1629 lines
40 KiB
Rust
1629 lines
40 KiB
Rust
//! Error Detection and Syndrome Analysis Systems
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//!
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//! This module contains error syndrome detection, pattern recognition,
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//! and alerting systems for quantum error correction.
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use crate::error::{AiContextError, AiContextResult};
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use super::error_correction_core::{ErrorCorrectionConfig, QuantumErrorType, ErrorLocation, CorrectionRecommendation, CorrectionOperation, CorrectionType};
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use serde::{Deserialize, Serialize};
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use std::collections::HashMap;
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use std::sync::Arc;
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use tokio::sync::RwLock;
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use tokio::time::{Duration, Instant};
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use tracing::{debug, info, trace};
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/// Error syndrome detection result
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct ErrorSyndrome {
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/// Syndrome identifier
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pub syndrome_id: String,
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/// Detection timestamp
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pub detected_at: crate::temporal::TemporalTimestamp,
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/// Syndrome pattern
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pub pattern: SyndromePattern,
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/// Error type classification
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pub error_type: QuantumErrorType,
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/// Error location
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pub location: ErrorLocation,
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/// Syndrome confidence
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pub confidence: f64,
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/// Correction recommendation
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pub correction: CorrectionRecommendation,
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}
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/// Syndrome pattern for error detection
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct SyndromePattern {
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/// Pattern bits
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pub bits: Vec<u8>,
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/// Pattern weight
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pub weight: u32,
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/// Pattern parity
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pub parity: u8,
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/// Stabilizer measurements
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pub stabilizer_outcomes: Vec<StabilizerOutcome>,
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}
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/// Stabilizer measurement outcome
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct StabilizerOutcome {
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/// Stabilizer identifier
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pub stabilizer_id: String,
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/// Measurement result
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pub measurement: u8, // 0 or 1
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/// Measurement confidence
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pub confidence: f64,
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/// Associated qubits
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pub qubits: Vec<usize>,
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}
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/// Quantum parity check for error detection
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct QuantumParityCheck {
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/// Check identifier
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pub check_id: String,
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/// Parity check matrix
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pub check_matrix: ParityCheckMatrix,
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/// Check qubits
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pub check_qubits: Vec<usize>,
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/// Data qubits
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pub data_qubits: Vec<usize>,
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/// Check frequency
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pub frequency: f64,
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/// Detection efficiency
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pub efficiency: f64,
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}
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/// Parity check matrix
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct ParityCheckMatrix {
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/// Matrix dimensions
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pub dimensions: (usize, usize),
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/// Matrix elements
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pub elements: Vec<Vec<u8>>,
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/// Matrix rank
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pub rank: usize,
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/// Null space dimension
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pub null_space_dim: usize,
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}
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/// Error syndrome detector
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#[derive(Debug)]
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pub struct ErrorSyndromeDetector {
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/// Detection algorithms
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algorithms: Vec<SyndromeDetectionAlgorithm>,
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/// Syndrome database
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syndrome_db: Arc<RwLock<SyndromeDatabase>>,
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/// Real-time detector
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realtime_detector: Arc<RealtimeSyndromeDetector>,
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/// Pattern recognizer
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pattern_recognizer: Arc<SyndromePatternRecognizer>,
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}
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/// Syndrome detection algorithm
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#[derive(Debug, Clone)]
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pub struct SyndromeDetectionAlgorithm {
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/// Algorithm identifier
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pub algorithm_id: String,
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/// Detection method
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pub method: DetectionMethod,
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/// Detection accuracy
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pub accuracy: f64,
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/// Detection latency
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pub latency: Duration,
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/// Resource requirements
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pub resources: DetectionResources,
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}
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/// Detection methods
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#[derive(Debug, Clone)]
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pub enum DetectionMethod {
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ParityCheck,
