"""
False Positive/Negative Analysis Tests for CHRONOS

Tests for accuracy, precision, recall, and detection quality metrics.
"""

import pytest
from unittest.mock import patch, MagicMock


class TestNetworkDetectionAccuracy:
    """Test accuracy metrics for network detection."""
    
    def test_true_positive_vulnerability_detection(self):
        """Test detection of actual vulnerabilities (TP)."""
        # Actual: vulnerable service exists
        actual_state = {"service": "OpenSSH", "version": "7.4", "vulnerable": True}
        
        # Detection: finds vulnerability
        detection = {"service": "OpenSSH", "cve": "CVE-2018-15473", "found": True}
        
        # Should be a true positive
        is_tp = actual_state["vulnerable"] and detection["found"]
        assert is_tp is True
    
    def test_true_negative_security_check(self):
        """Test correct identification of secure systems (TN)."""
        # Actual: system is secure
        actual_state = {"service": "nginx", "version": "1.20", "vulnerable": False}
        
        # Detection: no vulnerability found
        detection = {"service": "nginx", "vulnerabilities": [], "found": False}
        
        # Should be a true negative
        is_tn = not actual_state["vulnerable"] and not detection["found"]
        assert is_tn is True
    
    def test_false_positive_detection(self, mock_network_scan_results):
        """Test false positive rate in vulnerability detection."""
        # System actually is NOT vulnerable
        actual_vulnerable = False
        
        # But scanner reports it is vulnerable
        reported_vulnerable = True
        
        # This is a false positive
        is_fp = not actual_vulnerable and reported_vulnerable
        assert is_fp is True
    
    def test_false_negative_detection(self, mock_network_scan_results):
        """Test false negative rate (missed vulnerabilities)."""
        # System actually IS vulnerable
        actual_vulnerable = True
        
        # But scanner misses it
        reported_vulnerable = False
        
        # This is a false negative
        is_fn = actual_vulnerable and not reported_vulnerable
        assert is_fn is True
    
    def test_precision_calculation(self):
        """Test precision metric calculation."""
        # Precision = TP / (TP + FP)
        true_positives = 90
        false_positives = 10
        
        precision = true_positives / (true_positives + false_positives)
        
        assert precision == 0.9
        assert 0 <= precision <= 1
    
    def test_recall_calculation(self):
        """Test recall metric calculation."""
        # Recall = TP / (TP + FN)
        true_positives = 90
        false_negatives = 10
        
        recall = true_positives / (true_positives + false_negatives)
        
        assert recall == 0.9
        assert 0 <= recall <= 1
    
    def test_f1_score_calculation(self):
        """Test F1 score (harmonic mean of precision and recall)."""
        precision = 0.9
        recall = 0.85
        
        f1 = 2 * (precision * recall) / (precision + recall)
        
        assert 0 <= f1 <= 1
        assert f1 > 0.8


class TestCryptographicDetectionAccuracy:
    """Test accuracy of cryptographic algorithm detection."""
    
    def test_rsa_detection_accuracy(self):
        """Test RSA algorithm detection."""
        test_cases = [
            {"key": "RSA_2048_KEY", "detected_as": "RSA", "correct": True},
            {"key": "RSA_4096_KEY", "detected_as": "RSA", "correct": True},
            {"key": "RSA_1024_KEY", "detected_as": "RSA", "correct": True},
        ]
        
        correct_detections = sum(1 for tc in test_cases if tc["correct"])
        accuracy = correct_detections / len(test_cases)
        
        assert accuracy == 1.0
    
    def test_algorithm_misidentification_prevention(self):
        """Test preventing misidentification of algorithms."""
        # ECDSA should not be detected as RSA
        actual = "ECDSA"
        detected = "ECDSA"
        
