright_cyan().to_string()
        }
    );

    // Sometimes add a requested action
    if rng().random_ratio(1, 2) {
        let actions = [
            "Review requested on PR #342",
            "Mentioned you in a comment",
            "Assigned ticket DEV-867 to you",
            "Requested your input on design decision",
            "Shared documentation for your review",
        ];

        let action = actions.choose(&mut rng()).unwrap();
        println!("  ↳ ACTION NEEDED: {}", action);
    }

    println!();

    // Short pause to notice the team activity
    thread::sleep(Duration::from_millis(800));
}

use crate::DevelopmentType;
use rand::{prelude::*, rng};

pub fn generate_filename(dev_type: DevelopmentType) -> String {
    let extensions = match dev_type {
        DevelopmentType::Backend => [
            "rs", "go", "java", "py", "js", "ts", "rb", "php", "cs", "scala",
        ],
        DevelopmentType::Frontend => [
            "js", "ts", "jsx", "tsx", "vue", "scss", "css", "html", "svelte", "elm",
        ],
        DevelopmentType::Fullstack => [
            "js", "ts", "rs", "go", "py", "jsx", "tsx", "vue", "rb", "php",
        ],
        DevelopmentType::DataScience => [
            "py", "ipynb", "R", "jl", "scala", "sql", "m", "stan", "cpp", "h",
        ],
        DevelopmentType::DevOps => [
            "yaml",
            "yml",
            "tf",
            "hcl",
            "sh",
            "Dockerfile",
            "json",
            "toml",
            "ini",
            "conf",
        ],
        DevelopmentType::Blockchain => [
            "sol", "rs", "go", "js", "ts", "wasm", "move", "cairo", "vy", "cpp",
        ],
        DevelopmentType::MachineLearning => [
            "py", "ipynb", "pth", "h5", "pb", "tflite", "onnx", "pt", "cpp", "cu",
        ],
        DevelopmentType::SystemsProgramming => {
            ["rs", "c", "cpp", "h", "hpp", "asm", "s", "go", "zig", "d"]
        }
        DevelopmentType::GameDevelopment => [
            "cpp", "h", "cs", "js", "ts", "glsl", "hlsl", "shader", "unity", "prefab",
        ],
        DevelopmentType::Security => [
            "rs", "go", "c", "cpp", "py", "java", "js", "ts", "rb", "php",
        ],
    };

    let components = match dev_type {
        DevelopmentType::Backend => [
            "Service",
            "Controller",
            "Repository",
            "DAO",
            "Manager",
            "Factory",
            "Provider",
            "Client",
            "Handler",
            "Middleware",
            "Interceptor",
            "Connector",
            "Processor",
            "Worker",
            "Queue",
            "Cache",
            "Store",
            "Adapter",
            "Wrapper",
            "Mapper",
        ],
        DevelopmentType::Frontend => [
            "Component",
            "Container",
            "Page",
            "View",
            "Screen",
            "Element",
            "Layout",
            "Widget",
            "Hook",
            "Context",
            "Provider",
            "Reducer",
            "Action",
            "State",
            "Form",
            "Modal",
            "Card",
            "Button",
            "Input",
            "Selector",
        ],
        DevelopmentType::Fullstack => [
            "Service",
            "Controller",
            "Component",
            "Container",
            "Connector",
            "Integration",
            "Provider",
            "Client",
            "Api",
            "Interface",
            "Bridge",
            "Adapter",
            "Manager",
            "Handler",
            "Processor",
            "Orchestrator",
            "Facade",
            "Proxy",
            "Wrapper",
            "Mapper",
        ],
        DevelopmentType::DataScience => [
            "Analysis",
            "Processor",
            "Transformer",
            "Pipeline",
            "Extractor",
            "Loader",
            "Model",
            "Predictor",
            "Classifier",
            "Regressor",
            "Clusterer",
            "Encoder",
            "Trainer",
            "Evaluator",
            "Feature",
            "Dataset",
            "Optimizer",
            "Validator",
            "Sampler",
            "Splitter",
        ],
        DevelopmentType::DevOps => [
            "Config",
            "Setup",
            "Deployment",
            "Pipeline",
            "Builder",
            "Runner",
            "Provisioner",
            "Monitor",
            "Logger",
            "Alerter",
            "Scanner",
            "Tester",
            "Backup",
            "Security",
            "Network",
            "Cluster",
            "Container",
            "Orchestrator",
            "Manager",
            "Scheduler",
        ],
        DevelopmentType::Blockchain => [
            "Contract",
            "Wallet",
            "Token",
            "Chain",
            "Block",
            "Transaction",
            "Validator",
            "Miner",
            "Node",
            "Consensus",
            "Ledger",
            "Network",
            "Pool",
            "Oracle",
            "Signer",
            "Verifier",
            "Bridge",
            "Protocol",
            "Exchange",
            "Market",
        ],
        DevelopmentType::MachineLearning => [
            "Model",
            "Trainer",
            "Predictor",
            "Pipeline",
            "Transformer",
            "Encoder",
            "Embedder",
            "Classifier",
            "Regressor",
            "Optimizer",
            "Layer",
            "Network",
            "DataLoader",
            "Preprocessor",
            "Evaluator",
            "Validator",
            "Callback",
            "Metric",
            "Loss",
            "Sampler",
        ],
        DevelopmentType::SystemsProgramming => [
            "Allocator",
            "Memory",
            "Thread",
            "Process",
            "Scheduler",
            "Dispatcher",
            "Device",
            "Driver",
            "Buffer",
            "Stream",
            "Channel",
            "IO",
            "FS",
            "Network",
            "Synchronizer",
            "Lock",
            "Atomic",
            "Signal",
            "Interrupt",
            "Handler",
        ],
        DevelopmentType::GameDevelopment => [
            "Engine",
            "Renderer",
            "Physics",
            "Audio",
            "Input",
            "Entity",
            "Component",
            "System",
            "Scene",
            "Level",
            "Player",
            "Character",
            "Animation",
            "Sprite",
            "Camera",
            "Light",
            "Particle",
            "Collision",
            "AI",
            "Pathfinding",
        ],
        DevelopmentType::Security => [
            "Auth",
            "Identity",
            "Credential",
            "Token",
            "Certificate",
            "Encryption",
            "Hasher",
            "Signer",
            "Verifier",
            "Scanner",
            "Detector",
            "Analyzer",
            "Filter",
            "Firewall",
            "Proxy",
            "Inspector",
            "Monitor",
            "Logger",
            "Policy",
            "Permission",
        ],
    };

    let domain_prefixes = match dev_type {
        DevelopmentType::Backend => [
            "User",
            "Account",
            "Order",
            "Payment",
            "Product",
            "Inventory",
            "Customer",
            "Shipment",
            "Transaction",
            "Notification",
            "Message",
            "Event",
            "Task",
            "Job",
            "Schedule",
            "Catalog",
            "Cart",
            "Recommendation",
            "Analytics",
            "Report",
        ],
        DevelopmentType::Frontend => [
            "User",
            "Auth",
            "Product",
            "Cart",
            "Checkout",
            "Profile",
            "Dashboard",
            "Settings",
            "Notification",
            "Message",
            "Search",
            "List",
            "Detail",
            "Home",
            "Landing",
            "Admin",
            "Modal",
            "Navigation",
            "Theme",
            "Responsive",
        ],
        _ => [
            "Core", "Main", "Base", "Shared", "Util", "Helper", "Abstract", "Default", "Custom",
            "Advanced", "Simple", "Complex", "Dynamic", "Static", "Global", "Local", "Internal",
            "External", "Public", "Private",
        ],
    };

    let prefix = if rng().random_ratio(2, 3) {
        domain_prefixes.choose(&mut rng()).unwrap()
    } else {
        components.choose(&mut rng()).unwrap()
    };

    let component = components.choose(&mut rng()).unwrap();
    let extension = extensions.choose(&mut rng()).unwrap();