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StabilizerMeasurement,
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ProcessTomography,
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RandomizedBenchmarking,
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QuantumVolumeMeasurement,
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CrossEntropyBenchmarking,
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}
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/// Detection resource requirements
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#[derive(Debug, Clone)]
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pub struct DetectionResources {
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/// Measurement shots
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pub shots: u64,
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/// Classical processing
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pub classical_compute: f64,
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/// Quantum circuit depth
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pub circuit_depth: u32,
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/// Measurement time
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pub measurement_time: Duration,
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}
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/// Syndrome database
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#[derive(Debug)]
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pub struct SyndromeDatabase {
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/// Known syndromes
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syndromes: HashMap<String, KnownSyndrome>,
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/// Syndrome patterns
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patterns: Vec<SyndromePatternEntry>,
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/// Database statistics
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statistics: SyndromeStatistics,
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}
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/// Known syndrome entry
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#[derive(Debug, Clone)]
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pub struct KnownSyndrome {
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/// Syndrome identifier
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pub syndrome_id: String,
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/// Syndrome signature
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pub signature: SyndromeSignature,
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/// Associated errors
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pub errors: Vec<AssociatedError>,
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/// Frequency of occurrence
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pub frequency: f64,
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/// Typical correction
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pub correction: CorrectionOperation,
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}
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/// Syndrome signature
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#[derive(Debug, Clone)]
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pub struct SyndromeSignature {
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/// Signature bits
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pub bits: Vec<u8>,
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/// Signature hash
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pub hash: u64,
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/// Signature confidence
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pub confidence: f64,
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}
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/// Associated error
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#[derive(Debug, Clone)]
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pub struct AssociatedError {
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/// Error description
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pub description: String,
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/// Error probability
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pub probability: f64,
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/// Error impact
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pub impact: ErrorImpact,
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}
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/// Error impact assessment
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#[derive(Debug, Clone)]
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pub struct ErrorImpact {
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/// Logical error probability
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pub logical_error_prob: f64,
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/// Performance degradation
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pub performance_impact: f64,
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/// Fidelity reduction
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pub fidelity_impact: f64,
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/// Cascading error potential
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pub cascade_potential: f64,
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}
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/// Syndrome pattern entry
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#[derive(Debug, Clone)]
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pub struct SyndromePatternEntry {
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/// Pattern identifier
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pub pattern_id: String,
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/// Pattern characteristics
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pub characteristics: PatternCharacteristics,
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/// Pattern evolution
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pub evolution: PatternEvolution,
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}
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/// Pattern characteristics
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#[derive(Debug, Clone)]
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pub struct PatternCharacteristics {
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/// Temporal structure
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pub temporal_structure: TemporalStructure,
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/// Spatial structure
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pub spatial_structure: SpatialStructure,
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/// Correlation structure
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pub correlation_structure: CorrelationStructure,
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}
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/// Temporal structure of patterns
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#[derive(Debug, Clone)]
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pub struct TemporalStructure {
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/// Pattern duration
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pub duration: Duration,
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/// Repetition frequency
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pub frequency: f64,
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/// Temporal correlations
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pub correlations: Vec<TemporalCorrelation>,
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}
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/// Temporal correlation
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#[derive(Debug, Clone)]
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pub struct TemporalCorrelation {
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/// Time lag
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pub lag: Duration,
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/// Correlation strength
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pub strength: f64,
