sklears_core/

compile_time_macros.rs

//! # Compile-Time Model Verification and Macro System
//!
//! This module provides advanced procedural macros for compile-time verification of ML models,
//! automatic benchmark generation, and mathematical correctness validation.
//!
//! The system includes:
//! - Model configuration verification
//! - Tensor dimension checking
//! - Performance constraint validation
//! - Automatic benchmark generation
//! - Mathematical property verification
//! - Type-level computation validation

use crate::error::Result;
use proc_macro2::{Span, TokenStream};
use quote::quote;
use serde::{Deserialize, Serialize};
use std::collections::HashMap;
use std::fmt;
use syn::{parse::Parse, parse::ParseStream, ItemFn, Type};

// ============================================================================
// Core Verification Framework
// ============================================================================

/// Configuration for compile-time verification
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct VerificationConfig {
    pub enable_dimension_checking: bool,
    pub enable_performance_validation: bool,
    pub enable_mathematical_verification: bool,
    pub enable_memory_safety_checks: bool,
    pub generate_benchmarks: bool,
    pub max_compilation_time_ms: u64,
    pub performance_targets: PerformanceTargets,
}

/// Performance targets for validation
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct PerformanceTargets {
    pub max_latency_ms: f64,
    pub min_throughput_ops_per_sec: f64,
    pub max_memory_usage_mb: f64,
    pub max_compilation_time_ms: u64,
}

/// Verification result from compile-time checks
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct VerificationResult {
    pub is_valid: bool,
    pub errors: Vec<VerificationError>,
    pub warnings: Vec<VerificationWarning>,
    pub optimizations: Vec<OptimizationSuggestion>,
    pub generated_code: Option<String>,
}

/// Compile-time verification error
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct VerificationError {
    pub error_type: VerificationErrorType,
    pub message: String,
    pub location: SourceLocation,
    pub suggestions: Vec<String>,
}

/// Types of verification errors
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub enum VerificationErrorType {
    DimensionMismatch,
    TypeMismatch,
    PerformanceViolation,
    MathematicalIncorrectness,
    MemorySafetyViolation,
    ConfigurationError,
    ResourceExhaustion,
}

/// Compile-time verification warning
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct VerificationWarning {
    pub warning_type: VerificationWarningType,
    pub message: String,
    pub location: SourceLocation,
    pub impact: ImpactLevel,
}

/// Types of verification warnings
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub enum VerificationWarningType {
    PerformanceSuboptimal,
    PotentialPrecisionLoss,
    MemoryInefficiency,
    ConfigurationRecommendation,
    CompatibilityIssue,
}

/// Impact level of warnings
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub enum ImpactLevel {
    Low,
    Medium,
    High,
    Critical,
}

impl fmt::Display for ImpactLevel {
    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
        match self {
            ImpactLevel::Low => write!(f, "Low"),
            ImpactLevel::Medium => write!(f, "Medium"),
            ImpactLevel::High => write!(f, "High"),
            ImpactLevel::Critical => write!(f, "Critical"),
        }
    }
}

/// Optimization suggestions
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct OptimizationSuggestion {
    pub optimization_type: OptimizationType,
    pub description: String,
    pub expected_improvement: ImprovementMetrics,
    pub implementation_complexity: ComplexityLevel,
}

/// Types of optimizations
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub enum OptimizationType {
    Vectorization,
    MemoryLayout,
    AlgorithmChoice,
    Parallelization,
    CacheOptimization,
    CompilerHints,
}

/// Expected improvement metrics
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ImprovementMetrics {
    pub performance_gain_percent: f64,
    pub memory_reduction_percent: f64,
    pub compilation_time_change_percent: f64,
}

/// Implementation complexity levels
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub enum ComplexityLevel {
    Trivial,
    Low,
    Medium,
    High,
    Expert,
}

/// Source code location for errors/warnings
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct SourceLocation {
    pub file: String,
    pub line: u32,
    pub column: u32,
    pub span_start: u32,
    pub span_end: u32,
}

// ============================================================================
// Model Verification Traits
// ============================================================================

/// Trait for types that can be verified at compile time
pub trait CompileTimeVerifiable {
    /// Verify the type at compile time
    fn verify() -> VerificationResult;

    /// Get verification configuration
    fn verification_config() -> VerificationConfig;

    /// Generate optimized code if possible
    fn generate_optimized_code() -> Option<TokenStream>;
}

/// Trait for dimension verification
pub trait DimensionVerifiable {
    /// Verify tensor dimensions are compatible
    fn verify_dimensions(input_dims: &[usize], output_dims: &[usize]) -> Result<()>;

    /// Check if dimensions support the operation
    fn supports_operation(op: &str, dims: &[usize]) -> bool;

    /// Get required dimension constraints
    fn dimension_constraints() -> Vec<DimensionConstraint>;
}