    // Only use prefix if it's different from component
    if prefix == component {
        format!("{}.{}", component, extension)
    } else {
        format!("{}{}.{}", prefix, component, extension)
    }
}

pub fn generate_code_issue(dev_type: DevelopmentType) -> String {
    let common_issues = [
        "Unused variable",
        "Unreachable code",
        "Redundant calculation",
        "Missing error handling",
        "Inefficient algorithm",
        "Potential null reference",
        "Code duplication",
        "Overly complex method",
        "Deprecated API usage",
        "Resource leak",
    ];

    let specific_issues = match dev_type {
        DevelopmentType::Backend => [
            "Unoptimized database query",
            "Missing transaction boundary",
            "Potential SQL injection",
            "Inefficient connection management",
            "Improper error propagation",
            "Race condition in concurrent request handling",
            "Inadequate request validation",
            "Excessive logging",
            "Missing authentication check",
            "Insufficient rate limiting",
        ],
        DevelopmentType::Frontend => [
            "Unnecessary component re-rendering",
            "Unhandled promise rejection",
            "Excessive DOM manipulation",
            "Memory leak in event listener",
            "Non-accessible UI element",
            "Inconsistent styling approach",
            "Unoptimized asset loading",
            "Browser compatibility issue",
            "Inefficient state management",
            "Poor mobile responsiveness",
        ],
        DevelopmentType::Fullstack => [
            "Inconsistent data validation",
            "Redundant data transformation",
            "Inefficient client-server communication",
            "Mismatched data types",
            "Inconsistent error handling",
            "Overly coupled client-server logic",
            "Duplicated business logic",
            "Inconsistent state management",
            "Security vulnerability in API integration",
            "Race condition in state synchronization",
        ],
        DevelopmentType::DataScience => [
            "Potential data leakage",
            "Inadequate data normalization",
            "Inefficient data transformation",
            "Missing null value handling",
            "Improper train-test split",
            "Unoptimized feature selection",
            "Insufficient data validation",
            "Model overfitting risk",
            "Numerical instability in calculation",
            "Memory inefficient data processing",
        ],
        DevelopmentType::DevOps => [
            "Insecure configuration default",
            "Missing resource constraint",
            "Inadequate error recovery mechanism",
            "Inefficient resource allocation",
            "Hardcoded credential",
            "Insufficient monitoring setup",
            "Non-idempotent operation",
            "Missing backup strategy",
            "Inadequate security policy",
            "Inefficient deployment process",
        ],
        DevelopmentType::Blockchain => [
            "Gas inefficient operation",
            "Potential reentrancy vulnerability",
            "Improper access control",
            "Integer overflow/underflow risk",
            "Unchecked external call result",
            "Inadequate transaction validation",
            "Front-running vulnerability",
            "Improper randomness source",
            "Inefficient storage pattern",
            "Missing event emission",
        ],
        DevelopmentType::MachineLearning => [
            "Potential data leakage",
            "Inefficient model architecture",
            "Improper learning rate scheduling",
            "Unhandled gradient explosion risk",
            "Inefficient batch processing",
            "Inadequate model evaluation metric",
            "Memory inefficient tensor operation",
            "Missing early stopping criteria",
            "Unoptimized hyperparameter",
            "Inefficient feature engineering",
        ],
        DevelopmentType::SystemsProgramming => [
            "Potential memory leak",
            "Uninitialized memory access",
            "Thread synchronization issue",
            "Inefficient memory allocation",
            "Resource cleanup failure",
            "Buffer overflow risk",
            "Race condition in concurrent access",
            "Inefficient cache usage pattern",
            "Blocking I/O in critical path",
            "Undefined behavior risk",
        ],
        DevelopmentType::GameDevelopment => [
            "Inefficient rendering call",
            "Physics calculation in rendering thread",
            "Unoptimized asset loading",
            "Missing frame rate cap",
            "Memory fragmentation risk",
            "Inefficient collision detection",
            "Unoptimized shader complexity",
            "Animation state machine complexity",
            "Inefficient particle system update",
            "Missing object pooling",
        ],
        DevelopmentType::Security => [
            "Potential privilege escalation",
            "Insecure cryptographic algorithm",
            "Missing input validation",
            "Hardcoded credential",
            "Insufficient authentication check",
            "Security misconfiguration",
            "Inadequate error handling exposing details",
            "Missing rate limiting",
            "Insecure direct object reference",
            "Improper certificate validation",
        ],
    };

    if rng().random_ratio(1, 3) {
        common_issues.choose(&mut rng()).unwrap().to_string()
    } else {
        specific_issues.choose(&mut rng()).unwrap().to_string()
    }
}

pub fn generate_complexity_metric() -> String {
    let complexity_metrics = [
        "Cyclomatic complexity: 5 (good)",
        "Cyclomatic complexity: 8 (acceptable)",
        "Cyclomatic complexity: 12 (moderate)",
        "Cyclomatic complexity: 18 (high)",
        "Cyclomatic complexity: 25 (very high)",
        "Cognitive complexity: 4 (good)",
        "Cognitive complexity: 7 (acceptable)",
        "Cognitive complexity: 15 (moderate)",
        "Cognitive complexity: 22 (high)",
        "Cognitive complexity: 30 (very high)",
        "Maintainability index: 85 (highly maintainable)",
        "Maintainability index: 75 (maintainable)",
        "Maintainability index: 65 (moderately maintainable)",
        "Maintainability index: 55 (difficult to maintain)",
        "Maintainability index: 45 (very difficult to maintain)",
        "Lines of code: 25 (compact)",
        "Lines of code: 75 (moderate)",
        "Lines of code: 150 (large)",
        "Lines of code: 300 (very large)",
        "Lines of code: 500+ (extremely large)",
        "Nesting depth: 2 (good)",
        "Nesting depth: 3 (acceptable)",
        "Nesting depth: 4 (moderate)",
        "Nesting depth: 5 (high)",
        "Nesting depth: 6+ (very high)",
    ];

    complexity_metrics.choose(&mut rng()).unwrap().to_string()
}

use crate::{DevelopmentType, JargonLevel};
use rand::{prelude::*, rng};

pub fn generate_code_jargon(dev_type: DevelopmentType, level: JargonLevel) -> String {
    let basic_terms = match dev_type {
        DevelopmentType::Backend => [
            "Optimized query execution paths for improved database throughput",
            "Reduced API latency via connection pooling and request batching",
            "Implemented stateless authentication with JWT token rotation",
            "Applied circuit breaker pattern to prevent cascading failures",
            "Utilized CQRS pattern for complex domain operations",
        ],
        DevelopmentType::Frontend => [
            "Implemented virtual DOM diffing for optimal rendering performance",
            "Applied tree-shaking and code-splitting for bundle optimization",
            "Utilized CSS containment for layout performance improvement",
            "Implemented intersection observer for lazy-loading optimization",
            "Reduced reflow calculations with CSS will-change property",
        ],
        DevelopmentType::Fullstack => [
            "Optimized client-server data synchronization protocols",
            "Implemented isomorphic rendering for optimal user experience",
            "Applied domain-driven design across frontend and backend boundaries",
            "Utilized BFF pattern to optimize client-specific API responses",
            "Implemented event sourcing for consistent system state",
        ],
        DevelopmentType::DataScience => [
            "Applied regularization techniques to prevent overfitting",
            "Implemented feature engineering pipeline with dimensionality reduction",
            "Utilized distributed computing for parallel data processing",
            "Optimized data transformations with vectorized operations",
            "Applied statistical significance testing to validate results",
        ],
        DevelopmentType::DevOps => [
            "Implemented infrastructure as code with immutable deployment patterns",
            "Applied blue-green deployment strategy for zero-downtime updates",
            "Utilized service mesh for enhanced observability and traffic control",
            "Implemented GitOps workflow for declarative configuration management",
            "Applied chaos engineering principles to improve resilience",
        ],
        DevelopmentType::Blockchain => [
            "Optimized transaction validation through merkle tree verification",
            "Implemented sharding for improved blockchain throughput",
            "Applied zero-knowledge proofs for privacy-preserving transactions",
            "Utilized state channels for off-chain scaling optimization",
            "Implemented consensus algorithm with Byzantine fault tolerance",
        ],
        DevelopmentType::MachineLearning => [
            "Applied gradient boosting for improved model performance",
            "Implemented feature importance analysis for model interpretability",
            "Utilized transfer learning to optimize training efficiency",
            "Applied hyperparameter tuning with Bayesian optimization",
            "Implemented ensemble methods for model robustness",
        ],
        DevelopmentType::SystemsProgramming => [
            "Optimized cache locality with data-oriented design patterns",
            "Implemented zero-copy memory management for I/O operations",
            "Applied lock-free algorithms for concurrent data structures",
            "Utilized SIMD instructions for vectorized processing",
            "Implemented memory pooling for reduced allocation overhead",
        ],
        DevelopmentType::GameDevelopment => [
            "Optimized spatial partitioning for collision detection performance",
            "Implemented entity component system for flexible game architecture",
            "Applied level of detail techniques for rendering optimization",
            "Utilized GPU instancing for rendering large object counts",
            "Implemented deterministic physics for consistent simulation",
        ],
        DevelopmentType::Security => [
            "Applied principle of least privilege across security boundaries",
            "Implemented defense-in-depth strategies for layered security",
            "Utilized cryptographic primitives for secure data exchange",
            "Applied security by design with threat modeling methodology",
            "Implemented zero-trust architecture for access control",
        ],
    };