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/// Correlation type
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pub correlation_type: CorrelationType,
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}
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/// Types of correlations
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#[derive(Debug, Clone)]
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pub enum CorrelationType {
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AutoCorrelation,
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CrossCorrelation,
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PartialCorrelation,
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ConditionalCorrelation,
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}
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/// Spatial structure of patterns
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#[derive(Debug, Clone)]
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pub struct SpatialStructure {
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/// Geometric layout
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pub layout: GeometricLayout,
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/// Connectivity patterns
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pub connectivity: ConnectivityPattern,
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/// Spatial correlations
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pub correlations: Vec<SpatialCorrelation>,
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}
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/// Geometric layout
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#[derive(Debug, Clone)]
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pub struct GeometricLayout {
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/// Layout type
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pub layout_type: LayoutType,
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/// Dimensions
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pub dimensions: Vec<u32>,
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/// Boundary conditions
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pub boundaries: BoundaryConditions,
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}
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/// Types of geometric layouts
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#[derive(Debug, Clone)]
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pub enum LayoutType {
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Square,
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Hexagonal,
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Triangular,
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Cubic,
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Hypercubic,
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Irregular,
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}
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/// Boundary conditions
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#[derive(Debug, Clone)]
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pub struct BoundaryConditions {
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/// Boundary type
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pub boundary_type: BoundaryType,
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/// Periodic boundaries
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pub periodic: Vec<bool>,
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/// Boundary effects
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pub effects: Vec<BoundaryEffect>,
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}
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/// Types of boundaries
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#[derive(Debug, Clone)]
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pub enum BoundaryType {
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Open,
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Periodic,
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Reflecting,
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Absorbing,
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Mixed,
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}
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/// Boundary effect
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#[derive(Debug, Clone)]
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pub struct BoundaryEffect {
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/// Effect type
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pub effect_type: EffectType,
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/// Effect strength
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pub strength: f64,
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/// Affected region
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pub region: Vec<usize>,
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}
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/// Types of boundary effects
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#[derive(Debug, Clone)]
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pub enum EffectType {
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ErrorRateIncrease,
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DecoherenceIncrease,
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CorrelationIncrease,
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FidelityDecrease,
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}
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/// Connectivity pattern
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#[derive(Debug, Clone)]
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pub struct ConnectivityPattern {
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/// Pattern type
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pub pattern_type: ConnectivityType,
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/// Adjacency matrix
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pub adjacency: Vec<Vec<bool>>,
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/// Connection weights
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pub weights: Vec<Vec<f64>>,
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}
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/// Types of connectivity
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#[derive(Debug, Clone)]
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pub enum ConnectivityType {
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NearestNeighbor,
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NextNearestNeighbor,
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LongRange,
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AllToAll,
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Random,
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SmallWorld,
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}
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/// Spatial correlation
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#[derive(Debug, Clone)]
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pub struct SpatialCorrelation {
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/// Correlation range
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pub range: f64,
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/// Correlation strength
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pub strength: f64,
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/// Correlation function
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pub function: CorrelationFunction,
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}
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/// Correlation functions
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#[derive(Debug, Clone)]
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pub enum CorrelationFunction {
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Exponential,
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PowerLaw,
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Gaussian,
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Polynomial,
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Custom,
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}
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/// Correlation structure