/// Dimension constraint specification
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct DimensionConstraint {
    pub constraint_type: ConstraintType,
    pub dimensions: Vec<usize>,
    pub relationship: DimensionRelationship,
    pub error_message: String,
}

/// Types of dimension constraints
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub enum ConstraintType {
    Exact,
    Minimum,
    Maximum,
    Multiple,
    Relationship,
}

/// Relationships between dimensions
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub enum DimensionRelationship {
    Equal,
    GreaterThan,
    LessThan,
    Divisible,
    PowerOfTwo,
    Custom(String),
}

// ============================================================================
// Mathematical Verification System
// ============================================================================

/// Mathematical property verification
pub trait MathematicallyVerifiable {
    /// Verify mathematical properties hold
    fn verify_mathematical_properties() -> Result<MathematicalVerification>;

    /// Check numerical stability
    fn verify_numerical_stability() -> Result<StabilityAnalysis>;

    /// Validate algorithmic correctness
    fn verify_algorithm_correctness() -> Result<CorrectnessProof>;
}

/// Mathematical verification result
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct MathematicalVerification {
    pub properties_verified: Vec<MathematicalProperty>,
    pub stability_guaranteed: bool,
    pub convergence_proven: bool,
    pub error_bounds: Option<ErrorBounds>,
}

/// Mathematical properties that can be verified
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct MathematicalProperty {
    pub property_type: PropertyType,
    pub description: String,
    pub verification_method: VerificationMethod,
    pub confidence_level: f64,
}

/// Types of mathematical properties
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub enum PropertyType {
    Convexity,
    Monotonicity,
    Continuity,
    Differentiability,
    Boundedness,
    Symmetry,
    Invariance,
    Conservation,
}

/// Methods for verification
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub enum VerificationMethod {
    SymbolicProof,
    NumericalAnalysis,
    StatisticalTest,
    FormalVerification,
    PropertyTesting,
}

/// Numerical stability analysis
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct StabilityAnalysis {
    pub condition_number: f64,
    pub error_propagation: ErrorPropagation,
    pub precision_requirements: PrecisionRequirements,
    pub stability_recommendations: Vec<String>,
}

/// Error propagation analysis
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ErrorPropagation {
    pub input_sensitivity: f64,
    pub accumulated_error: f64,
    pub worst_case_amplification: f64,
}

/// Precision requirements
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct PrecisionRequirements {
    pub minimum_precision_bits: u8,
    pub recommended_precision: PrecisionType,
    pub precision_critical_operations: Vec<String>,
}

/// Precision types
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub enum PrecisionType {
    Float16,
    Float32,
    Float64,
    Float128,
    Arbitrary,
}

/// Algorithm correctness proof
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct CorrectnessProof {
    pub proof_method: ProofMethod,
    pub invariants_maintained: Vec<String>,
    pub preconditions: Vec<String>,
    pub postconditions: Vec<String>,
    pub termination_guaranteed: bool,
}

/// Methods for proving correctness
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub enum ProofMethod {
    Induction,
    LoopInvariant,
    HoareLogic,
    ModelChecking,
    TheoremProving,
    SymbolicExecution,
}

/// Error bounds for numerical computations
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ErrorBounds {
    pub absolute_error: f64,
    pub relative_error: f64,
    pub confidence_interval: (f64, f64),
    pub error_distribution: ErrorDistribution,
}

/// Error distribution types
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub enum ErrorDistribution {
    Uniform,
    Normal,
    Exponential,
    PowerLaw,
    Custom(String),
}

// ============================================================================
// Benchmark Generation System
// ============================================================================

/// Automatic benchmark generation configuration
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct BenchmarkConfig {
    pub enable_microbenchmarks: bool,
    pub enable_integration_benchmarks: bool,
    pub enable_regression_tests: bool,
    pub benchmark_dimensions: Vec<BenchmarkDimension>,
    pub performance_targets: PerformanceTargets,
    pub comparison_baselines: Vec<BaselineConfig>,
}

/// Benchmark dimension configuration
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct BenchmarkDimension {
    pub parameter_name: String,
    pub values: BenchmarkValues,
    pub scaling_behavior: ScalingBehavior,
}

/// Benchmark values specification
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum BenchmarkValues {
    Range {
        start: f64,
        end: f64,
        steps: usize,
    },
    List(Vec<f64>),
    Geometric {
        start: f64,
        ratio: f64,
        steps: usize,
    },
    Powers {
        base: f64,
        exponents: Vec<i32>,
    },
}

/// Expected scaling behavior
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub enum ScalingBehavior {
    Constant,     // O(1)
    Logarithmic,  // O(log n)
    Linear,       // O(n)
    Linearithmic, // O(n log n)
    Quadratic,    // O(n²)
    Cubic,        // O(n³)
    Exponential,  // O(2^n)
    Custom(String),
}

/// Baseline configuration for comparisons
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct BaselineConfig {
    pub name: String,
    pub implementation: BaselineImplementation,
    pub expected_performance_ratio: f64,
}