    let advanced_terms = match dev_type {
        DevelopmentType::Backend => [
            "Implemented polyglot persistence with domain-specific data storage optimization",
            "Applied event-driven architecture with CQRS and event sourcing for eventual consistency",
            "Utilized domain-driven hexagonal architecture for maintainable business logic isolation",
            "Implemented reactive non-blocking I/O with backpressure handling for system resilience",
            "Applied saga pattern for distributed transaction management with compensating actions",
        ],
        DevelopmentType::Frontend => [
            "Implemented compile-time static analysis for type-safe component composition",
            "Applied atomic CSS methodology with tree-shakable style injection",
            "Utilized custom rendering reconciliation with incremental DOM diffing",
            "Implemented time-sliced rendering with priority-based task scheduling",
            "Applied declarative animation system with hardware acceleration optimization",
        ],
        DevelopmentType::Fullstack => [
            "Implemented protocol buffers for bandwidth-efficient binary communication",
            "Applied graphql federation with distributed schema composition",
            "Utilized optimistic UI updates with conflict resolution strategies",
            "Implemented real-time synchronization with operational transformation",
            "Applied CQRS with event sourcing for cross-boundary domain consistency",
        ],
        DevelopmentType::DataScience => [
            "Implemented ensemble stacking with meta-learner optimization",
            "Applied automated feature engineering with genetic programming",
            "Utilized distributed training with parameter server architecture",
            "Implemented gradient checkpointing for memory-efficient backpropagation",
            "Applied causal inference methods with propensity score matching",
        ],
        DevelopmentType::DevOps => [
            "Implemented policy-as-code with OPA for declarative security guardrails",
            "Applied progressive delivery with automated canary analysis",
            "Utilized custom control plane for multi-cluster orchestration",
            "Implemented observability with distributed tracing and context propagation",
            "Applied predictive scaling based on time-series forecasting",
        ],
        DevelopmentType::Blockchain => [
            "Implemented plasma chains with fraud proofs for scalable layer-2 solutions",
            "Applied zero-knowledge SNARKs for privacy-preserving transaction validation",
            "Utilized threshold signatures for distributed key management",
            "Implemented state channels with watch towers for secure off-chain transactions",
            "Applied formal verification for smart contract security guarantees",
        ],
        DevelopmentType::MachineLearning => [
            "Implemented neural architecture search with reinforcement learning",
            "Applied differentiable programming for end-to-end trainable pipelines",
            "Utilized federated learning with secure aggregation protocols",
            "Implemented attention mechanisms with sparse transformers",
            "Applied meta-learning for few-shot adaptation capabilities",
        ],
        DevelopmentType::SystemsProgramming => [
            "Implemented heterogeneous memory management with NUMA awareness",
            "Applied compile-time computation with constexpr metaprogramming",
            "Utilized lock-free concurrency with hazard pointers for memory reclamation",
            "Implemented vectorized processing with auto-vectorization hints",
            "Applied formal correctness proofs for critical system components",
        ],
        DevelopmentType::GameDevelopment => [
            "Implemented procedural generation with constraint-based wave function collapse",
            "Applied hierarchical task network for advanced AI planning",
            "Utilized data-oriented entity component system with SoA memory layout",
            "Implemented GPU-driven rendering pipeline with indirect drawing",
            "Applied reinforcement learning for emergent NPC behavior",
        ],
        DevelopmentType::Security => [
            "Implemented homomorphic encryption for secure multi-party computation",
            "Applied formal verification for cryptographic protocol security",
            "Utilized post-quantum cryptographic primitives for forward security",
            "Implemented secure multi-party computation with secret sharing",
            "Applied hardware-backed trusted execution environments for secure enclaves",
        ],
    };

    let extreme_terms = [
        "Implemented isomorphic polymorphic runtime with transpiled metaprogramming for cross-paradigm interoperability",
        "Utilized quantum-resistant cryptographic primitives with homomorphic computation capabilities",
        "Applied non-euclidean topology optimization for multi-dimensional data representation",
        "Implemented stochastic gradient Langevin dynamics with cyclical annealing for robust convergence",
        "Utilized differentiable neural computers with external memory addressing for complex reasoning tasks",
        "Applied topological data analysis with persistent homology for feature extraction",
        "Implemented zero-knowledge recursive composition for scalable verifiable computation",
        "Utilized category theory-based functional abstractions for composable system architecture",
        "Applied generalized abstract non-commutative algebra for cryptographic protocol design",
    ];

    match level {
        JargonLevel::Low => basic_terms.choose(&mut rng()).unwrap().to_string(),
        JargonLevel::Medium => basic_terms.choose(&mut rng()).unwrap().to_string(),
        JargonLevel::High => advanced_terms.choose(&mut rng()).unwrap().to_string(),
        JargonLevel::Extreme => {
            if rng().random_ratio(7, 10) {
                extreme_terms.choose(&mut rng()).unwrap().to_string()
            } else {
                advanced_terms.choose(&mut rng()).unwrap().to_string()
            }
        }
    }
}

pub fn generate_performance_jargon(dev_type: DevelopmentType, level: JargonLevel) -> String {
    let basic_terms = match dev_type {
        DevelopmentType::Backend => [
            "Optimized request handling with connection pooling",
            "Implemented caching layer for frequently accessed data",
            "Applied query optimization for improved database performance",
            "Utilized async I/O for non-blocking request processing",
            "Implemented rate limiting to prevent resource contention",
        ],
        DevelopmentType::Frontend => [
            "Optimized rendering pipeline with virtual DOM diffing",
            "Implemented code splitting for reduced initial load time",
            "Applied tree-shaking for reduced bundle size",
            "Utilized resource prioritization for critical path rendering",
            "Implemented request batching for reduced network overhead",
        ],
        _ => [
            "Optimized execution path for improved throughput",
            "Implemented data caching for repeated operations",
            "Applied resource pooling for reduced initialization overhead",
            "Utilized parallel processing for compute-intensive operations",
            "Implemented lazy evaluation for on-demand computation",
        ],
    };

    let advanced_terms = match dev_type {
        DevelopmentType::Backend => [
            "Implemented adaptive rate limiting with token bucket algorithm",
            "Applied distributed caching with write-through invalidation",
            "Utilized query denormalization for read-path optimization",
            "Implemented database sharding with consistent hashing",
            "Applied predictive data preloading based on access patterns",
        ],
        DevelopmentType::Frontend => [
            "Implemented speculative rendering for perceived performance improvement",
            "Applied RAIL performance model with user-centric metrics",
            "Utilized intersection observer for just-in-time resource loading",
            "Implemented partial hydration with selective client-side execution",
            "Applied computation caching with memoization strategies",
        ],
        _ => [
            "Implemented adaptive computation with context-aware optimization",
            "Applied memory access pattern optimization for cache efficiency",
            "Utilized workload partitioning with load balancing strategies",
            "Implemented algorithm selection based on input characteristics",
            "Applied predictive execution for latency hiding",
        ],
    };

    let extreme_terms = [
        "Implemented quantum-inspired optimization for NP-hard scheduling problems",
        "Applied multi-level heterogeneous caching with ML-driven eviction policies",
        "Utilized holographic data compression with lossy reconstruction tolerance",
        "Implemented custom memory hierarchy with algorithmic complexity-aware caching",
        "Applied tensor computation with specialized hardware acceleration paths",
    ];

    match level {
        JargonLevel::Low => basic_terms.choose(&mut rng()).unwrap().to_string(),
        JargonLevel::Medium => basic_terms.choose(&mut rng()).unwrap().to_string(),
        JargonLevel::High => advanced_terms.choose(&mut rng()).unwrap().to_string(),
        JargonLevel::Extreme => {
            if rng().random_ratio(7, 10) {
                extreme_terms.choose(&mut rng()).unwrap().to_string()
            } else {
                advanced_terms.choose(&mut rng()).unwrap().to_string()
            }
        }
    }
}

pub fn generate_data_jargon(dev_type: DevelopmentType, level: JargonLevel) -> String {
    let basic_terms = match dev_type {
        DevelopmentType::DataScience | DevelopmentType::MachineLearning => [
            "Applied feature normalization for improved model convergence",
            "Implemented data augmentation for enhanced training set diversity",
            "Utilized cross-validation for robust model evaluation",
            "Applied dimensionality reduction for feature space optimization",
            "Implemented ensemble methods for improved prediction accuracy",
        ],
        _ => [
            "Optimized data serialization for efficient transmission",
            "Implemented data compression for reduced storage requirements",
            "Applied data partitioning for improved query performance",
            "Utilized caching strategies for frequently accessed data",
            "Implemented data validation for improved consistency",
        ],
    };

    let advanced_terms = match dev_type {
        DevelopmentType::DataScience | DevelopmentType::MachineLearning => [
            "Implemented adversarial validation for dataset shift detection",
            "Applied bayesian hyperparameter optimization with gaussian processes",
            "Utilized gradient accumulation for large batch training",
            "Implemented feature interaction discovery with neural factorization machines",
            "Applied time-series forecasting with attention-based sequence models",
        ],
        _ => [
            "Implemented custom serialization with schema evolution support",
            "Applied data denormalization with materialized view maintenance",
            "Utilized bloom filters for membership testing optimization",
            "Implemented data sharding with consistent hashing algorithms",
            "Applied real-time stream processing with windowed aggregation",
        ],
    };

    let extreme_terms = [
        "Implemented manifold learning with locally linear embedding for nonlinear dimensionality reduction",
        "Applied topological data analysis with persistent homology for feature engineering",
        "Utilized quantum-resistant homomorphic encryption for privacy-preserving data processing",
        "Implemented causal inference with structural equation modeling and counterfactual analysis",
        "Applied differentiable programming for end-to-end trainable data transformation",
    ];

    match level {
        JargonLevel::Low => basic_terms.choose(&mut rng()).unwrap().to_string(),
        JargonLevel::Medium => basic_terms.choose(&mut rng()).unwrap().to_string(),
        JargonLevel::High => advanced_terms.choose(&mut rng()).unwrap().to_string(),
        JargonLevel::Extreme => {
            if rng().random_ratio(7, 10) {
                extreme_terms.choose(&mut rng()).unwrap().to_string()
            } else {
                advanced_terms.choose(&mut rng()).unwrap().to_string()
            }
        }
    }
}