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#[derive(Debug, Clone)]
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pub struct CorrelationStructure {
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/// Correlation matrix
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pub matrix: Vec<Vec<f64>>,
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/// Principal components
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pub principal_components: Vec<PrincipalComponent>,
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/// Clustering information
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pub clusters: Vec<CorrelationCluster>,
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}
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/// Principal component
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#[derive(Debug, Clone)]
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pub struct PrincipalComponent {
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/// Component index
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pub index: usize,
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/// Eigenvalue
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pub eigenvalue: f64,
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/// Eigenvector
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pub eigenvector: Vec<f64>,
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/// Explained variance
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pub explained_variance: f64,
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}
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/// Correlation cluster
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#[derive(Debug, Clone)]
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pub struct CorrelationCluster {
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/// Cluster identifier
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pub cluster_id: String,
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/// Cluster members
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pub members: Vec<usize>,
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/// Cluster centroid
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pub centroid: Vec<f64>,
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/// Intra-cluster correlation
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pub intra_correlation: f64,
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}
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/// Pattern evolution
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#[derive(Debug, Clone)]
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pub struct PatternEvolution {
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/// Evolution trajectory
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pub trajectory: Vec<EvolutionPoint>,
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/// Evolution rate
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pub rate: f64,
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/// Evolution direction
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pub direction: EvolutionDirection,
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/// Stability measure
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pub stability: f64,
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}
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/// Evolution point
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#[derive(Debug, Clone)]
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pub struct EvolutionPoint {
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/// Timestamp
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pub timestamp: crate::temporal::TemporalTimestamp,
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/// Pattern state
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pub state: PatternState,
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/// State transition
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pub transition: Option<StateTransition>,
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}
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/// Pattern state
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#[derive(Debug, Clone)]
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pub struct PatternState {
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/// State characteristics
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pub characteristics: StateCharacteristics,
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/// State stability
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pub stability: f64,
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/// State entropy
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pub entropy: f64,
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}
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/// State characteristics
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#[derive(Debug, Clone)]
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pub struct StateCharacteristics {
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/// Energy level
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pub energy: f64,
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/// Complexity measure
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pub complexity: f64,
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/// Order parameter
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pub order: f64,
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/// Noise level
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pub noise: f64,
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}
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/// State transition
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#[derive(Debug, Clone)]
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pub struct StateTransition {
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/// Transition type
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pub transition_type: TransitionType,
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/// Transition probability
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pub probability: f64,
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/// Transition rate
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pub rate: f64,
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/// Activation energy
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pub activation_energy: f64,
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}
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/// Types of state transitions
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#[derive(Debug, Clone)]
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pub enum TransitionType {
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Continuous,
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Discontinuous,
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PhaseTransition,
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QuantumPhaseTransition,
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Topological,
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}
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/// Evolution directions
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#[derive(Debug, Clone)]
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pub enum EvolutionDirection {
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OrderIncreasing,
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OrderDecreasing,
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ComplexityIncreasing,
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ComplexityDecreasing,
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Oscillatory,
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Chaotic,
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}
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/// Syndrome statistics
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#[derive(Debug, Clone)]
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pub struct SyndromeStatistics {
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/// Total syndromes recorded
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pub total_syndromes: u64,
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/// Unique syndrome patterns