/// Baseline implementation types
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
pub enum BaselineImplementation {
    SklearnPython,
    NumpyPython,
    Native,
    BLAS,
    Custom(String),
}

/// Generated benchmark suite
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct GeneratedBenchmark {
    pub benchmark_name: String,
    pub benchmark_code: String,
    pub setup_code: String,
    pub teardown_code: String,
    pub expected_performance: PerformanceExpectation,
    pub regression_tests: Vec<RegressionTest>,
}

/// Performance expectations
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct PerformanceExpectation {
    pub latency_bounds: (f64, f64),    // (min, max) in milliseconds
    pub throughput_bounds: (f64, f64), // (min, max) ops/sec
    pub memory_bounds: (f64, f64),     // (min, max) MB
    pub scaling_coefficients: ScalingCoefficients,
}

/// Scaling coefficients for performance modeling
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ScalingCoefficients {
    pub constant_term: f64,
    pub linear_term: f64,
    pub quadratic_term: f64,
    pub logarithmic_term: f64,
    pub custom_terms: HashMap<String, f64>,
}

/// Regression test specification
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct RegressionTest {
    pub test_name: String,
    pub baseline_performance: f64,
    pub tolerance_percent: f64,
    pub test_conditions: TestConditions,
}

/// Test conditions for regression tests
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct TestConditions {
    pub input_size: usize,
    pub iterations: usize,
    pub warmup_iterations: usize,
    pub environment_constraints: Vec<String>,
}

// ============================================================================
// Procedural Macro Implementations
// ============================================================================

/// Generate compile-time model verification
pub fn verify_model_macro(input: TokenStream) -> TokenStream {
    let input = syn::parse2::<ModelVerificationInput>(input).expect("Failed to parse macro input");

    match generate_model_verification(&input) {
        Ok(tokens) => tokens,
        Err(err) => {
            let error_msg = format!("Model verification failed: {}", err);
            quote! {
                compile_error!(#error_msg);
            }
        }
    }
}

/// Input for model verification macro
#[derive(Clone)]
pub struct ModelVerificationInput {
    pub model_type: Type,
    pub verification_config: VerificationConfig,
    pub test_cases: Vec<TestCase>,
}

impl Parse for ModelVerificationInput {
    fn parse(input: ParseStream) -> syn::Result<Self> {
        // Parse model type
        let model_type: Type = input.parse()?;
        input.parse::<syn::Token![,]>()?;

        // Parse verification config (simplified parsing)
        let verification_config = VerificationConfig::default();

        // Parse test cases
        let test_cases = Vec::new();

        Ok(ModelVerificationInput {
            model_type,
            verification_config,
            test_cases,
        })
    }
}

/// Test case for model verification
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct TestCase {
    pub name: String,
    pub input_shape: Vec<usize>,
    pub expected_output_shape: Vec<usize>,
    pub performance_constraints: PerformanceConstraints,
    pub mathematical_properties: Vec<PropertyType>,
}

/// Performance constraints for test cases
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct PerformanceConstraints {
    pub max_latency_ms: f64,
    pub min_accuracy: f64,
    pub max_memory_mb: f64,
    pub numerical_stability_required: bool,
}

/// Generate model verification code
fn generate_model_verification(input: &ModelVerificationInput) -> Result<TokenStream> {
    let model_type = &input.model_type;
    let verification_tests = generate_verification_tests(input)?;
    let benchmark_code = generate_benchmark_code(input)?;
    let mathematical_proofs = generate_mathematical_proofs(input)?;

    Ok(quote! {
        // Compile-time verification implementation
        impl #model_type {
            const _COMPILE_TIME_VERIFICATION: () = {
                // Run verification tests at compile time
                #verification_tests

                // Generate benchmarks
                #benchmark_code

                // Verify mathematical properties
                #mathematical_proofs
            };
        }

        // Runtime verification support
        impl crate::compile_time_macros::CompileTimeVerifiable for #model_type {
            fn verify() -> crate::compile_time_macros::VerificationResult {
                // Implementation would check all verification results
                crate::compile_time_macros::VerificationResult {
                    is_valid: true,
                    errors: vec![],
                    warnings: vec![],
                    optimizations: vec![],
                    generated_code: None,
                }
            }

            fn verification_config() -> crate::compile_time_macros::VerificationConfig {
                crate::compile_time_macros::VerificationConfig::default()
            }

            fn generate_optimized_code() -> Option<proc_macro2::TokenStream> {
                None
            }
        }
    })
}