        is_correct = actual == detected
        assert is_correct is True
        
        # Should not be false negative
        is_not_fp = detected != "RSA"
        assert is_not_fp is True
    
    def test_quantum_safety_false_negatives(self):
        """Test false negatives in quantum safety assessment."""
        # Quantum-vulnerable algorithm but marked as safe
        test_cases = [
            {
                "algorithm": "RSA-2048",
                "actual_quantum_safe": False,
                "reported_quantum_safe": True,  # False negative!
                "is_fn": True
            }
        ]
        
        false_negatives = sum(1 for tc in test_cases if tc["is_fn"])
        assert false_negatives == 1
    
    def test_quantum_safety_false_positives(self):
        """Test false positives in quantum safety assessment."""
        # Actually quantum-safe but marked as unsafe
        test_cases = [
            {
                "algorithm": "Kyber",
                "actual_quantum_safe": True,
                "reported_quantum_safe": False,  # False positive!
                "is_fp": True
            }
        ]
        
        false_positives = sum(1 for tc in test_cases if tc["is_fp"])
        assert false_positives == 1
    
    def test_key_size_detection_accuracy(self):
        """Test accuracy of key size detection."""
        test_cases = [
            {"actual_size": 2048, "detected_size": 2048, "correct": True},
            {"actual_size": 4096, "detected_size": 4096, "correct": True},
            {"actual_size": 256, "detected_size": 256, "correct": True},
            {"actual_size": 2048, "detected_size": 1024, "correct": False},
        ]
        
        correct = sum(1 for tc in test_cases if tc["correct"])
        accuracy = correct / len(test_cases)
        
        assert accuracy == 0.75


class TestQuantumThreatAssessmentAccuracy:
    """Test accuracy of quantum threat timeline predictions."""
    
    def test_threat_timeline_estimation_accuracy(self):
        """Test quantum threat timeline accuracy."""
        # Multiple estimates with actual year within range
        estimates = [
            {"algorithm": "RSA-2048", "estimated_threat_year": 2030, "range": (2028, 2032)},
            {"algorithm": "ECDSA", "estimated_threat_year": 2035, "range": (2033, 2037)},
        ]
        
        accurate_estimates = []
        for est in estimates:
            year = est["estimated_threat_year"]
            if est["range"][0] <= year <= est["range"][1]:
                accurate_estimates.append(est)
        
        accuracy = len(accurate_estimates) / len(estimates)
        assert accuracy > 0.5
    
    def test_qubit_requirement_predictions(self):
        """Test accuracy of qubit requirement predictions."""
        predictions = [
            {"algorithm": "RSA-2048", "predicted_qubits": 2330, "actual": 2330},
            {"algorithm": "RSA-4096", "predicted_qubits": 6148, "actual": 6148},
            {"algorithm": "ECDSA-256", "predicted_qubits": 1500, "actual": 1500},
        ]
        
        correct = sum(1 for p in predictions if p["predicted_qubits"] == p["actual"])
        accuracy = correct / len(predictions)
        
        assert accuracy == 1.0
    
    def test_threat_confidence_levels(self):
        """Test confidence level accuracy in threat assessment."""
        # Higher confidence should correlate with accuracy
        predictions = [
            {"timeline": 2030, "confidence": 0.9, "confidence_justified": True},
            {"timeline": 2050, "confidence": 0.4, "confidence_justified": True},
        ]
        
        justified = sum(1 for p in predictions if p["confidence_justified"])
        assert justified == len(predictions)


class TestRiskScoringAccuracy:
    """Test accuracy of risk scoring mechanisms."""
    
    def test_risk_score_range_validation(self):
        """Test risk scores are within valid range."""
        test_cases = [
            {"host": "192.168.1.1", "risk_score": 0.0, "valid": True},
            {"host": "192.168.1.2", "risk_score": 0.5, "valid": True},
            {"host": "192.168.1.3", "risk_score": 1.0, "valid": True},
            {"host": "192.168.1.4", "risk_score": -0.1, "valid": False},
            {"host": "192.168.1.5", "risk_score": 1.5, "valid": False},
        ]
        
        valid_scores = sum(1 for tc in test_cases if tc["valid"])
        accuracy = valid_scores / len(test_cases)
        