pub fn generate_network_jargon(dev_type: DevelopmentType, level: JargonLevel) -> String {
    let basic_terms = [
        "Optimized request batching for reduced network overhead",
        "Implemented connection pooling for improved throughput",
        "Applied response compression for bandwidth optimization",
        "Utilized HTTP/2 multiplexing for parallel requests",
        "Implemented retry strategies with exponential backoff",
    ];

    let advanced_terms = match dev_type {
        DevelopmentType::Backend | DevelopmentType::DevOps => [
            "Implemented adaptive load balancing with consistent hashing",
            "Applied circuit breaking with health-aware routing",
            "Utilized connection multiplexing with protocol negotiation",
            "Implemented traffic shaping with token bucket rate limiting",
            "Applied distributed tracing with context propagation",
        ],
        _ => [
            "Implemented request prioritization with critical path analysis",
            "Applied proactive connection management with warm pooling",
            "Utilized content negotiation for optimized payload delivery",
            "Implemented response streaming with backpressure handling",
            "Applied predictive resource loading based on usage patterns",
        ],
    };

    let extreme_terms = [
        "Implemented quantum-resistant secure transport layer with post-quantum cryptography",
        "Applied autonomous traffic management with ML-driven routing optimization",
        "Utilized programmable data planes with in-network computation capabilities",
        "Implemented distributed consensus with Byzantine fault tolerance guarantees",
        "Applied formal verification for secure protocol implementation correctness",
    ];

    match level {
        JargonLevel::Low => basic_terms.choose(&mut rng()).unwrap().to_string(),
        JargonLevel::Medium => basic_terms.choose(&mut rng()).unwrap().to_string(),
        JargonLevel::High => advanced_terms.choose(&mut rng()).unwrap().to_string(),
        JargonLevel::Extreme => {
            if rng().random_ratio(7, 10) {
                extreme_terms.choose(&mut rng()).unwrap().to_string()
            } else {
                advanced_terms.choose(&mut rng()).unwrap().to_string()
            }
        }
    }
}

use crate::DevelopmentType;
use rand::{prelude::*, rng};

pub fn generate_endpoint(dev_type: DevelopmentType) -> String {
    let endpoints = match dev_type {
        DevelopmentType::Backend => [
            "/api/v1/users",
            "/api/v1/users/{id}",
            "/api/v1/products",
            "/api/v1/orders",
            "/api/v1/payments",
            "/api/v1/auth/login",
            "/api/v1/auth/refresh",
            "/api/v1/analytics/report",
            "/api/v1/notifications",
            "/api/v1/system/health",
            "/api/v2/recommendations",
            "/internal/metrics",
            "/internal/cache/flush",
            "/webhook/payment-provider",
            "/graphql",
        ],
        DevelopmentType::Frontend => [
            "/assets/main.js",
            "/assets/styles.css",
            "/api/v1/user-preferences",
            "/api/v1/cart",
            "/api/v1/products/featured",
            "/api/v1/auth/session",
            "/assets/fonts/roboto.woff2",
            "/api/v1/notifications/unread",
            "/assets/images/hero.webp",
            "/api/v1/search/autocomplete",
            "/socket.io/",
            "/api/v1/analytics/client-events",
            "/manifest.json",
            "/service-worker.js",
            "/api/v1/feature-flags",
        ],
        DevelopmentType::Fullstack => [
            "/api/v1/users/profile",
            "/api/v1/cart/checkout",
            "/api/v1/products/recommendations",
            "/api/v1/orders/history",
            "/api/v1/sync/client-state",
            "/api/v1/settings/preferences",
            "/api/v1/notifications/subscribe",
            "/api/v1/auth/validate",
            "/api/v1/content/dynamic",
            "/api/v1/analytics/events",
            "/graphql",
            "/socket.io/",
            "/api/v1/realtime/connect",
            "/api/v1/system/status",
            "/api/v1/feature-flags",
        ],
        DevelopmentType::DataScience => [
            "/api/v1/data/insights",
            "/api/v1/models/predict",
            "/api/v1/datasets/process",
            "/api/v1/analytics/report",
            "/api/v1/visualization/render",
            "/api/v1/features/importance",
            "/api/v1/experiments/results",
            "/api/v1/models/evaluate",
            "/api/v1/pipeline/execute",
            "/api/v1/data/validate",
            "/api/v1/data/transform",
            "/api/v1/models/train/status",
            "/api/v1/datasets/schema",
            "/api/v1/metrics/model-performance",
            "/api/v1/data/export",
        ],
        DevelopmentType::DevOps => [
            "/api/v1/infrastructure/status",
            "/api/v1/deployments/latest",
            "/api/v1/metrics/system",
            "/api/v1/alerts",
            "/api/v1/logs/query",
            "/api/v1/scaling/triggers",
            "/api/v1/config/validate",
            "/api/v1/backups/status",
            "/api/v1/security/scan-results",
            "/api/v1/environments/health",
            "/api/v1/pipeline/status",
            "/api/v1/services/dependencies",
            "/api/v1/resources/utilization",
            "/api/v1/network/topology",
            "/api/v1/incidents/active",
        ],
        DevelopmentType::Blockchain => [
            "/api/v1/transactions/submit",
            "/api/v1/blocks/latest",
            "/api/v1/wallet/balance",
            "/api/v1/smart-contracts/execute",
            "/api/v1/nodes/status",
            "/api/v1/network/peers",
            "/api/v1/consensus/status",
            "/api/v1/transactions/verify",
            "/api/v1/wallet/sign",
            "/api/v1/tokens/transfer",
            "/api/v1/chain/info",
            "/api/v1/mempool/status",
            "/api/v1/validators/performance",
            "/api/v1/oracle/data",
            "/api/v1/smart-contracts/audit",
        ],
        DevelopmentType::MachineLearning => [
            "/api/v1/models/infer",
            "/api/v1/models/train",
            "/api/v1/datasets/process",
            "/api/v1/features/extract",
            "/api/v1/models/evaluate",
            "/api/v1/hyperparameters/optimize",
            "/api/v1/experiments/results",
            "/api/v1/models/export",
            "/api/v1/models/versions",
            "/api/v1/predictions/batch",
            "/api/v1/embeddings/generate",
            "/api/v1/models/metrics",
            "/api/v1/training/status",
            "/api/v1/deployment/model",
            "/api/v1/features/importance",
        ],
        DevelopmentType::SystemsProgramming => [
            "/api/v1/memory/profile",
            "/api/v1/processes/stats",
            "/api/v1/threads/activity",
            "/api/v1/io/performance",
            "/api/v1/cpu/utilization",
            "/api/v1/network/statistics",
            "/api/v1/locks/contention",
            "/api/v1/allocations/trace",
            "/api/v1/system/interrupts",
            "/api/v1/devices/status",
            "/api/v1/filesystem/stats",
            "/api/v1/cache/performance",
            "/api/v1/kernel/parameters",
            "/api/v1/syscalls/frequency",
            "/api/v1/performance/profile",
        ],
        DevelopmentType::GameDevelopment => [
            "/api/v1/assets/download",
            "/api/v1/player/progress",
            "/api/v1/matchmaking/find",
            "/api/v1/leaderboard/global",
            "/api/v1/game/state/sync",
            "/api/v1/player/inventory",
            "/api/v1/player/achievements",
            "/api/v1/multiplayer/session",
            "/api/v1/analytics/gameplay",
            "/api/v1/content/updates",
            "/api/v1/physics/simulation",
            "/api/v1/rendering/performance",
            "/api/v1/player/settings",
            "/api/v1/server/regions",
            "/api/v1/telemetry/submit",
        ],
        DevelopmentType::Security => [
            "/api/v1/auth/token",
            "/api/v1/auth/validate",
            "/api/v1/users/permissions",
            "/api/v1/audit/logs",
            "/api/v1/security/scan",
            "/api/v1/vulnerabilities/report",
            "/api/v1/threats/intelligence",
            "/api/v1/compliance/check",
            "/api/v1/encryption/keys",
            "/api/v1/certificates/validate",
            "/api/v1/firewall/rules",
            "/api/v1/access/control",
            "/api/v1/identity/verify",
            "/api/v1/incidents/report",
            "/api/v1/monitoring/alerts",
        ],
    };

    endpoints.choose(&mut rng()).unwrap().to_string()
}

pub fn generate_method() -> String {
    let methods = ["GET", "POST", "PUT", "DELETE", "PATCH", "OPTIONS", "HEAD"];
    let weights = [15, 8, 5, 3, 2, 1, 1]; // Weighted distribution

    let dist = rand::distr::weighted::WeightedIndex::new(weights).unwrap();
    let mut rng = rng();

    methods[dist.sample(&mut rng)].to_string()
}

pub fn generate_status() -> u16 {
    let status_codes = [
        200, 201, 204, // 2xx Success
        301, 302, 304, // 3xx Redirection
        400, 401, 403, 404, 422, 429, // 4xx Client Error
        500, 502, 503, 504, // 5xx Server Error
    ];

    let weights = [
        60, 10, 5, // 2xx - most common
        3, 3, 5, // 3xx - less common
        5, 3, 2, 8, 3, 2, // 4xx - somewhat common
        2, 1, 1, 1, // 5xx - least common
    ];

    let dist = rand::distr::weighted::WeightedIndex::new(weights).unwrap();
    let mut rng = rng();