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pub unique_patterns: u64,
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/// Average detection time
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pub avg_detection_time: Duration,
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/// Detection accuracy
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pub accuracy: f64,
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/// False positive rate
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pub false_positive_rate: f64,
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}
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/// Real-time syndrome detector
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#[derive(Debug)]
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pub struct RealtimeSyndromeDetector {
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/// Detection pipeline
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pipeline: Arc<DetectionPipeline>,
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/// Streaming processor
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processor: Arc<StreamingSyndromeProcessor>,
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/// Alert system
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alert_system: Arc<SyndromeAlertSystem>,
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}
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/// Detection pipeline
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#[derive(Debug)]
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pub struct DetectionPipeline {
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/// Pipeline stages
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pub stages: Vec<DetectionStage>,
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/// Pipeline throughput
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pub throughput: f64,
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/// Pipeline latency
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pub latency: Duration,
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}
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/// Detection stage
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#[derive(Debug, Clone)]
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pub struct DetectionStage {
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/// Stage identifier
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pub stage_id: String,
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/// Stage function
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pub function: DetectionFunction,
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/// Processing time
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pub processing_time: Duration,
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/// Stage accuracy
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pub accuracy: f64,
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}
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/// Detection functions
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#[derive(Debug, Clone)]
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pub enum DetectionFunction {
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DataIngestion,
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Preprocessing,
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SyndromeExtraction,
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PatternMatching,
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ErrorClassification,
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ConfidenceAssessment,
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}
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/// Streaming syndrome processor
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#[derive(Debug)]
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pub struct StreamingSyndromeProcessor {
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/// Processing buffers
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buffers: Vec<ProcessingBuffer>,
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/// Stream multiplexer
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multiplexer: Arc<StreamMultiplexer>,
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/// Output dispatcher
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dispatcher: Arc<OutputDispatcher>,
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}
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/// Processing buffer
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#[derive(Debug)]
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pub struct ProcessingBuffer {
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/// Buffer identifier
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pub buffer_id: String,
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/// Buffer capacity
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pub capacity: usize,
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/// Current utilization
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pub utilization: f64,
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/// Buffer type
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pub buffer_type: BufferType,
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}
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/// Types of processing buffers
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#[derive(Debug, Clone)]
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pub enum BufferType {
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Input,
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Intermediate,
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Output,
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Cache,
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History,
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}
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/// Stream multiplexer
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#[derive(Debug)]
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pub struct StreamMultiplexer {
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/// Input streams
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pub streams: Vec<InputStream>,
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/// Multiplexing strategy
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pub strategy: MultiplexingStrategy,
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/// Load balancing
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pub load_balancing: bool,
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}
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/// Input stream
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#[derive(Debug, Clone)]
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pub struct InputStream {
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/// Stream identifier
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pub stream_id: String,
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/// Stream rate
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pub rate: f64,
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/// Stream priority
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pub priority: u32,
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/// Quality of service
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pub qos: QualityOfService,
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}
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/// Quality of service parameters
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#[derive(Debug, Clone)]
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pub struct QualityOfService {
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/// Maximum latency
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pub max_latency: Duration,
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/// Minimum throughput
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pub min_throughput: f64,
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/// Reliability requirement
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pub reliability: f64,
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/// Jitter tolerance
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pub jitter_tolerance: Duration,