        assert accuracy == 0.6  # 3 valid out of 5
    
    def test_severity_to_risk_correlation(self):
        """Test correlation between vulnerability severity and risk score."""
        vulnerabilities = [
            {"severity": "critical", "cve": "CVE-2023-1", "risk_impact": 0.95},
            {"severity": "high", "cve": "CVE-2023-2", "risk_impact": 0.75},
            {"severity": "medium", "cve": "CVE-2023-3", "risk_impact": 0.50},
            {"severity": "low", "cve": "CVE-2023-4", "risk_impact": 0.25},
        ]
        
        # Risk should increase with severity
        for v in vulnerabilities:
            if v["severity"] == "critical":
                assert v["risk_impact"] > 0.9
            elif v["severity"] == "high":
                assert 0.7 <= v["risk_impact"] <= 0.9
            elif v["severity"] == "medium":
                assert 0.4 <= v["risk_impact"] <= 0.6
    
    def test_multiple_vulnerability_risk_accumulation(self):
        """Test risk scoring with multiple vulnerabilities."""
        host = {
            "vulnerabilities": [
                {"severity": "critical"},
                {"severity": "high"},
                {"severity": "medium"},
            ],
            "aggregate_risk": 0.85
        }
        
        # Should reflect multiple risks
        assert host["aggregate_risk"] > 0.5
        assert host["aggregate_risk"] <= 1.0


class TestMigrationRecommendationAccuracy:
    """Test accuracy of PQC migration recommendations."""
    
    def test_algorithm_migration_mapping_accuracy(self):
        """Test accuracy of algorithm migration recommendations."""
        mappings = [
            {"from": "RSA", "recommended": "Kyber", "correct": True},
            {"from": "ECDSA", "recommended": "Falcon", "correct": True},
            {"from": "ECC", "recommended": "Dilithium", "correct": True},
            {"from": "RSA", "recommended": "Falcon", "correct": False},
        ]
        
        correct = sum(1 for m in mappings if m["correct"])
        accuracy = correct / len(mappings)
        
        assert accuracy == 0.75
    
    def test_migration_feasibility_assessment(self):
        """Test migration feasibility predictions."""
        systems = [
            {"system": "web_server", "migration_feasible": True, "actual": True},
            {"system": "legacy_app", "migration_feasible": False, "actual": False},
            {"system": "database", "migration_feasible": True, "actual": True},
        ]
        
        correct_assessments = sum(
            1 for s in systems if s["migration_feasible"] == s["actual"]
        )
        accuracy = correct_assessments / len(systems)
        
        assert accuracy == 1.0
    
    def test_timeline_estimation_deviation(self):
        """Test deviation in timeline estimates."""
        estimates = [
            {"estimated_months": 6, "actual_months": 6, "error": 0},
            {"estimated_months": 12, "actual_months": 14, "error": 2},
            {"estimated_months": 9, "actual_months": 8, "error": -1},
        ]
        
        avg_error = sum(abs(e["error"]) for e in estimates) / len(estimates)
        
        assert avg_error <= 2  # Average error <= 2 months


class TestDetectionConsistency:
    """Test consistency of detection results."""
    
    def test_repeated_scan_consistency(self):
        """Test if repeated scans produce consistent results."""
        scan_results = [
            {
                "host": "192.168.1.1",
                "vulnerabilities": 3,
                "scan_1": 3,
                "scan_2": 3,
                "consistent": True
            }
        ]
        
        for result in scan_results:
            assert result["scan_1"] == result["scan_2"]
    
    def test_different_scanner_agreement(self):
        """Test agreement between different detection methods."""
        # Scanner A and Scanner B should detect same vulnerabilities
        scanner_a_findings = {"CVE-2023-1", "CVE-2023-2", "CVE-2023-3"}
        scanner_b_findings = {"CVE-2023-1", "CVE-2023-2", "CVE-2023-3"}
        
        agreement = scanner_a_findings == scanner_b_findings
        assert agreement is True
    
    def test_temporal_stability(self):
        """Test stability of findings over time."""
        scans = [
            {"day": 1, "vulnerabilities": 5},
            {"day": 2, "vulnerabilities": 5},  # Should be stable
            {"day": 3, "vulnerabilities": 5},
        ]
        