    status_codes[dist.sample(&mut rng)]
}

pub fn generate_request_details(dev_type: DevelopmentType) -> String {
    let details = match dev_type {
        DevelopmentType::Backend => [
            "Content-Type: application/json, User authenticated, Rate limit: 1000/hour",
            "Database queries: 3, Cache hit ratio: 85%, Auth: JWT",
            "Processed in service layer, Business rules applied: 5, Validation passed",
            "Using connection pool, Transaction isolation: READ_COMMITTED",
            "Response compression: gzip, Caching: public, max-age=3600",
            "API version: v1, Deprecation warning: Use v2 endpoint",
            "Rate limited client: example-corp, Remaining: 240/minute",
            "Downstream services: payment-service, notification-service",
            "Tenant: acme-corp, Shard: eu-central-1-b, Replica: 3",
            "Auth scopes: read:users,write:orders, Principal: system-service",
        ],
        DevelopmentType::Frontend => [
            "Asset loaded from CDN, Cache status: HIT, Compression: Brotli",
            "Component rendered: ProductCard, Props: 8, Re-renders: 0",
            "User session active, Feature flags: new-checkout,dark-mode",
            "Local storage usage: 120KB, IndexedDB tables: 3",
            "RTT: 78ms, Resource timing: tcpConnect=45ms, ttfb=120ms",
            "View transition animated, FPS: 58, Layout shifts: 0",
            "Form validation, Fields: 6, Errors: 2, Async validation",
            "State update batched, Components affected: 3, Virtual DOM diff: minimal",
            "Client capabilities: webp,webgl,bluetooth, Viewport: mobile",
            "A/B test: checkout-flow-v2, Variation: B, User cohort: returning-purchaser",
        ],
        DevelopmentType::Fullstack => [
            "End-to-end transaction, Client version: 3.5.2, Server version: 4.1.0",
            "Data synchronization, Client state: stale, Delta sync applied",
            "Authentication: OAuth2, Scopes: profile,orders,payment",
            "Request origin: iOS native app, API version: v2, Feature flags: 5",
            "Response transformation applied, Fields pruned: 12, Size reduction: 68%",
            "Validated against schema v3, Frontend compatible: true",
            "Backend services: user-service, inventory-service, pricing-service",
            "Client capabilities detected, Optimized response stream enabled",
            "Session context propagated, Tenant: example-corp, User tier: premium",
            "Real-time channel established, Protocol: WebSocket, Compression: enabled",
        ],
        DevelopmentType::DataScience => [
            "Dataset: user_behavior_v2, Records: 25K, Features: 18, Processing mode: batch",
            "Model: recommendation_engine_v3, Architecture: gradient_boosting, Accuracy: 92.5%",
            "Feature importance analyzed, Top features: last_purchase_date, category_affinity",
            "Transformation pipeline applied: normalize, encode_categorical, reduce_dimensions",
            "Prediction confidence: 87.3%, Alternative predictions generated: 3",
            "Processing node: data-science-pod-7, GPUs allocated: 2, Batch size: 256",
            "Cross-validation: 5-fold, Metrics: precision=0.88, recall=0.92, f1=0.90",
            "Time-series forecast, Horizon: 30 days, MAPE: 12.5%, Seasonality detected",
            "Anomaly detection, Threshold: 3.5σ, Anomalies found: 7, Confidence: high",
            "Experiment: price_elasticity_test, Group: control, Version: A, Sample size: 15K",
        ],
        DevelopmentType::DevOps => [
            "Deployment: canary, Version: v2.5.3, Rollout: 15%, Health: green",
            "Infrastructure: Kubernetes, Namespace: production, Pod count: 24/24 ready",
            "Autoscaling event, Trigger: CPU utilization 85%, New replicas: 5, Cooldown: 300s",
            "CI/CD pipeline: main-branch, Stage: integration-tests, Duration: 8m45s",
            "Resource allocation: CPU: 250m/500m, Memory: 1.2GB/2GB, Storage: 45GB/100GB",
            "Monitoring alert: Response latency p95 > 500ms, Duration: 15m, Severity: warning",
            "Log aggregation: 15K events/min, Retention: 30 days, Sampling rate: 100%",
            "Infrastructure as Code: Terraform v1.2.0, Modules: networking, compute, storage",
            "Service mesh: traffic shifted, Destination: v2=80%,v1=20%, Retry budget: 3x",
            "Security scan complete, Vulnerabilities: 0 critical, 2 high, 8 medium, CVEs: 5",
        ],
        DevelopmentType::Blockchain => [
            "Transaction hash: 0x3f5e..., Gas used: 45,000, Block: 14,322,556, Confirmations: 12",
            "Smart contract: Token (0x742A...), Method: transfer, Arguments: address,uint256",
            "Block producer: validator-12, Slot: 52341, Transactions: 126, Size: 1.2MB",
            "Consensus round: 567432, Validators participated: 95/100, Agreement: 98.5%",
            "Wallet balance: 1,250.75 tokens, Nonce: 42, Available: 1,245.75 (5 staked)",
            "Network status: Ethereum mainnet, Gas price: 25 gwei, TPS: 15.3, Finality: 15 blocks",
            "Token transfer: 125.5 USDC → 0x9eA2..., Network fee: 0.0025 ETH, Status: confirmed",
            "Mempool: 1,560 pending transactions, Priority fee range: 1-30 gwei",
            "Smart contract verification: source matches bytecode, Optimizer: enabled (200 runs)",
            "Blockchain analytics: daily active addresses: 125K, New wallets: 8.2K, Volume: $1.2B",
        ],
        DevelopmentType::MachineLearning => [
            "Model: resnet50_v2, Batch size: 64, Hardware: GPU T4, Memory usage: 8.5GB",
            "Training iteration: 12,500/50,000, Loss: 0.0045, Learning rate: 0.0001, ETA: 2h15m",
            "Inference request, Model: sentiment_analyzer_v3, Version: production, Latency: 45ms",
            "Dataset: customer_feedback_2023, Samples: 1.2M, Features: 25, Classes: 5",
            "Hyperparameter tuning, Trial: 28/100, Parameters: lr=0.001,dropout=0.3,layers=3",
            "Model deployment: recommendation_engine, Environment: production, A/B test: enabled",
            "Feature engineering pipeline, Steps: 8, Transformations: normalize,pca,encoding",
            "Model evaluation, Metrics: accuracy=0.925,precision=0.88,recall=0.91,f1=0.895",
            "Experiment tracking: run_id=78b3e, Framework: PyTorch 2.0, Checkpoints: 5",
            "Model serving, Requests: 250/s, p99 latency: 120ms, Cache hit ratio: 85%",
        ],
        DevelopmentType::SystemsProgramming => [
            "Memory profile: Heap: 245MB, Stack: 12MB, Allocations: 12K, Fragmentation: 8%",
            "Thread activity: Threads: 24, Blocked: 2, CPU-bound: 18, I/O-wait: 4",
            "I/O operations: Read: 12MB/s, Write: 4MB/s, IOPS: 250, Queue depth: 3",
            "Process stats: PID: 12458, CPU: 45%, Memory: 1.2GB, Open files: 128, Uptime: 5d12h",
            "Lock contention: Mutex M1: 15% contended, RwLock R1: reader-heavy (98/2)",
            "System calls: Rate: 15K/s, Top: read=25%,write=15%,futex=12%,poll=10%",
            "Cache statistics: L1 miss: 2.5%, L2 miss: 8.5%, L3 miss: 12%, TLB miss: 0.5%",
            "Network stack: TCP connections: 1,250, UDP sockets: 25, Listen backlog: 2/100",
            "Context switches: 25K/s, Voluntary: 85%, Involuntary: 15%, Latency: 12μs avg",
            "Interrupt handling: Rate: 15K/s, Top sources: network=45%,disk=25%,timer=15%",
        ],
        DevelopmentType::GameDevelopment => [
            "Rendering stats: FPS: 120, Draw calls: 450, Triangles: 2.5M, Textures: 120MB",
            "Physics simulation: Bodies: 1,250, Contacts: 850, Sub-steps: 3, Time: 3.5ms",
            "Animation system: Skeletons: 25, Blend operations: 85, Memory: 12MB",
            "Asset loading: Streaming: 15MB/s, Loaded textures: 85/120, Mesh LODs: 3/5",
            "Game state: Players: 45, NPCs: 120, Interactive objects: 350, Memory: 85MB",
            "Multiplayer: Clients: 48/64, Bandwidth: 1.2Mbit/s, Latency: 45ms, Packet loss: 0.5%",
            "Particle systems: Active: 25, Particles: 12K, Update time: 1.2ms",
            "AI processing: Pathfinding: 35 agents, Behavior trees: 120, CPU time: 4.5ms",
            "Audio engine: Channels: 24/32, Sounds: 45, 3D sources: 18, Memory: 24MB",
            "Player telemetry: Events: 120/min, Session: 45min, Area: desert_ruins_05",
        ],
        DevelopmentType::Security => [
            "Authentication: Method: OIDC, Provider: Azure AD, Session: 2h45m remaining",
            "Authorization check: Principal: user@example.com, Roles: admin,editor, Access: granted",
            "Security scan: Resources checked: 45, Vulnerabilities: 0 critical, 2 high, 8 medium",
            "Certificate: Subject: api.example.com, Issuer: Let's Encrypt, Expires: 60 days",
            "Encryption: Algorithm: AES-256-GCM, Key rotation: 25 days ago, KMS: AWS",
            "Audit log: User: admin@example.com, Action: user.create, Status: success, IP: 203.0.113.42",
            "Rate limiting: Client: mobile-app-v3, Limit: 100/min, Current: 45/min",
            "Threat intelligence: IP reputation: medium risk, Known signatures: 0, Geo: Netherlands",
            "WAF analysis: Rules triggered: 0, Inspected: headers,body,cookies, Mode: block",
            "Security token: JWT, Signature: RS256, Claims: 12, Scope: api:full",
        ],
    };