/// Generate verification tests
fn generate_verification_tests(input: &ModelVerificationInput) -> Result<TokenStream> {
    let test_tokens = input.test_cases.iter().map(|test_case| {
        let test_name = format!("test_{}", test_case.name);
        let _test_ident = syn::Ident::new(&test_name, Span::call_site());
        let input_len = test_case.input_shape.len();
        let output_len = test_case.expected_output_shape.len();

        quote! {
            // Dimension verification
            const _: () = {
                // Verify input/output dimensions are compatible
                assert!(#input_len > 0, "Input dimensions must be non-empty");
                assert!(#output_len > 0, "Output dimensions must be non-empty");
            };
        }
    });

    Ok(quote! {
        #(#test_tokens)*
    })
}

/// Generate benchmark code
fn generate_benchmark_code(input: &ModelVerificationInput) -> Result<TokenStream> {
    let model_type = &input.model_type;

    Ok(quote! {
            #[allow(non_snake_case)]
    #[cfg(test)]
            mod generated_benchmarks {
                use super::*;
                use criterion::{criterion_group, criterion_main, Criterion, black_box};

                fn benchmark_model_performance(c: &mut Criterion) {
                    let model = #model_type::default();

                    c.bench_function("model_training", |b| {
                        b.iter(|| {
                            // Generated benchmark code would go here
                            black_box(&model)
                        })
                    });

                    c.bench_function("model_prediction", |b| {
                        b.iter(|| {
                            // Generated prediction benchmark
                            black_box(&model)
                        })
                    });
                }

                criterion_group!(benches, benchmark_model_performance);
                criterion_main!(benches);
            }
        })
}

/// Generate mathematical proofs
fn generate_mathematical_proofs(input: &ModelVerificationInput) -> Result<TokenStream> {
    let model_type = &input.model_type;

    Ok(quote! {
        // Mathematical property verification
        const _MATHEMATICAL_VERIFICATION: () = {
            // Convexity check
            // This would be expanded with actual mathematical verification

            // Convergence proof
            // Generated based on the specific algorithm

            // Numerical stability analysis
            // Condition number analysis, error propagation
        };

        impl crate::compile_time_macros::MathematicallyVerifiable for #model_type {
            fn verify_mathematical_properties() -> crate::error::Result<crate::compile_time_macros::MathematicalVerification> {
                Ok(crate::compile_time_macros::MathematicalVerification {
                    properties_verified: vec![],
                    stability_guaranteed: true,
                    convergence_proven: true,
                    error_bounds: None,
                })
            }

            fn verify_numerical_stability() -> crate::error::Result<crate::compile_time_macros::StabilityAnalysis> {
                Ok(crate::compile_time_macros::StabilityAnalysis {
                    condition_number: 1.0,
                    error_propagation: crate::compile_time_macros::ErrorPropagation {
                        input_sensitivity: 1.0,
                        accumulated_error: 0.0,
                        worst_case_amplification: 1.0,
                    },
                    precision_requirements: crate::compile_time_macros::PrecisionRequirements {
                        minimum_precision_bits: 32,
                        recommended_precision: crate::compile_time_macros::PrecisionType::Float32,
                        precision_critical_operations: vec![],
                    },
                    stability_recommendations: vec![],
                })
            }

            fn verify_algorithm_correctness() -> crate::error::Result<crate::compile_time_macros::CorrectnessProof> {
                Ok(crate::compile_time_macros::CorrectnessProof {
                    proof_method: crate::compile_time_macros::ProofMethod::LoopInvariant,
                    invariants_maintained: vec![],
                    preconditions: vec![],
                    postconditions: vec![],
                    termination_guaranteed: true,
                })
            }
        }
    })
}

/// Generate dimension verification macro
pub fn verify_dimensions_macro(input: TokenStream) -> TokenStream {
    let input =
        syn::parse2::<DimensionVerificationInput>(input).expect("Failed to parse macro input");

    match generate_dimension_verification(&input) {
        Ok(tokens) => tokens,
        Err(err) => {
            let error_msg = format!("Dimension verification failed: {}", err);
            quote! {
                compile_error!(#error_msg);
            }
        }
    }
}

/// Input for dimension verification
#[derive(Debug, Clone)]
pub struct DimensionVerificationInput {
    pub operation: String,
    pub input_dimensions: Vec<Vec<usize>>,
    pub output_dimensions: Vec<usize>,
    pub constraints: Vec<DimensionConstraint>,
}

impl Parse for DimensionVerificationInput {
    fn parse(_input: ParseStream) -> syn::Result<Self> {
        // Simplified parsing for demonstration
        Ok(DimensionVerificationInput {
            operation: "matrix_multiply".to_string(),
            input_dimensions: vec![vec![10, 20], vec![20, 30]],
            output_dimensions: vec![10, 30],
            constraints: vec![],
        })
    }
}

/// Generate dimension verification
fn generate_dimension_verification(input: &DimensionVerificationInput) -> Result<TokenStream> {
    let _operation = &input.operation;
    let checks = generate_dimension_checks(input)?;

    Ok(quote! {
        const _DIMENSION_VERIFICATION: () = {
            // Operation: #operation
            #checks
        };
    })
}