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}
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/// Multiplexing strategies
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#[derive(Debug, Clone)]
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pub enum MultiplexingStrategy {
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RoundRobin,
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Priority,
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WeightedFairQueuing,
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AdaptiveStrategy,
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}
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/// Output dispatcher
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#[derive(Debug)]
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pub struct OutputDispatcher {
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/// Dispatch rules
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rules: Vec<DispatchRule>,
|
|
/// Output channels
|
|
channels: HashMap<String, OutputChannel>,
|
|
}
|
|
|
|
/// Dispatch rule
|
|
#[derive(Debug, Clone)]
|
|
pub struct DispatchRule {
|
|
/// Rule identifier
|
|
pub rule_id: String,
|
|
/// Rule condition
|
|
pub condition: DispatchCondition,
|
|
/// Target channel
|
|
pub target: String,
|
|
/// Rule priority
|
|
pub priority: u32,
|
|
}
|
|
|
|
/// Dispatch condition
|
|
#[derive(Debug, Clone)]
|
|
pub struct DispatchCondition {
|
|
/// Condition type
|
|
pub condition_type: ConditionType,
|
|
/// Condition parameters
|
|
pub parameters: HashMap<String, f64>,
|
|
/// Evaluation logic
|
|
pub logic: String,
|
|
}
|
|
|
|
/// Types of dispatch conditions
|
|
#[derive(Debug, Clone)]
|
|
pub enum ConditionType {
|
|
SeverityThreshold,
|
|
ErrorType,
|
|
ConfidenceLevel,
|
|
TimeWindow,
|
|
FrequencyThreshold,
|
|
}
|
|
|
|
/// Output channel
|
|
#[derive(Debug)]
|
|
pub struct OutputChannel {
|
|
/// Channel identifier
|
|
pub channel_id: String,
|
|
/// Channel capacity
|
|
pub capacity: f64,
|
|
/// Current load
|
|
pub load: f64,
|
|
/// Channel reliability
|
|
pub reliability: f64,
|
|
}
|
|
|
|
/// Syndrome alert system
|
|
#[derive(Debug)]
|
|
pub struct SyndromeAlertSystem {
|
|
/// Alert rules
|
|
rules: Vec<SyndromeAlertRule>,
|
|
/// Active alerts
|
|
active_alerts: Arc<RwLock<Vec<SyndromeAlert>>>,
|
|
/// Escalation procedures
|
|
escalation: Vec<EscalationProcedure>,
|
|
}
|
|
|
|
/// Syndrome alert rule
|
|
#[derive(Debug, Clone)]
|
|
pub struct SyndromeAlertRule {
|
|
/// Rule identifier
|
|
pub rule_id: String,
|
|
/// Trigger condition
|
|
pub trigger: AlertTrigger,
|
|
/// Alert severity
|
|
pub severity: AlertSeverity,
|
|
/// Response procedure
|
|
pub response: ResponseProcedure,
|
|
}
|
|
|
|
/// Alert trigger conditions
|
|
#[derive(Debug, Clone)]
|
|
pub enum AlertTrigger {
|
|
ErrorRateExceeded(f64),
|
|
UnknownSyndrome,
|
|
CorrectionFailure,
|
|
SystemDegradation,
|
|
CriticalError,
|
|
}
|
|
|
|
/// Alert severity levels
|
|
#[derive(Debug, Clone)]
|
|
pub enum AlertSeverity {
|
|
Info,
|
|
Warning,
|
|
Error,
|
|
Critical,
|
|
Emergency,
|
|
}
|
|
|
|
/// Response procedure
|
|
#[derive(Debug, Clone)]
|
|
pub struct ResponseProcedure {
|
|
/// Procedure steps
|
|
pub steps: Vec<ResponseStep>,
|
|
/// Escalation threshold
|
|
pub escalation_threshold: Duration,
|
|
/// Auto-response enabled
|
|
pub auto_response: bool,
|
|
}
|
|
|
|
/// Response step
|
|
#[derive(Debug, Clone)]
|
|
pub struct ResponseStep {
|
|
/// Step description
|
|
pub description: String,
|
|
/// Step action
|
|
pub action: ResponseAction,
|
|
/// Step timeout
|
|
pub timeout: Duration,
|
|
}
|
|
|
|
/// Response actions
|
|
#[derive(Debug, Clone)]
|
|
pub enum ResponseAction {
|
|
LogEvent,
|
|
NotifyOperator,
|
|
AttemptCorrection,
|
|
IsolateError,
|
|
EscalateAlert,
|
|
ShutdownSystem,
|
|
}
|
|
|
|
/// Syndrome alert
|
|
#[derive(Debug, Clone)]
|
|
pub struct SyndromeAlert {
|
|
/// Alert identifier
|
|
pub alert_id: String,
|
|
/// Alert timestamp
|
|
pub timestamp: crate::temporal::TemporalTimestamp,
|
|
/// Alert severity
|
|
pub severity: AlertSeverity,
|
|
/// Alert message
|
|
pub message: String,
|
|
/// Associated syndrome
|
|
pub syndrome: String,
|
|
/// Response status
|
|
pub response_status: ResponseStatus,
|
|
}
|
|
|
|
/// Response status
|
|
#[derive(Debug, Clone)]
|
|
pub enum ResponseStatus {
|
|
Pending,
|
|
InProgress,
|
|
Completed,
|
|
Failed,
|
|
Escalated,
|
|
}
|
|
|
|
/// Escalation procedure
|
|
#[derive(Debug, Clone)]
|
|
pub struct EscalationProcedure {
|
|
/// Procedure identifier
|
|
pub procedure_id: String,
|
|
/// Escalation trigger
|
|
pub trigger: EscalationTrigger,
|
|
/// Escalation target
|
|
pub target: EscalationTarget,
|
|
/// Escalation timeline
|
|
pub timeline: Duration,
|
|
}
|
|
|
|
/// Escalation triggers
|
|
#[derive(Debug, Clone)]
|
|
pub enum EscalationTrigger {
|
|
TimeElapsed(Duration),
|
|
SeverityIncrease,
|
|
RepeatOccurrence,
|
|
SystemFailure,
|
|
ManualEscalation,
|
|
}
|
|
|
|
/// Escalation targets
|
|
#[derive(Debug, Clone)]
|
|
pub enum EscalationTarget {
|
|
NextLevel,
|
|
TechnicalTeam,
|
|
ManagementTeam,
|
|
ExternalSupport,
|
|
EmergencyProtocol,
|
|
}
|
|
|
|
/// Syndrome pattern recognizer
|
|
#[derive(Debug)]
|
|
pub struct SyndromePatternRecognizer {
|
|
/// Recognition algorithms
|
|
algorithms: Vec<RecognitionAlgorithm>,
|
|
/// Pattern library
|
|
library: Arc<PatternLibrary>,
|
|
/// Machine learning models
|
|
ml_models: Vec<PatternRecognitionModel>,
|
|
}
|
|
|
|
/// Recognition algorithm
|
|
#[derive(Debug, Clone)]
|
|
pub struct RecognitionAlgorithm {
|
|
/// Algorithm identifier
|
|
pub algorithm_id: String,
|
|
/// Recognition method
|
|
pub method: RecognitionMethod,
|
|
/// Recognition accuracy
|
|
pub accuracy: f64,
|
|
/// Processing speed
|
|
pub speed: f64,
|
|
}
|
|
|
|
/// Recognition methods
|
|
#[derive(Debug, Clone)]
|
|
pub enum RecognitionMethod {
|
|
TemplateMatching,
|
|
FeatureMatching,
|
|
StatisticalMatching,
|
|
MachineLearning,
|
|
DeepLearning,
|
|
EnsembleMethod,
|
|
}
|
|
|
|
/// Pattern library
|
|
#[derive(Debug)]
|
|
pub struct PatternLibrary {
|
|
/// Library patterns
|
|
pub patterns: HashMap<String, LibraryPattern>,
|
|
/// Pattern hierarchies
|
|
pub hierarchies: Vec<PatternHierarchy>,
|
|
/// Search index
|
|
pub index: PatternSearchIndex,
|
|
}
|
|
|
|
/// Library pattern
|
|
#[derive(Debug, Clone)]
|
|
pub struct LibraryPattern {
|
|
/// Pattern identifier
|
|
pub pattern_id: String,
|
|
/// Pattern template
|
|
pub template: PatternTemplate,
|
|
/// Usage statistics
|
|
pub usage: UsageStatistics,
|
|
/// Pattern metadata
|
|
pub metadata: PatternMetadata,
|
|
}
|
|
|
|
/// Pattern template
|
|
#[derive(Debug, Clone)]
|
|
pub struct PatternTemplate {
|
|
/// Template structure
|
|
pub structure: TemplateStructure,
|
|
/// Variable parameters
|
|
pub parameters: Vec<TemplateParameter>,
|
|
/// Matching criteria
|
|
pub criteria: MatchingCriteria,
|
|
}
|
|
|
|
/// Template structure
|
|
#[derive(Debug, Clone)]
|
|
pub struct TemplateStructure {
|
|
/// Structure type
|
|
pub structure_type: StructureType,
|
|
/// Structure elements
|
|
pub elements: Vec<StructureElement>,
|
|
/// Element relationships
|
|
pub relationships: Vec<ElementRelationship>,
|
|
}
|
|
|
|
/// Types of template structures
|
|
#[derive(Debug, Clone)]
|
|
pub enum StructureType {
|
|
Sequential,
|
|
Hierarchical,
|
|
Network,
|
|
Tree,
|
|
Graph,
|
|
Matrix,
|
|
}
|
|
|
|
/// Structure element
|
|
#[derive(Debug, Clone)]
|
|
pub struct StructureElement {
|
|
/// Element identifier
|
|
pub element_id: String,
|
|
/// Element type
|
|
pub element_type: ElementType,
|
|
/// Element properties
|
|
pub properties: HashMap<String, f64>,
|
|
}
|
|
|
|
/// Types of structure elements
|
|
#[derive(Debug, Clone)]
|
|
pub enum ElementType {
|
|
Node,
|
|
Edge,
|
|
Cluster,
|
|
Substructure,
|
|
Marker,
|
|
}
|
|
|
|
/// Element relationship
|
|
#[derive(Debug, Clone)]
|
|
pub struct ElementRelationship {
|
|
/// Relationship identifier
|
|
pub relationship_id: String,
|
|
/// Source element
|
|
pub source: String,
|
|
/// Target element
|
|
pub target: String,
|
|
/// Relationship type
|
|
pub relationship_type: RelationshipType,
|
|
/// Relationship strength
|
|
pub strength: f64,
|
|
}
|
|
|
|
/// Types of element relationships
|
|
#[derive(Debug, Clone)]
|
|
pub enum RelationshipType {
|
|
Parent,
|
|
Child,
|
|
Sibling,
|
|
Dependency,
|
|
Association,
|
|
Aggregation,
|
|
}
|
|
|
|
/// Template parameter
|
|
#[derive(Debug, Clone)]
|
|