    details.choose(&mut rng()).unwrap().to_string()
}

use crate::types::{Complexity, DevelopmentType, JargonLevel};

pub struct SessionConfig {
    pub dev_type: DevelopmentType,
    pub jargon_level: JargonLevel,
    pub complexity: Complexity,
    pub alerts_enabled: bool,
    pub project_name: String,
    pub minimal_output: bool,
    pub team_activity: bool,
    pub framework: String,
}

use crate::DevelopmentType;
use rand::{prelude::*, rng};

pub fn generate_metric_unit(dev_type: DevelopmentType) -> String {
    let units = match dev_type {
        DevelopmentType::DataScience | DevelopmentType::MachineLearning => [
            "MB/s",
            "GB/s",
            "records/s",
            "samples/s",
            "iterations/s",
            "ms/batch",
            "s/epoch",
            "%",
            "MB",
            "GB",
        ],
        DevelopmentType::Backend | DevelopmentType::Fullstack => [
            "req/s",
            "ms",
            "μs",
            "MB/s",
            "connections",
            "sessions",
            "%",
            "threads",
            "MB",
            "ops/s",
        ],
        DevelopmentType::Frontend => [
            "ms", "fps", "KB", "MB", "elements", "nodes", "req/s", "s", "μs", "%",
        ],
        _ => [
            "ms", "s", "MB/s", "GB/s", "ops/s", "%", "MB", "KB", "count", "ratio",
        ],
    };

    units.choose(&mut rng()).unwrap().to_string()
}

pub fn generate_optimization_recommendation(dev_type: DevelopmentType) -> String {
    let recommendations = match dev_type {
        DevelopmentType::Backend => [
            "Consider implementing request batching for high-volume endpoints",
            "Database query optimization could improve response times by 15-20%",
            "Adding a distributed cache layer would reduce database load",
            "Implement connection pooling to reduce connection overhead",
            "Consider async processing for non-critical operations",
            "Implement circuit breakers for external service dependencies",
            "Database index optimization could improve query performance",
            "Consider implementing a read replica for heavy read workloads",
            "API response compression could reduce bandwidth consumption",
            "Implement rate limiting to protect against traffic spikes",
        ],
        DevelopmentType::Frontend => [
            "Implement code splitting to reduce initial bundle size",
            "Consider lazy loading for off-screen components",
            "Optimize critical rendering path for faster first paint",
            "Use memoization for expensive component calculations",
            "Implement virtualization for long scrollable lists",
            "Consider using web workers for CPU-intensive tasks",
            "Optimize asset loading with preload/prefetch strategies",
            "Implement request batching for multiple API calls",
            "Reduce JavaScript execution time with debouncing/throttling",
            "Optimize animation performance with CSS GPU acceleration",
        ],
        DevelopmentType::Fullstack => [
            "Implement more efficient data serialization between client and server",
            "Consider GraphQL for more efficient data fetching",
            "Optimize state management to reduce unnecessary renders",
            "Implement server-side rendering for improved initial load time",
            "Consider BFF pattern for optimized client-specific endpoints",
            "Reduce client-server round trips with data denormalization",
            "Implement WebSocket for real-time updates instead of polling",
            "Consider implementing a service worker for offline capabilities",
            "Optimize API contract for reduced payload sizes",
            "Implement shared validation logic between client and server",
        ],
        DevelopmentType::DataScience => [
            "Optimize feature engineering pipeline for parallel processing",
            "Consider incremental processing for large datasets",
            "Implement vectorized operations for numerical computations",
            "Consider dimensionality reduction to improve model efficiency",
            "Optimize data loading with memory-mapped files",
            "Implement distributed processing for large-scale computations",
            "Consider feature selection to reduce model complexity",
            "Optimize hyperparameter search strategy",
            "Implement early stopping criteria for training efficiency",
            "Consider model quantization for inference optimization",
        ],
        DevelopmentType::DevOps => [
            "Implement horizontal scaling for improved throughput",
            "Consider containerization for consistent deployment",
            "Optimize CI/CD pipeline for faster build times",
            "Implement infrastructure as code for reproducible environments",
            "Consider implementing a service mesh for observability",
            "Optimize resource allocation based on usage patterns",
            "Implement automated scaling policies based on demand",
            "Consider implementing blue-green deployments for zero downtime",
            "Optimize container image size for faster deployments",
            "Implement distributed tracing for performance bottleneck identification",
        ],
        DevelopmentType::Blockchain => [
            "Optimize smart contract gas usage with storage pattern refinement",
            "Consider implementing a layer 2 solution for improved throughput",
            "Optimize transaction validation with batched signature verification",
            "Implement more efficient consensus algorithm for reduced latency",
            "Consider sharding for improved scalability",
            "Optimize state storage with pruning strategies",
            "Implement efficient merkle tree computation",
            "Consider optimistic execution for improved transaction throughput",
            "Optimize P2P network propagation with better peer selection",
            "Implement efficient cryptographic primitives for reduced overhead",
        ],
        DevelopmentType::MachineLearning => [
            "Implement model quantization for faster inference",
            "Consider knowledge distillation for smaller model footprint",
            "Optimize batch size for improved training throughput",
            "Implement mixed-precision training for better GPU utilization",
            "Consider implementing gradient accumulation for larger effective batch sizes",
            "Optimize data loading pipeline with prefetching",
            "Implement model pruning for reduced parameter count",
            "Consider feature selection for improved model efficiency",
            "Optimize distributed training communication patterns",
            "Implement efficient checkpoint strategies for reduced storage requirements",
        ],
        DevelopmentType::SystemsProgramming => [
            "Optimize memory access patterns for improved cache utilization",
            "Consider implementing custom memory allocators for specific workloads",
            "Implement lock-free data structures for concurrent access",
            "Optimize instruction pipelining with code layout restructuring",
            "Consider SIMD instructions for vectorized processing",
            "Implement efficient thread pooling for reduced creation overhead",
            "Optimize I/O operations with asynchronous processing",
            "Consider memory-mapped I/O for large file operations",
            "Implement efficient serialization for data interchange",
            "Consider zero-copy strategies for data processing pipelines",
        ],
        DevelopmentType::GameDevelopment => [
            "Implement object pooling for frequently created entities",
            "Consider frustum culling optimization for rendering performance",
            "Optimize draw call batching for reduced GPU overhead",
            "Implement level of detail (LOD) for distant objects",
            "Consider async loading for game assets",
            "Optimize physics simulation with spatial partitioning",
            "Implement efficient animation blending techniques",
            "Consider GPU instancing for similar objects",
            "Optimize shader complexity for better performance",
            "Implement efficient collision detection with broad-phase algorithms",
        ],
        DevelopmentType::Security => [
            "Implement cryptographic acceleration for improved performance",
            "Consider session caching for reduced authentication overhead",
            "Optimize security scanning with incremental analysis",
            "Implement efficient key management for reduced overhead",
            "Consider least-privilege optimization for security checks",
            "Optimize certificate validation with efficient revocation checking",
            "Implement efficient secure channel negotiation",
            "Consider security policy caching for improved evaluation performance",
            "Optimize encryption algorithm selection based on data sensitivity",
            "Implement efficient log analysis with streaming processing",
        ],
    };