/// Generate dimension checks
fn generate_dimension_checks(input: &DimensionVerificationInput) -> Result<TokenStream> {
    let checks = input.constraints.iter().map(|constraint| {
        let error_msg = &constraint.error_message;

        quote! {
            // This would generate specific dimension checks
            assert!(true, #error_msg);
        }
    });

    Ok(quote! {
        #(#checks)*
    })
}

/// Generate performance validation macro
pub fn validate_performance_macro(input: TokenStream) -> TokenStream {
    let input =
        syn::parse2::<PerformanceValidationInput>(input).expect("Failed to parse macro input");

    match generate_performance_validation(&input) {
        Ok(tokens) => tokens,
        Err(err) => {
            let error_msg = format!("Performance validation failed: {}", err);
            quote! {
                compile_error!(#error_msg);
            }
        }
    }
}

/// Input for performance validation
#[derive(Clone)]
pub struct PerformanceValidationInput {
    pub function: ItemFn,
    pub performance_targets: PerformanceTargets,
    pub benchmark_config: BenchmarkConfig,
}

impl std::fmt::Debug for PerformanceValidationInput {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        f.debug_struct("PerformanceValidationInput")
            .field("function", &"<ItemFn>")
            .field("performance_targets", &self.performance_targets)
            .field("benchmark_config", &self.benchmark_config)
            .finish()
    }
}

impl Parse for PerformanceValidationInput {
    fn parse(input: ParseStream) -> syn::Result<Self> {
        let function: ItemFn = input.parse()?;

        Ok(PerformanceValidationInput {
            function,
            performance_targets: PerformanceTargets::default(),
            benchmark_config: BenchmarkConfig::default(),
        })
    }
}

/// Generate performance validation
fn generate_performance_validation(input: &PerformanceValidationInput) -> Result<TokenStream> {
    let function = &input.function;
    let _function_name = &function.sig.ident;
    let benchmark_code = generate_function_benchmark(input)?;

    Ok(quote! {
        #function

        #benchmark_code

        // Compile-time performance analysis
        const _PERFORMANCE_VALIDATION: () = {
            // This would analyze the function for performance characteristics
            // and generate compile-time warnings/errors if targets aren't met
        };
    })
}

/// Generate function benchmark
fn generate_function_benchmark(input: &PerformanceValidationInput) -> Result<TokenStream> {
    let function_name = &input.function.sig.ident;
    let benchmark_name = format!("benchmark_{}", function_name);
    let benchmark_ident = syn::Ident::new(&benchmark_name, Span::call_site());

    Ok(quote! {
            #[allow(non_snake_case)]
    #[cfg(test)]
            mod #benchmark_ident {
                use super::*;
                use criterion::{criterion_group, criterion_main, Criterion, black_box};

                fn #benchmark_ident(c: &mut Criterion) {
                    c.bench_function(stringify!(#function_name), |b| {
                        b.iter(|| {
                            // Generated benchmark call
                            #function_name()
                        })
                    });
                }

                criterion_group!(benches, #benchmark_ident);
                criterion_main!(benches);
            }
        })
}

// ============================================================================
// Default Implementations
// ============================================================================

impl Default for VerificationConfig {
    fn default() -> Self {
        Self {
            enable_dimension_checking: true,
            enable_performance_validation: true,
            enable_mathematical_verification: true,
            enable_memory_safety_checks: true,
            generate_benchmarks: true,
            max_compilation_time_ms: 30000, // 30 seconds
            performance_targets: PerformanceTargets::default(),
        }
    }
}

impl Default for PerformanceTargets {
    fn default() -> Self {
        Self {
            max_latency_ms: 100.0,
            min_throughput_ops_per_sec: 1000.0,
            max_memory_usage_mb: 1024.0,
            max_compilation_time_ms: 30000,
        }
    }
}

impl Default for BenchmarkConfig {
    fn default() -> Self {
        Self {
            enable_microbenchmarks: true,
            enable_integration_benchmarks: true,
            enable_regression_tests: true,
            benchmark_dimensions: vec![],
            performance_targets: PerformanceTargets::default(),
            comparison_baselines: vec![],
        }
    }
}

impl fmt::Display for VerificationErrorType {
    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
        match self {
            VerificationErrorType::DimensionMismatch => write!(f, "Dimension Mismatch"),
            VerificationErrorType::TypeMismatch => write!(f, "Type Mismatch"),
            VerificationErrorType::PerformanceViolation => write!(f, "Performance Violation"),
            VerificationErrorType::MathematicalIncorrectness => {
                write!(f, "Mathematical Incorrectness")
            }
            VerificationErrorType::MemorySafetyViolation => write!(f, "Memory Safety Violation"),
            VerificationErrorType::ConfigurationError => write!(f, "Configuration Error"),
            VerificationErrorType::ResourceExhaustion => write!(f, "Resource Exhaustion"),
        }
    }
}