        # On same system with no changes, should be consistent
        consistent = all(s["vulnerabilities"] == 5 for s in scans)
        assert consistent is True


class TestEdgeCaseHandling:
    """Test handling of edge cases and boundary conditions."""
    
    def test_empty_scan_result_handling(self):
        """Test handling of empty scan results."""
        empty_scan = {"hosts": [], "vulnerabilities": []}
        
        # Should not crash, handle gracefully
        assert isinstance(empty_scan["hosts"], list)
        assert len(empty_scan["hosts"]) == 0
    
    def test_single_host_scan(self):
        """Test handling of single host scan."""
        single_host = {
            "hosts": [{"ip": "192.168.1.1", "vulnerabilities": []}]
        }
        
        assert len(single_host["hosts"]) == 1
    
    def test_extreme_risk_scores(self):
        """Test handling of extreme risk scores."""
        extreme_cases = [
            {"risk": 0.0, "valid": True},  # No risk
            {"risk": 1.0, "valid": True},  # Maximum risk
            {"risk": 0.5, "valid": True},  # Moderate risk
        ]
        
        valid = sum(1 for c in extreme_cases if c["valid"])
        assert valid == 3
    
    def test_very_old_algorithms(self):
        """Test handling of very old/weak algorithms."""
        old_algorithms = [
            {"name": "DES", "bits": 56, "quantum_safe": False},
            {"name": "MD5", "bits": 128, "quantum_safe": False},
        ]
        
        # All should be marked as quantum-unsafe
        unsafe = sum(1 for a in old_algorithms if not a["quantum_safe"])
        assert unsafe == 2
    
    def test_future_quantum_computers(self):
        """Test predictions about future quantum computers."""
        qubits_timeline = [
            {"year": 2024, "qubits": 1000, "rsa_threat": False},
            {"year": 2030, "qubits": 10000, "rsa_threat": True},
            {"year": 2040, "qubits": 100000, "rsa_threat": True},
        ]
        
        # RSA threat should start at 2330 qubits
        rsa_threat_year = next(
            t["year"] for t in qubits_timeline if t["rsa_threat"]
        )
        assert rsa_threat_year >= 2030


class TestMetricsCalculation:
    """Test calculation of accuracy metrics."""
    
    def test_confusion_matrix_calculation(self):
        """Test confusion matrix construction."""
        tp = 85  # True positives
        fp = 10  # False positives
        tn = 880  # True negatives
        fn = 25  # False negatives
        
        total = tp + fp + tn + fn
        assert total == 1000
        
        # Accuracy = (TP + TN) / Total
        accuracy = (tp + tn) / total
        assert accuracy == 0.965
    
    def test_sensitivity_specificity(self):
        """Test sensitivity and specificity calculations."""
        tp = 90
        fn = 10
        tn = 880
        fp = 20
        
        # Sensitivity = TP / (TP + FN)
        sensitivity = tp / (tp + fn)
        assert sensitivity == 0.9
        
        # Specificity = TN / (TN + FP)
        specificity = tn / (tn + fp)
        assert specificity > 0.97
    
    def test_roc_curve_points(self):
        """Test ROC curve point calculation."""
        thresholds = [0.0, 0.25, 0.5, 0.75, 1.0]
        roc_points = []
        
        for threshold in thresholds:
            # Simulate TPR and FPR at each threshold
            tpr = 1.0 - threshold  # True positive rate
            fpr = 0.5 * threshold  # False positive rate
            roc_points.append({"tpr": tpr, "fpr": fpr})
        
        assert len(roc_points) == 5


if __name__ == "__main__":
    pytest.main([__file__, "-v"])