    recommendations.choose(&mut rng()).unwrap().to_string()
}

pub fn generate_performance_metric(dev_type: DevelopmentType) -> String {
    let metrics = match dev_type {
        DevelopmentType::Backend => [
            "API Response Time",
            "Database Query Latency",
            "Request Throughput",
            "Cache Hit Ratio",
            "Connection Pool Utilization",
            "Thread Pool Saturation",
            "Queue Depth",
            "Active Sessions",
            "Error Rate",
            "GC Pause Time",
        ],
        DevelopmentType::Frontend => [
            "Render Time",
            "First Contentful Paint",
            "Time to Interactive",
            "Bundle Size",
            "DOM Node Count",
            "Frame Rate",
            "Memory Usage",
            "Network Request Count",
            "Asset Load Time",
            "Input Latency",
        ],
        DevelopmentType::Fullstack => [
            "End-to-End Response Time",
            "API Integration Latency",
            "Data Serialization Time",
            "Client-Server Round Trip",
            "Authentication Time",
            "State Synchronization Time",
            "Cache Coherency Ratio",
            "Concurrent User Sessions",
            "Bandwidth Utilization",
            "Resource Contention Index",
        ],
        DevelopmentType::DataScience => [
            "Data Processing Time",
            "Model Training Iteration",
            "Feature Extraction Time",
            "Data Transformation Throughput",
            "Prediction Latency",
            "Dataset Load Time",
            "Memory Utilization",
            "Parallel Worker Efficiency",
            "I/O Throughput",
            "Query Execution Time",
        ],
        DevelopmentType::DevOps => [
            "Deployment Time",
            "Build Duration",
            "Resource Provisioning Time",
            "Autoscaling Response Time",
            "Container Startup Time",
            "Service Discovery Latency",
            "Configuration Update Time",
            "Health Check Response Time",
            "Log Processing Rate",
            "Alert Processing Time",
        ],
        DevelopmentType::Blockchain => [
            "Transaction Validation Time",
            "Block Creation Time",
            "Consensus Round Duration",
            "Smart Contract Execution Time",
            "Network Propagation Delay",
            "Cryptographic Verification Time",
            "Merkle Tree Computation",
            "State Transition Latency",
            "Chain Sync Rate",
            "Gas Utilization Efficiency",
        ],
        DevelopmentType::MachineLearning => [
            "Model Inference Time",
            "Training Epoch Duration",
            "Feature Engineering Throughput",
            "Gradient Computation Time",
            "Batch Processing Rate",
            "Model Serialization Time",
            "Memory Utilization",
            "GPU Utilization",
            "Data Loading Throughput",
            "Hyperparameter Evaluation Time",
        ],
        DevelopmentType::SystemsProgramming => [
            "Memory Allocation Time",
            "Context Switch Overhead",
            "Lock Contention Ratio",
            "Cache Miss Rate",
            "Syscall Latency",
            "I/O Operation Throughput",
            "Thread Synchronization Time",
            "Memory Bandwidth Utilization",
            "Instruction Throughput",
            "Branch Prediction Accuracy",
        ],
        DevelopmentType::GameDevelopment => [
            "Frame Render Time",
            "Physics Simulation Time",
            "Asset Loading Duration",
            "Particle System Update Time",
            "Animation Blending Time",
            "AI Pathfinding Computation",
            "Collision Detection Time",
            "Memory Fragmentation Ratio",
            "Draw Call Count",
            "Audio Processing Latency",
        ],
        DevelopmentType::Security => [
            "Encryption/Decryption Time",
            "Authentication Latency",
            "Signature Verification Time",
            "Security Scan Duration",
            "Threat Detection Latency",
            "Policy Evaluation Time",
            "Access Control Check Latency",
            "Certificate Validation Time",
            "Secure Channel Establishment",
            "Log Analysis Throughput",
        ],
    };

    metrics.choose(&mut rng()).unwrap().to_string()
}

use crate::DevelopmentType;
use rand::{prelude::*, rng};

pub fn generate_data_operation(dev_type: DevelopmentType) -> String {
    let operations = match dev_type {
        DevelopmentType::Backend => [
            "Processing batch transactions",
            "Syncing database replicas",
            "Aggregating analytics data",
            "Generating user activity reports",
            "Optimizing database indexes",
            "Compressing log archives",
            "Validating data integrity",
            "Processing webhook events",
            "Migrating legacy data",
            "Generating API documentation",
        ],
        DevelopmentType::Frontend => [
            "Processing user interaction events",
            "Optimizing rendering performance data",
            "Analyzing component render times",
            "Compressing asset bundles",
            "Processing form submission data",
            "Validating client-side data",
            "Generating localization files",
            "Analyzing user session flows",
            "Optimizing client-side caching",
            "Processing offline data sync",
        ],
        DevelopmentType::Fullstack => [
            "Synchronizing client-server data",
            "Processing distributed transactions",
            "Validating cross-system integrity",
            "Generating system topology maps",
            "Optimizing data transfer formats",
            "Analyzing API usage patterns",
            "Processing multi-tier cache data",
            "Generating integration test data",
            "Optimizing client-server protocols",
            "Validating end-to-end workflows",
        ],
        DevelopmentType::DataScience => [
            "Processing raw dataset",
            "Performing feature engineering",
            "Generating training batches",
            "Validating statistical significance",
            "Normalizing input features",
            "Generating cross-validation folds",
            "Analyzing feature importance",
            "Optimizing dimensionality reduction",
            "Processing time-series forecasts",
            "Generating data visualization assets",
        ],
        DevelopmentType::DevOps => [
            "Analyzing system log patterns",
            "Processing deployment metrics",
            "Generating infrastructure reports",
            "Validating security compliance",
            "Optimizing resource allocation",
            "Processing alert aggregation",
            "Analyzing performance bottlenecks",
            "Generating capacity planning models",
            "Validating configuration consistency",
            "Processing automated scaling events",
        ],
        DevelopmentType::Blockchain => [
            "Validating transaction blocks",
            "Processing consensus votes",
            "Generating merkle proofs",
            "Validating smart contract executions",
            "Analyzing gas optimization metrics",
            "Processing state transition deltas",
            "Generating network health reports",
            "Validating cross-chain transactions",
            "Optimizing storage proof generation",
            "Processing validator stake distribution",
        ],
        DevelopmentType::MachineLearning => [
            "Processing training batch",
            "Generating model embeddings",
            "Validating prediction accuracy",
            "Optimizing hyperparameters",
            "Processing inference requests",
            "Analyzing model sensitivity",
            "Generating feature importance maps",
            "Validating model robustness",
            "Optimizing model quantization",
            "Processing distributed training gradients",
        ],
        DevelopmentType::SystemsProgramming => [
            "Analyzing memory access patterns",
            "Processing thread scheduling metrics",
            "Generating heap fragmentation reports",
            "Validating lock contention patterns",
            "Optimizing cache utilization",
            "Processing syscall frequency analysis",
            "Analyzing I/O bottlenecks",
            "Generating performance flamegraphs",
            "Validating memory safety guarantees",
            "Processing interrupt handling metrics",
        ],
        DevelopmentType::GameDevelopment => [
            "Processing physics simulation batch",
            "Generating level of detail models",
            "Validating collision detection",
            "Optimizing rendering pipelines",
            "Processing animation blend trees",
            "Analyzing gameplay telemetry",
            "Generating procedural content",
            "Validating player progression data",
            "Optimizing asset streaming",
            "Processing particle system batches",
        ],
        DevelopmentType::Security => [
            "Analyzing threat intelligence data",
            "Processing security event logs",
            "Generating vulnerability reports",
            "Validating authentication patterns",
            "Optimizing encryption performance",
            "Processing network traffic analysis",
            "Analyzing anomaly detection signals",
            "Generating security compliance documentation",
            "Validating access control policies",
            "Processing certificate validation chains",
        ],
    };

    operations.choose(&mut rng()).unwrap().to_string()
}

pub fn generate_data_sub_operation(dev_type: DevelopmentType) -> String {
    let sub_operations = match dev_type {
        DevelopmentType::Backend | DevelopmentType::Fullstack => [
            "Applying data normalization rules",
            "Validating referential integrity",
            "Optimizing query execution plan",
            "Applying business rule validations",
            "Processing data transformation mappings",
            "Applying schema validation rules",
            "Executing incremental data updates",
            "Processing conditional logic branches",
            "Applying security filtering rules",
            "Executing transaction compensation logic",
        ],
        DevelopmentType::Frontend => [
            "Applying data binding transformations",
            "Validating input constraints",
            "Optimizing render tree calculations",
            "Processing event propagation",
            "Applying localization transforms",
            "Validating UI state consistency",
            "Processing animation frame calculations",
            "Applying accessibility transformations",
            "Executing conditional rendering logic",
            "Processing style calculation optimizations",
        ],
        DevelopmentType::DataScience | DevelopmentType::MachineLearning => [
            "Applying feature scaling transformations",
            "Validating statistical distributions",
            "Processing categorical encoding",
            "Executing outlier detection",
            "Applying missing value imputation",
            "Validating correlation significance",
            "Processing dimensionality reduction",
            "Applying cross-validation splits",
            "Executing feature selection algorithms",
            "Processing data augmentation transforms",
        ],
        _ => [
            "Applying transformation rules",
            "Validating integrity constraints",
            "Processing conditional logic",
            "Executing optimization algorithms",
            "Applying filtering criteria",
            "Validating consistency rules",
            "Processing batch operations",
            "Applying normalization steps",
            "Executing validation checks",
            "Processing incremental updates",
        ],
    };