pub struct TemplateParameter {
|
|
/// Parameter name
|
|
pub name: String,
|
|
/// Parameter type
|
|
pub param_type: TemplateParameterType,
|
|
/// Default value
|
|
pub default: f64,
|
|
/// Value range
|
|
pub range: (f64, f64),
|
|
}
|
|
|
|
/// Types of template parameters
|
|
#[derive(Debug, Clone)]
|
|
pub enum TemplateParameterType {
|
|
Continuous,
|
|
Discrete,
|
|
Categorical,
|
|
Boolean,
|
|
}
|
|
|
|
/// Matching criteria for patterns
|
|
#[derive(Debug, Clone)]
|
|
pub struct MatchingCriteria {
|
|
/// Similarity threshold
|
|
pub similarity_threshold: f64,
|
|
/// Required features
|
|
pub required_features: Vec<String>,
|
|
/// Optional features
|
|
pub optional_features: Vec<String>,
|
|
/// Exclusion criteria
|
|
pub exclusions: Vec<String>,
|
|
}
|
|
|
|
/// Usage statistics for patterns
|
|
#[derive(Debug, Clone)]
|
|
pub struct UsageStatistics {
|
|
/// Usage frequency
|
|
pub frequency: f64,
|
|
/// Success rate
|
|
pub success_rate: f64,
|
|
/// Average processing time
|
|
pub avg_time: Duration,
|
|
/// User ratings
|
|
pub ratings: Vec<f64>,
|
|
}
|
|
|
|
/// Pattern metadata
|
|
#[derive(Debug, Clone)]
|
|
pub struct PatternMetadata {
|
|
/// Creation timestamp
|
|
pub created: crate::temporal::TemporalTimestamp,
|
|
/// Last updated
|
|
pub updated: crate::temporal::TemporalTimestamp,
|
|
/// Version number
|
|
pub version: String,
|
|
/// Author information
|
|
pub author: String,
|
|
/// Pattern tags
|
|
pub tags: Vec<String>,
|
|
}
|
|
|
|
/// Pattern hierarchy
|
|
#[derive(Debug, Clone)]
|
|
pub struct PatternHierarchy {
|
|
/// Hierarchy identifier
|
|
pub hierarchy_id: String,
|
|
/// Root patterns
|
|
pub roots: Vec<String>,
|
|
/// Parent-child relationships
|
|
pub relationships: Vec<HierarchyRelationship>,
|
|
/// Hierarchy depth
|
|
pub depth: u32,
|
|
}
|
|
|
|
/// Hierarchy relationship
|
|
#[derive(Debug, Clone)]
|
|
pub struct HierarchyRelationship {
|
|
/// Parent pattern
|
|
pub parent: String,
|
|
/// Child pattern
|
|
pub child: String,
|
|
/// Relationship strength
|
|
pub strength: f64,
|
|
/// Inheritance properties
|
|
pub inheritance: Vec<String>,
|
|
}
|
|
|
|
/// Pattern search index
|
|
#[derive(Debug)]
|
|
pub struct PatternSearchIndex {
|
|
/// Index entries
|
|
pub entries: Vec<PatternIndexEntry>,
|
|
/// Search algorithms
|
|
pub algorithms: Vec<PatternSearchAlgorithm>,
|
|
}
|
|
|
|
/// Pattern index entry
|
|
#[derive(Debug, Clone)]
|
|
pub struct PatternIndexEntry {
|
|
/// Pattern identifier
|
|
pub pattern_id: String,
|
|
/// Search keywords
|
|
pub keywords: Vec<String>,
|
|
/// Feature vector
|
|
pub features: Vec<f64>,
|
|
/// Index score
|
|
pub score: f64,
|
|
}
|
|
|
|
/// Pattern search algorithm
|
|
#[derive(Debug, Clone)]
|
|
pub struct PatternSearchAlgorithm {
|
|
/// Algorithm identifier
|
|
pub algorithm_id: String,
|
|
/// Search method
|
|
pub method: PatternSearchMethod,
|
|
/// Search accuracy
|
|
pub accuracy: f64,
|
|
/// Search speed
|
|
pub speed: f64,
|
|
}
|
|
|
|
/// Pattern search methods
|
|
#[derive(Debug, Clone)]
|
|
pub enum PatternSearchMethod {
|
|
ExactMatch,
|
|
FuzzyMatch,
|
|
SemanticSearch,
|
|
VectorSimilarity,
|
|
GraphMatching,
|
|
MachineLearning,
|
|
}
|
|
|
|
/// Pattern recognition model
|
|
#[derive(Debug, Clone)]
|
|
pub struct PatternRecognitionModel {
|
|
/// Model identifier
|
|
pub model_id: String,
|
|
/// Model architecture
|
|
pub architecture: ModelArchitecture,
|
|
/// Training configuration
|
|
pub training: TrainingConfiguration,
|
|
/// Performance metrics
|
|
pub performance: ModelPerformance,
|
|
}
|
|
|
|
/// Model architecture
|
|
#[derive(Debug, Clone)]
|
|
pub struct ModelArchitecture {
|
|
/// Architecture type
|
|
pub arch_type: ArchitectureType,
|
|
/// Layer configuration
|
|
pub layers: Vec<LayerConfiguration>,
|
|
/// Activation functions
|
|
pub activations: Vec<ActivationFunction>,
|
|
/// Regularization
|
|
pub regularization: RegularizationConfig,
|
|
}
|
|
|
|
/// Types of model architectures
|
|
#[derive(Debug, Clone)]
|
|
pub enum ArchitectureType {
|
|
FeedForward,
|
|
Convolutional,
|
|
Recurrent,
|
|
Transformer,
|
|
ResNet,
|
|
Attention,
|
|
}
|
|
|
|
/// Layer configuration
|
|
#[derive(Debug, Clone)]
|
|
pub struct LayerConfiguration {
|
|
/// Layer type
|
|
pub layer_type: LayerType,
|
|
/// Layer size
|
|
pub size: usize,
|
|
/// Activation function
|
|
pub activation: String,
|
|
/// Dropout rate
|
|
pub dropout: f64,
|
|
}
|
|
|
|
/// Types of neural layers
|
|
#[derive(Debug, Clone)]
|
|
pub enum LayerType {
|
|
Dense,
|
|
Convolutional,
|
|
Pooling,
|
|
Normalization,
|
|
Dropout,
|
|
Attention,
|
|
}
|
|
|
|
/// Activation functions
|
|
#[derive(Debug, Clone)]
|
|
pub enum ActivationFunction {
|
|
ReLU,
|
|
Sigmoid,
|
|
Tanh,
|
|
Softmax,
|
|
LeakyReLU,
|
|
ELU,
|
|
}
|
|
|
|
/// Regularization configuration
|
|
#[derive(Debug, Clone)]
|
|
pub struct RegularizationConfig {
|
|
/// L1 regularization weight
|
|
pub l1_weight: f64,
|
|
/// L2 regularization weight
|
|
pub l2_weight: f64,
|
|
/// Dropout rate
|
|
pub dropout_rate: f64,
|
|
/// Batch normalization
|
|
pub batch_norm: bool,
|
|
}
|
|
|
|
/// Training configuration
|
|
#[derive(Debug, Clone)]
|
|
pub struct TrainingConfiguration {
|
|
/// Learning rate
|
|
pub learning_rate: f64,
|
|
/// Batch size
|
|
pub batch_size: usize,
|
|
/// Number of epochs
|
|
pub epochs: u32,
|
|
/// Optimizer type
|
|
pub optimizer: OptimizerType,
|
|
/// Loss function
|
|
pub loss_function: LossFunction,
|
|
}
|
|
|
|
/// Types of optimizers
|
|
#[derive(Debug, Clone)]
|
|
pub enum OptimizerType {
|
|
SGD,
|
|
Adam,
|
|
AdamW,
|
|
RMSprop,
|
|
Adagrad,
|
|
}
|
|
|
|
/// Loss functions
|
|
#[derive(Debug, Clone)]
|
|
pub enum LossFunction {
|
|
MeanSquaredError,
|
|
CrossEntropy,
|
|
BinaryCrossEntropy,
|
|
MeanAbsoluteError,
|
|
Huber,
|
|
}
|
|
|
|
/// Model performance metrics
|
|
#[derive(Debug, Clone)]
|
|
pub struct ModelPerformance {
|
|
/// Training accuracy
|
|
pub training_accuracy: f64,
|
|
/// Validation accuracy
|
|
pub validation_accuracy: f64,
|
|
/// Test accuracy
|
|
pub test_accuracy: f64,
|
|
/// F1 score
|
|
pub f1_score: f64,
|
|
/// Precision
|
|
pub precision: f64,
|
|
/// Recall
|
|
pub recall: f64,
|
|
}
|
|
|
|
// Implementation
|
|
impl ErrorSyndromeDetector {
|
|
pub async fn new(_config: &ErrorCorrectionConfig) -> AiContextResult<Self> {
|
|
Ok(Self {
|
|
algorithms: vec![],
|
|
syndrome_db: Arc::new(RwLock::new(SyndromeDatabase {
|
|
syndromes: HashMap::new(),
|
|
patterns: vec![],
|
|
statistics: SyndromeStatistics {
|
|
total_syndromes: 0,
|
|
unique_patterns: 0,
|
|
avg_detection_time: Duration::from_millis(1),
|
|
accuracy: 0.95,
|
|
false_positive_rate: 0.01,
|
|
},
|
|
})),
|
|
realtime_detector: Arc::new(RealtimeSyndromeDetector::new()),
|
|
pattern_recognizer: Arc::new(SyndromePatternRecognizer::new()),
|
|
})
|
|
}
|
|
|
|
pub async fn detect_syndromes(
|
|
&self,
|
|
_code: &str,
|
|
potential_errors: &[String],
|
|
) -> AiContextResult<Vec<ErrorSyndrome>> {
|
|
let mut syndromes = Vec::new();
|
|
|
|
for (i, error) in potential_errors.iter().enumerate() {
|
|
syndromes.push(ErrorSyndrome {
|
|
syndrome_id: format!("syndrome_{}", i),
|
|
detected_at: crate::temporal::TemporalTimestamp::now(),
|
|
pattern: SyndromePattern {
|
|
bits: vec![1, 0, 1, 0], // Simplified pattern
|
|
weight: 2,
|
|
parity: 0,
|
|
stabilizer_outcomes: vec![],
|
|
},
|
|
error_type: QuantumErrorType::BitFlipError,
|
|
location: ErrorLocation {
|
|
physical_qubits: vec![i],
|
|
logical_qubit: Some(0),
|
|
syndrome: vec![1, 0],
|
|
probability: 0.8,
|
|
confidence: 0.9,
|
|
},
|
|
confidence: 0.9,
|
|
correction: CorrectionRecommendation {
|
|
correction: CorrectionOperation {
|
|
operation_type: CorrectionType::PauliX,
|
|
target_qubits: vec![i],
|
|
parameters: HashMap::new(),
|
|
effectiveness: 0.95,
|
|
},
|
|
success_probability: 0.95,
|
|
alternatives: vec![],
|
|
cost: 0.1,
|
|
},
|
|
});
|
|
}
|
|
|
|
Ok(syndromes)
|
|
}
|
|
}
|
|
|
|
impl RealtimeSyndromeDetector {
|
|
pub fn new() -> Self {
|
|
Self {
|
|
pipeline: Arc::new(DetectionPipeline {
|
|
stages: vec![],
|
|
throughput: 1000.0,
|
|
latency: Duration::from_micros(100),
|
|
}),
|
|
processor: Arc::new(StreamingSyndromeProcessor::new()),
|
|
alert_system: Arc::new(SyndromeAlertSystem::new()),
|
|
}
|
|
}
|
|
}
|
|
|
|
impl StreamingSyndromeProcessor {
|
|
pub fn new() -> Self {
|
|
Self {
|
|
buffers: vec![],
|
|
multiplexer: Arc::new(StreamMultiplexer {
|
|
streams: vec![],
|
|
strategy: MultiplexingStrategy::Priority,
|
|
load_balancing: true,
|
|
}),
|
|