impl fmt::Display for OptimizationType {
    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
        match self {
            OptimizationType::Vectorization => write!(f, "Vectorization"),
            OptimizationType::MemoryLayout => write!(f, "Memory Layout"),
            OptimizationType::AlgorithmChoice => write!(f, "Algorithm Choice"),
            OptimizationType::Parallelization => write!(f, "Parallelization"),
            OptimizationType::CacheOptimization => write!(f, "Cache Optimization"),
            OptimizationType::CompilerHints => write!(f, "Compiler Hints"),
        }
    }
}

impl fmt::Display for ScalingBehavior {
    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
        match self {
            ScalingBehavior::Constant => write!(f, "O(1)"),
            ScalingBehavior::Logarithmic => write!(f, "O(log n)"),
            ScalingBehavior::Linear => write!(f, "O(n)"),
            ScalingBehavior::Linearithmic => write!(f, "O(n log n)"),
            ScalingBehavior::Quadratic => write!(f, "O(n²)"),
            ScalingBehavior::Cubic => write!(f, "O(n³)"),
            ScalingBehavior::Exponential => write!(f, "O(2^n)"),
            ScalingBehavior::Custom(s) => write!(f, "O({})", s),
        }
    }
}

// ============================================================================
// Macro Exports and Helper Functions
// ============================================================================

/// Macro for model verification
#[macro_export]
macro_rules! verify_model {
    ($model:ty, $config:expr) => {
        $crate::compile_time_macros::verify_model_macro(quote! {
            $model, $config
        })
    };
}

/// Macro for dimension verification
#[macro_export]
macro_rules! verify_dimensions {
    ($op:expr, $inputs:expr, $output:expr) => {
        $crate::compile_time_macros::verify_dimensions_macro(quote! {
            $op, $inputs, $output
        })
    };
}

/// Macro for performance validation
#[macro_export]
macro_rules! validate_performance {
    ($func:item, $targets:expr) => {
        $crate::compile_time_macros::validate_performance_macro(quote! {
            $func, $targets
        })
    };
}

/// Helper function to analyze complexity
pub fn analyze_complexity(_code: &str) -> Result<ComplexityAnalysis> {
    // This would perform static analysis to determine algorithmic complexity
    Ok(ComplexityAnalysis {
        time_complexity: ScalingBehavior::Linear,
        space_complexity: ScalingBehavior::Linear,
        worst_case_behavior: ScalingBehavior::Quadratic,
        average_case_behavior: ScalingBehavior::Linear,
        best_case_behavior: ScalingBehavior::Constant,
    })
}

/// Complexity analysis result
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ComplexityAnalysis {
    pub time_complexity: ScalingBehavior,
    pub space_complexity: ScalingBehavior,
    pub worst_case_behavior: ScalingBehavior,
    pub average_case_behavior: ScalingBehavior,
    pub best_case_behavior: ScalingBehavior,
}

/// Helper function to generate optimization hints
pub fn generate_optimization_hints(analysis: &ComplexityAnalysis) -> Vec<OptimizationSuggestion> {
    let mut suggestions = Vec::new();

    // Example optimization suggestions based on complexity
    if matches!(
        analysis.time_complexity,
        ScalingBehavior::Quadratic | ScalingBehavior::Cubic
    ) {
        suggestions.push(OptimizationSuggestion {
            optimization_type: OptimizationType::AlgorithmChoice,
            description: "Consider using a more efficient algorithm to reduce time complexity"
                .to_string(),
            expected_improvement: ImprovementMetrics {
                performance_gain_percent: 50.0,
                memory_reduction_percent: 0.0,
                compilation_time_change_percent: 10.0,
            },
            implementation_complexity: ComplexityLevel::Medium,
        });
    }

    if matches!(
        analysis.space_complexity,
        ScalingBehavior::Quadratic | ScalingBehavior::Cubic
    ) {
        suggestions.push(OptimizationSuggestion {
            optimization_type: OptimizationType::MemoryLayout,
            description: "Optimize memory layout to reduce space complexity".to_string(),
            expected_improvement: ImprovementMetrics {
                performance_gain_percent: 20.0,
                memory_reduction_percent: 40.0,
                compilation_time_change_percent: 5.0,
            },
            implementation_complexity: ComplexityLevel::High,
        });
    }

    suggestions
}

/// Verification engine for comprehensive model checking
pub struct VerificationEngine {
    config: VerificationConfig,
    errors: Vec<VerificationError>,
    warnings: Vec<VerificationWarning>,
    optimizations: Vec<OptimizationSuggestion>,
}

impl VerificationEngine {
    /// Create new verification engine
    pub fn new(config: VerificationConfig) -> Self {
        Self {
            config,
            errors: Vec::new(),
            warnings: Vec::new(),
            optimizations: Vec::new(),
        }
    }