    sub_operations.choose(&mut rng()).unwrap().to_string()
}

pub fn generate_data_details(dev_type: DevelopmentType) -> String {
    let details = match dev_type {
        DevelopmentType::Backend => [
            "Reduced database query time by 35% through index optimization",
            "Improved data integrity by implementing transaction boundaries",
            "Reduced API response size by 42% through selective field inclusion",
            "Optimized cache hit ratio increased to 87%",
            "Implemented sharded processing for 4.5x throughput improvement",
            "Reduced duplicate processing by implementing idempotency keys",
            "Applied compression resulting in 68% storage reduction",
            "Improved validation speed by 29% through optimized rule execution",
            "Reduced error rate from 2.3% to 0.5% with improved validation",
            "Implemented batch processing for 3.2x throughput improvement",
        ],
        DevelopmentType::Frontend => [
            "Reduced bundle size by 28% through tree-shaking optimization",
            "Improved render performance by 45% with memo optimization",
            "Reduced time-to-interactive by 1.2 seconds",
            "Implemented virtualized rendering for 5x scrolling performance",
            "Reduced network payload by 37% through selective data loading",
            "Improved animation smoothness with requestAnimationFrame optimization",
            "Reduced layout thrashing by 82% with optimized DOM operations",
            "Implemented progressive loading for 2.3s perceived performance improvement",
            "Improved form submission speed by 40% with optimized validation",
            "Reduced memory usage by 35% with proper cleanup of event listeners",
        ],
        DevelopmentType::DataScience | DevelopmentType::MachineLearning => [
            "Improved model accuracy by 3.7% through feature engineering",
            "Reduced training time by 45% with optimized batch processing",
            "Improved inference latency by 28% through model optimization",
            "Reduced dimensionality from 120 to 18 features while maintaining 98.5% variance",
            "Improved data throughput by 3.2x with parallel processing",
            "Reduced memory usage by 67% with sparse matrix representation",
            "Improved cross-validation speed by 2.8x with optimized splitting",
            "Reduced prediction variance by 18% with ensemble techniques",
            "Improved outlier detection precision from 82% to 96.5%",
            "Reduced training data requirements by 48% with data augmentation",
        ],
        DevelopmentType::DevOps => [
            "Reduced deployment time by 68% through pipeline optimization",
            "Improved resource utilization by 34% with optimized allocation",
            "Reduced error rate by 76% with improved validation checks",
            "Implemented auto-scaling resulting in 28% cost reduction",
            "Improved monitoring coverage to 98.5% of critical systems",
            "Reduced incident response time by 40% through automated alerting",
            "Improved configuration consistency to 99.8% across environments",
            "Reduced security vulnerabilities by 85% through automated scanning",
            "Improved backup reliability to 99.99% with verification",
            "Reduced network latency by 25% with optimized routing",
        ],
        DevelopmentType::Blockchain => [
            "Reduced transaction validation time by 35% with optimized algorithms",
            "Improved smart contract execution efficiency by 28% through gas optimization",
            "Reduced storage requirements by 47% with optimized data structures",
            "Implemented sharding for 4.2x throughput improvement",
            "Improved consensus time by 38% with optimized protocols",
            "Reduced network propagation delay by 42% with optimized peer selection",
            "Improved cryptographic verification speed by 30% with batch processing",
            "Reduced fork rate by 75% with improved synchronization",
            "Implemented state pruning for 68% storage reduction",
            "Improved validator participation rate to 97.8% with incentive optimization",
        ],
        _ => [
            "Reduced processing time by 40% through algorithm optimization",
            "Improved throughput by 3.5x with parallel processing",
            "Reduced error rate from 2.1% to 0.3% with improved validation",
            "Implemented batching for 2.8x performance improvement",
            "Reduced memory usage by 45% with optimized data structures",
            "Improved cache hit ratio to 92% with predictive loading",
            "Reduced latency by 65% with optimized processing paths",
            "Implemented incremental processing for 4.2x throughput on large datasets",
            "Improved consistency to 99.7% with enhanced validation",
            "Reduced resource contention by 80% with improved scheduling",
        ],
    };

    details.choose(&mut rng()).unwrap().to_string()
}

use clap::ValueEnum;

#[derive(Copy, Clone, PartialEq, Eq, PartialOrd, Ord, ValueEnum, Debug)]
pub enum DevelopmentType {
    Backend,
    Frontend,
    Fullstack,
    DataScience,
    DevOps,
    Blockchain,
    MachineLearning,
    SystemsProgramming,
    GameDevelopment,
    Security,
}

#[derive(Copy, Clone, PartialEq, Eq, PartialOrd, Ord, ValueEnum, Debug)]
pub enum JargonLevel {
    Low,
    Medium,
    High,
    Extreme,
}

#[derive(Copy, Clone, PartialEq, Eq, PartialOrd, Ord, ValueEnum, Debug)]
pub enum Complexity {
    Low,
    Medium,
    High,
    Extreme,
}

use rand::{prelude::*, rng};

pub fn generate_system_event() -> String {
    let events = [
        "New process started: backend-api-server (PID: 12358)",
        "Process terminated: worker-thread-pool-7 (PID: 8712)",
        "Memory threshold alert cleared (Usage: 68%)",
        "Connection established to database replica-3",
        "Network interface eth0: Link state changed to UP",
        "Garbage collection completed (Duration: 12ms, Freed: 124MB)",
        "CPU thermal throttling activated (Core temp: 82°C)",
        "Filesystem /data remounted read-write",
        "Docker container backend-api-1 restarted (Exit code: 137)",
        "HTTPS certificate for api.example.com renewed successfully",
        "Scheduled backup started (Target: primary-database)",
        "Swap space usage increased by 215MB (Current: 1.2GB)",
        "New USB device detected: Logitech Webcam C920",
        "System time synchronized with NTP server",
        "SELinux policy reloaded (Contexts: 1250)",
        "Firewall rule added: Allow TCP port 8080 from 10.0.0.0/24",
        "Package update available: security-updates (Priority: High)",
        "GPU driver loaded successfully (CUDA 12.1)",
        "Systemd service backend-api.service entered running state",
        "Cron job system-maintenance completed (Status: Success)",
        "SMART warning on /dev/sda (Reallocated sectors: 5)",
        "User authorization pattern changed (Last modified: 2 minutes ago)",
        "VM snapshot created (Size: 4.5GB, Name: pre-deployment)",
        "Load balancer added new backend server (Total: 5 active)",
        "Kubernetes pod scheduled on node worker-03",
        "Memory cgroup limit reached for container backend-api-2",
        "Audit log rotation completed (Archived: 250MB)",
        "Power source changed to battery (Remaining: 95%)",
        "System upgrade scheduled for next maintenance window",
        "Network traffic spike detected (Interface: eth0, 850Mbps)",
    ];

    events.choose(&mut rng()).unwrap().to_string()
}

pub fn generate_system_recommendation() -> String {
    let recommendations = [
        "Consider increasing memory allocation based on current usage patterns",
        "CPU utilization consistently high - evaluate scaling compute resources",
        "Network I/O bottleneck detected - consider optimizing data transfer patterns",
        "Disk I/O latency above threshold - evaluate storage performance options",
        "Process restart frequency increased - investigate potential memory leaks",
        "Connection pool utilization high - consider increasing maximum connections",
        "Thread contention detected - review synchronization strategies",
        "Database query cache hit ratio low - analyze query patterns",
        "Garbage collection pause times increasing - review memory management",
        "System load variability high - consider auto-scaling implementation",
        "Log volume increased by 45% - review logging verbosity",
        "SSL/TLS handshake failures detected - verify certificate configuration",
        "API endpoint response time degradation - review recent code changes",
        "Cache eviction rate high - consider increasing cache capacity",
        "Disk space trending toward threshold - implement cleanup procedures",
        "Background task queue growing - evaluate worker pool size",
        "Network packet retransmission rate above baseline - investigate network health",
        "Authentication failures increased - review security policies",
        "Container restart frequency above threshold - analyze container health checks",
        "Database connection establishment latency increasing - review connection handling",
        "Memory fragmentation detected - consider periodic service restarts",
        "File descriptor usage approaching limit - review resource management",
        "Thread pool saturation detected - evaluate concurrency settings",
        "Kernel parameter tuning recommended for workload profile",
        "Consider upgrading system packages for performance improvements",
        "Database index fragmentation detected - schedule maintenance window",
        "Background CPU usage high - investigate system processes",
        "TCP connection establishment rate above baseline - review connection pooling",
        "Memory swapping detected - increase physical memory or reduce consumption",
        "Consider implementing distributed tracing for performance analysis",
    ];

    recommendations.choose(&mut rng()).unwrap().to_string()
}

pub mod code_analyzer;
pub mod data_processing;
pub mod jargon;
pub mod metrics;
pub mod network_activity;
pub mod system_monitoring;

This code segment functions to: Orchestrate program execution flow by initializing configuration parameters, managing runtime duration controls, dynamically selecting and sequencing operational tasks based on complexity settings, and coordinating concurrent output generation with user interruption handling.

```rust
[TASK_BEGIN]
fn main() {
    let args = Args::parse();
    let term = Term::stdout();
    let _ = term.clear();

    let config = config::load_config(&args);
    let mut rng = rand::thread_rng();
    let alert_rng = rand::thread_rng();

    let running = Arc::new(AtomicBool::new(true));
    let r = running.clone();

    ctrlc::set_handler(move || {
        r.store(false, Ordering::SeqCst);
    }).unwrap();

    let start_time = Instant::now();
    let duration = if args.duration > 0 {
        Some(Duration::from_secs(args.duration))
    } else {
        None
    };

    while running.load(Ordering::SeqCst) {
        display::show_activity(&args, &config, &mut rng, &term);

        if args.alerts {
            display::show_alert(&args, &alert_rng, &term);
        }

        if args.team {
            display::show_collaboration(&args, &mut rng, &term);
        }

        if let Some(d) = duration {
            if start_time.elapsed() >= d {
                break;
            }
        }

        thread::sleep(Duration::from_millis(
            config.update_interval_ms as u64
        ));
    }

    let _ = term.show_cursor();
    println!("\n{}", "Simulation complete. All systems nominal.".green().bold());
}
[TASK_END]
```