dispatcher: Arc::new(OutputDispatcher::new()),
|
|
}
|
|
}
|
|
}
|
|
|
|
impl OutputDispatcher {
|
|
pub fn new() -> Self {
|
|
Self {
|
|
rules: vec![],
|
|
channels: HashMap::new(),
|
|
}
|
|
}
|
|
}
|
|
|
|
impl SyndromeAlertSystem {
|
|
pub fn new() -> Self {
|
|
Self {
|
|
rules: vec![],
|
|
active_alerts: Arc::new(RwLock::new(Vec::new())),
|
|
escalation: vec![],
|
|
}
|
|
}
|
|
}
|
|
|
|
impl SyndromePatternRecognizer {
|
|
pub fn new() -> Self {
|
|
Self {
|
|
algorithms: vec![],
|
|
library: Arc::new(PatternLibrary {
|
|
patterns: HashMap::new(),
|
|
hierarchies: vec![],
|
|
index: PatternSearchIndex {
|
|
entries: vec![],
|
|
algorithms: vec![],
|
|
},
|
|
}),
|
|
ml_models: vec![],
|
|
}
|
|
}
|
|
}
|
|
|
|
#[cfg(test)]
|
|
mod tests {
|
|
use super::*;
|
|
|
|
#[test]
|
|
fn test_error_syndrome_creation() {
|
|
let syndrome = ErrorSyndrome {
|
|
syndrome_id: "test_syndrome".to_string(),
|
|
detected_at: crate::temporal::TemporalTimestamp::now(),
|
|
pattern: SyndromePattern {
|
|
bits: vec![1, 0, 1, 1],
|
|
weight: 3,
|
|
parity: 1,
|
|
stabilizer_outcomes: vec![
|
|
StabilizerOutcome {
|
|
stabilizer_id: "X_stabilizer".to_string(),
|
|
measurement: 1,
|
|
confidence: 0.95,
|
|
qubits: vec![0, 1],
|
|
}
|
|
],
|
|
},
|
|
error_type: QuantumErrorType::BitFlipError,
|
|
location: ErrorLocation {
|
|
physical_qubits: vec![0, 1],
|
|
logical_qubit: Some(0),
|
|
syndrome: vec![1, 0, 1],
|
|
probability: 0.85,
|
|
confidence: 0.9,
|
|
},
|
|
confidence: 0.9,
|
|
correction: CorrectionRecommendation {
|
|
correction: CorrectionOperation {
|
|
operation_type: CorrectionType::PauliX,
|
|
target_qubits: vec![0],
|
|
parameters: HashMap::new(),
|
|
effectiveness: 0.98,
|
|
},
|
|
success_probability: 0.98,
|
|
alternatives: vec![],
|
|
cost: 0.05,
|
|
},
|
|
};
|
|
|
|
assert_eq!(syndrome.syndrome_id, "test_syndrome");
|
|
assert!(matches!(syndrome.error_type, QuantumErrorType::BitFlipError));
|
|
assert_eq!(syndrome.pattern.weight, 3);
|
|
assert_eq!(syndrome.location.physical_qubits.len(), 2);
|
|
assert!(matches!(syndrome.correction.correction.operation_type, CorrectionType::PauliX));
|
|
}
|
|
|
|
#[test]
|
|
fn test_syndrome_pattern() {
|
|
let pattern = SyndromePattern {
|
|
bits: vec![1, 1, 0, 1, 0],
|
|
weight: 3,
|
|
parity: 1,
|
|
stabilizer_outcomes: vec![],
|
|
};
|
|
|
|
assert_eq!(pattern.bits.len(), 5);
|
|
assert_eq!(pattern.weight, 3);
|
|
assert_eq!(pattern.parity, 1);
|
|
assert_eq!(pattern.stabilizer_outcomes.len(), 0);
|
|
}
|
|
|
|
#[test]
|
|
fn test_stabilizer_outcome() {
|
|
let outcome = StabilizerOutcome {
|
|
stabilizer_id: "Z_stabilizer_test".to_string(),
|
|
measurement: 0,
|
|
confidence: 0.87,
|
|
qubits: vec![1, 2, 3],
|
|
};
|
|
|
|
assert_eq!(outcome.stabilizer_id, "Z_stabilizer_test");
|
|
assert_eq!(outcome.measurement, 0);
|
|
assert_eq!(outcome.confidence, 0.87);
|
|
assert_eq!(outcome.qubits, vec![1, 2, 3]);
|
|
}
|
|
|
|
#[test]
|
|
fn test_quantum_parity_check() {
|
|
let parity_check = QuantumParityCheck {
|
|
check_id: "surface_code_check".to_string(),
|
|
check_matrix: ParityCheckMatrix {
|
|
dimensions: (4, 9),
|
|
elements: vec![
|
|
vec![1, 1, 0, 1, 1, 0, 0, 0, 0],
|
|
vec![0, 1, 1, 0, 1, 1, 0, 0, 0],
|
|
vec![0, 0, 0, 1, 1, 0, 1, 1, 0],
|
|
vec![0, 0, 0, 0, 1, 1, 0, 1, 1],
|
|
],
|
|
rank: 4,
|
|
null_space_dim: 1,
|
|
},
|
|
check_qubits: vec![0, 1, 2, 3],
|
|
data_qubits: vec![4, 5, 6, 7, 8],
|
|
frequency: 1000.0,
|
|
efficiency: 0.95,
|
|
};
|
|
|
|
assert_eq!(parity_check.check_id, "surface_code_check");
|
|
assert_eq!(parity_check.check_matrix.dimensions, (4, 9));
|
|
assert_eq!(parity_check.check_qubits.len(), 4);
|
|
assert_eq!(parity_check.data_qubits.len(), 5);
|
|
assert_eq!(parity_check.frequency, 1000.0);
|
|
assert_eq!(parity_check.efficiency, 0.95);
|
|
}
|
|
|
|
#[test]
|
|
fn test_syndrome_signature() {
|
|
let signature = SyndromeSignature {
|
|
bits: vec![1, 0, 1, 1, 0, 0, 1],
|
|
hash: 0xABCDEF123456789,
|
|
confidence: 0.92,
|
|
};
|
|
|
|
assert_eq!(signature.bits.len(), 7);
|
|
assert_eq!(signature.hash, 0xABCDEF123456789);
|
|
assert_eq!(signature.confidence, 0.92);
|
|
}
|
|
|
|
#[test]
|
|
fn test_detection_algorithm() {
|
|
let algorithm = SyndromeDetectionAlgorithm {
|
|
algorithm_id: "parity_check_detection".to_string(),
|
|
method: DetectionMethod::ParityCheck,
|
|
accuracy: 0.99,
|
|
latency: Duration::from_micros(50),
|
|
resources: DetectionResources {
|
|
shots: 1000,
|
|
classical_compute: 5.0,
|
|
circuit_depth: 3,
|
|
measurement_time: Duration::from_micros(10),
|
|
},
|
|
};
|
|
|
|
assert_eq!(algorithm.algorithm_id, "parity_check_detection");
|
|
assert!(matches!(algorithm.method, DetectionMethod::ParityCheck));
|
|
assert_eq!(algorithm.accuracy, 0.99);
|
|
assert_eq!(algorithm.resources.shots, 1000);
|
|
assert_eq!(algorithm.resources.circuit_depth, 3);
|
|
}
|
|
|
|
#[test]
|
|
fn test_temporal_correlation() {
|
|
let correlation = TemporalCorrelation {
|
|
lag: Duration::from_millis(5),
|
|
strength: 0.75,
|
|
correlation_type: CorrelationType::AutoCorrelation,
|
|
};
|
|
|
|
assert_eq!(correlation.lag, Duration::from_millis(5));
|
|
assert_eq!(correlation.strength, 0.75);
|
|
assert!(matches!(correlation.correlation_type, CorrelationType::AutoCorrelation));
|
|
}
|
|
|
|
#[test]
|
|
fn test_spatial_structure() {
|
|
let layout = GeometricLayout {
|
|
layout_type: LayoutType::Square,
|
|
dimensions: vec![7, 7],
|
|
boundaries: BoundaryConditions {
|
|
boundary_type: BoundaryType::Open,
|
|
periodic: vec![false, false],
|
|
effects: vec![],
|
|
},
|
|
};
|
|
|
|
assert!(matches!(layout.layout_type, LayoutType::Square));
|
|
assert_eq!(layout.dimensions, vec![7, 7]);
|
|
assert!(matches!(layout.boundaries.boundary_type, BoundaryType::Open));
|
|
}
|
|
|
|
#[test]
|
|
fn test_syndrome_alert() {
|
|
let alert = SyndromeAlert {
|
|
alert_id: "critical_error_001".to_string(),
|
|
timestamp: crate::temporal::TemporalTimestamp::now(),
|
|
severity: AlertSeverity::Critical,
|
|
message: "High error rate detected".to_string(),
|
|
syndrome: "syndrome_xyz".to_string(),
|
|
response_status: ResponseStatus::Pending,
|
|
};
|
|
|
|
assert_eq!(alert.alert_id, "critical_error_001");
|
|
assert!(matches!(alert.severity, AlertSeverity::Critical));
|
|
assert_eq!(alert.message, "High error rate detected");
|
|
assert!(matches!(alert.response_status, ResponseStatus::Pending));
|
|
}
|
|
|
|
#[test]
|
|
fn test_pattern_recognition_model() {
|
|
let model = PatternRecognitionModel {
|
|
model_id: "cnn_syndrome_classifier".to_string(),
|
|
architecture: ModelArchitecture {
|
|
arch_type: ArchitectureType::Convolutional,
|
|
layers: vec![
|
|
LayerConfiguration {
|
|
layer_type: LayerType::Convolutional,
|
|
size: 32,
|
|
activation: "relu".to_string(),
|
|
dropout: 0.1,
|
|
}
|
|
],
|
|
activations: vec![ActivationFunction::ReLU],
|
|
regularization: RegularizationConfig {
|
|
l1_weight: 0.01,
|
|
l2_weight: 0.001,
|
|
dropout_rate: 0.2,
|
|
batch_norm: true,
|
|
},
|
|
},
|
|
training: TrainingConfiguration {
|
|
learning_rate: 0.001,
|
|
batch_size: 32,
|
|
epochs: 100,
|
|
optimizer: OptimizerType::Adam,
|
|
loss_function: LossFunction::CrossEntropy,
|
|
},
|
|
performance: ModelPerformance {
|
|
training_accuracy: 0.95,
|
|
validation_accuracy: 0.92,
|
|
test_accuracy: 0.91,
|
|
f1_score: 0.90,
|
|
precision: 0.89,
|
|
recall: 0.91,
|
|
},
|
|
};
|
|
|
|
assert_eq!(model.model_id, "cnn_syndrome_classifier");
|
|
assert!(matches!(model.architecture.arch_type, ArchitectureType::Convolutional));
|
|
assert_eq!(model.training.learning_rate, 0.001);
|
|
assert_eq!(model.performance.test_accuracy, 0.91);
|
|
}
|
|
|
|
#[tokio::test]
|
|
async fn test_syndrome_detector_creation() {
|
|
let config = ErrorCorrectionConfig::default();
|
|
let detector = ErrorSyndromeDetector::new(&config).await;
|
|
|
|
assert!(detector.is_ok());
|
|
let detector = detector.unwrap();
|
|
assert_eq!(detector.algorithms.len(), 0); // Initially empty
|
|
}
|
|
|
|
#[tokio::test]
|
|
async fn test_syndrome_detection() {
|
|
let config = ErrorCorrectionConfig::default();
|
|
let detector = ErrorSyndromeDetector::new(&config).await.unwrap();
|
|
|
|
let code = "fn test() { vec![].get(0).unwrap(); }";
|
|
let errors = vec!["Potential panic".to_string(), "Out of bounds".to_string()];
|
|
|
|
let syndromes = detector.detect_syndromes(code, &errors).await;
|
|
assert!(syndromes.is_ok());
|
|
|
|
let syndromes = syndromes.unwrap();
|
|
assert_eq!(syndromes.len(), 2);
|
|
assert_eq!(syndromes[0].syndrome_id, "syndrome_0");
|
|
assert_eq!(syndromes[1].syndrome_id, "syndrome_1");
|
|
}
|
|
} |