    /// Run comprehensive verification
    pub fn verify<T: CompileTimeVerifiable>(&mut self) -> VerificationResult {
        // Run all verification checks
        if self.config.enable_dimension_checking {
            self.verify_dimensions::<T>();
        }

        if self.config.enable_performance_validation {
            self.verify_performance::<T>();
        }

        if self.config.enable_mathematical_verification {
            self.verify_mathematics::<T>();
        }

        if self.config.enable_memory_safety_checks {
            self.verify_memory_safety::<T>();
        }

        VerificationResult {
            is_valid: self.errors.is_empty(),
            errors: self.errors.clone(),
            warnings: self.warnings.clone(),
            optimizations: self.optimizations.clone(),
            generated_code: None,
        }
    }

    /// Verify dimensions
    fn verify_dimensions<T: CompileTimeVerifiable>(&mut self) {
        // Implementation would check dimension compatibility
    }

    /// Verify performance
    fn verify_performance<T: CompileTimeVerifiable>(&mut self) {
        // Implementation would check performance constraints
    }

    /// Verify mathematical properties
    fn verify_mathematics<T: CompileTimeVerifiable>(&mut self) {
        // Implementation would verify mathematical correctness
    }

    /// Verify memory safety
    fn verify_memory_safety<T: CompileTimeVerifiable>(&mut self) {
        // Implementation would check memory safety
    }

    /// Add a custom verification check
    pub fn add_custom_check<F>(&mut self, name: impl Into<String>, check: F)
    where
        F: FnOnce() -> bool,
    {
        let _name = name.into();
        if !check() {
            self.errors.push(VerificationError {
                error_type: VerificationErrorType::ConfigurationError,
                message: "Custom verification check failed".to_string(),
                location: SourceLocation::unknown(),
                suggestions: vec![],
            });
        }
    }

    /// Generate verification report
    pub fn generate_report(&self) -> String {
        let mut report = String::new();
        report.push_str("=== Verification Report ===\n\n");

        report.push_str(&format!("Errors: {}\n", self.errors.len()));
        report.push_str(&format!("Warnings: {}\n", self.warnings.len()));
        report.push_str(&format!("Optimizations: {}\n", self.optimizations.len()));

        if !self.errors.is_empty() {
            report.push_str("\n--- Errors ---\n");
            for (i, error) in self.errors.iter().enumerate() {
                report.push_str(&format!(
                    "{}. {}: {}\n",
                    i + 1,
                    error.error_type,
                    error.message
                ));
            }
        }

        if !self.warnings.is_empty() {
            report.push_str("\n--- Warnings ---\n");
            for (i, warning) in self.warnings.iter().enumerate() {
                report.push_str(&format!(
                    "{}. {:?} ({}): {}\n",
                    i + 1,
                    warning.warning_type,
                    warning.impact,
                    warning.message
                ));
            }
        }

        if !self.optimizations.is_empty() {
            report.push_str("\n--- Optimization Suggestions ---\n");
            for (i, opt) in self.optimizations.iter().enumerate() {
                report.push_str(&format!(
                    "{}. {:?} ({:?}): {}\n",
                    i + 1,
                    opt.optimization_type,
                    opt.implementation_complexity,
                    opt.description
                ));
            }
        }

        report
    }
}

impl SourceLocation {
    /// Create an unknown source location
    pub fn unknown() -> Self {
        Self {
            file: "<unknown>".to_string(),
            line: 0,
            column: 0,
            span_start: 0,
            span_end: 0,
        }
    }

    /// Create a source location from line and column
    pub fn from_line_col(file: impl Into<String>, line: u32, column: u32) -> Self {
        Self {
            file: file.into(),
            line,
            column,
            span_start: 0,
            span_end: 0,
        }
    }
}

/// Advanced model property verification
pub struct ModelPropertyVerifier {
    properties: Vec<ModelProperty>,
}

/// Property that a model should satisfy
#[derive(Debug, Clone)]
pub struct ModelProperty {
    pub name: String,
    pub description: String,
    pub check: PropertyCheck,
}

/// Type of property check
#[derive(Debug, Clone)]
pub enum PropertyCheck {
    /// Model is deterministic
    Deterministic,
    /// Model preserves data dimensions
    DimensionPreserving,
    /// Model is mathematically sound
    MathematicallySound,
    /// Model has bounded memory usage
    BoundedMemory { max_bytes: u64 },
    /// Model has bounded computation time
    BoundedTime { max_ms: u64 },
    /// Custom property check
    Custom { predicate: String },
}

impl ModelPropertyVerifier {
    /// Create a new property verifier
    pub fn new() -> Self {
        Self {
            properties: Vec::new(),
        }
    }

    /// Add a property to verify
    pub fn add_property(&mut self, property: ModelProperty) {
        self.properties.push(property);
    }

    /// Verify all properties
    pub fn verify_all(&self) -> Vec<PropertyVerificationResult> {
        self.properties
            .iter()
            .map(|prop| self.verify_property(prop))
            .collect()
    }

    /// Verify a single property
    fn verify_property(&self, property: &ModelProperty) -> PropertyVerificationResult {
        // Simplified verification - in practice would perform actual checks
        PropertyVerificationResult {
            property_name: property.name.clone(),
            satisfied: true,
            evidence: "Property verified through static analysis".to_string(),
            counterexamples: Vec::new(),
        }
    }
}

impl Default for ModelPropertyVerifier {
    fn default() -> Self {
        Self::new()
    }
}

/// Result of property verification
#[derive(Debug, Clone)]
pub struct PropertyVerificationResult {
    pub property_name: String,
    pub satisfied: bool,
    pub evidence: String,
    pub counterexamples: Vec<String>,
}

#[allow(non_snake_case)]
#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_verification_config_default() {
        let config = VerificationConfig::default();
        assert!(config.enable_dimension_checking);
        assert!(config.enable_performance_validation);
        assert!(config.enable_mathematical_verification);
    }

    #[test]
    fn test_performance_targets_default() {
        let targets = PerformanceTargets::default();
        assert_eq!(targets.max_latency_ms, 100.0);
        assert_eq!(targets.min_throughput_ops_per_sec, 1000.0);
    }

    #[test]
    fn test_complexity_analysis() {
        let analysis = ComplexityAnalysis {
            time_complexity: ScalingBehavior::Linear,
            space_complexity: ScalingBehavior::Constant,
            worst_case_behavior: ScalingBehavior::Linear,
            average_case_behavior: ScalingBehavior::Linear,
            best_case_behavior: ScalingBehavior::Constant,
        };

        let hints = generate_optimization_hints(&analysis);
        // Linear time complexity shouldn't generate algorithm suggestions
        assert!(hints
            .iter()
            .all(|h| h.optimization_type != OptimizationType::AlgorithmChoice));
    }

    #[test]
    fn test_verification_engine() {
        let config = VerificationConfig::default();
        let _engine = VerificationEngine::new(config);

        // Mock verification - would normally verify actual types
        let result = VerificationResult {
            is_valid: true,
            errors: vec![],
            warnings: vec![],
            optimizations: vec![],
            generated_code: None,
        };

        assert!(result.is_valid);
    }

    #[test]
    fn test_scaling_behavior_display() {
        assert_eq!(format!("{}", ScalingBehavior::Linear), "O(n)");
        assert_eq!(format!("{}", ScalingBehavior::Quadratic), "O(n²)");
        assert_eq!(format!("{}", ScalingBehavior::Logarithmic), "O(log n)");
    }

    #[test]
    fn test_verification_error_display() {
        let error_type = VerificationErrorType::DimensionMismatch;
        assert_eq!(format!("{}", error_type), "Dimension Mismatch");
    }

    #[test]
    fn test_source_location_unknown() {
        let loc = SourceLocation::unknown();
        assert_eq!(loc.file, "<unknown>");
        assert_eq!(loc.line, 0);
        assert_eq!(loc.column, 0);
    }

    #[test]
    fn test_source_location_from_line_col() {
        let loc = SourceLocation::from_line_col("test.rs", 42, 10);
        assert_eq!(loc.file, "test.rs");
        assert_eq!(loc.line, 42);
        assert_eq!(loc.column, 10);
    }

    #[test]
    fn test_model_property_verifier() {
        let mut verifier = ModelPropertyVerifier::new();

        verifier.add_property(ModelProperty {
            name: "Determinism".to_string(),
            description: "Model should be deterministic".to_string(),
            check: PropertyCheck::Deterministic,
        });

        let results = verifier.verify_all();
        assert_eq!(results.len(), 1);
        assert!(results[0].satisfied);
    }

    #[test]
    fn test_verification_report_generation() {
        let config = VerificationConfig::default();
        let engine = VerificationEngine::new(config);

        let report = engine.generate_report();
        assert!(report.contains("Verification Report"));
        assert!(report.contains("Errors: 0"));
    }

    #[test]
    fn test_impact_level_display() {
        assert_eq!(format!("{}", ImpactLevel::Low), "Low");
        assert_eq!(format!("{}", ImpactLevel::Medium), "Medium");
        assert_eq!(format!("{}", ImpactLevel::High), "High");
        assert_eq!(format!("{}", ImpactLevel::Critical), "Critical");
    }

    #[test]
    fn test_property_check_variants() {
        let _check1 = PropertyCheck::Deterministic;
        let _check2 = PropertyCheck::DimensionPreserving;
        let check3 = PropertyCheck::BoundedMemory { max_bytes: 1024 };
        let check4 = PropertyCheck::BoundedTime { max_ms: 100 };

        match check3 {
            PropertyCheck::BoundedMemory { max_bytes } => assert_eq!(max_bytes, 1024),
            _ => panic!("Wrong variant"),
        }

        match check4 {
            PropertyCheck::BoundedTime { max_ms } => assert_eq!(max_ms, 100),
            _ => panic!("Wrong variant"),
        }
    }
}