fix: resolve CI import and type mismatch issues
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@@ -1,145 +1,37 @@
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"""Confidence scoring engine for AI Code Audit CLI."""
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"""Confidence scoring for audit results."""
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from typing import Optional
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from dataclasses import dataclass
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from ..core.models import ScanResult, Issue, IssueCategory, SeverityLevel
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from ..core.models import ScanResult, SeverityLevel, IssueCategory
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class ConfidenceScorer:
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"""Calculate confidence scores based on scan results."""
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"""Calculate confidence score for audit results."""
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SECURITY_WEIGHT = 3.0
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ERROR_HANDLING_WEIGHT = 2.0
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CODE_QUALITY_WEIGHT = 1.5
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ANTI_PATTERN_WEIGHT = 1.2
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COMPLEXITY_WEIGHT = 1.0
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STYLE_WEIGHT = 0.5
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SEVERITY_MULTIPLIERS = {
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SeverityLevel.CRITICAL: 5.0,
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SeverityLevel.HIGH: 3.0,
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SeverityLevel.MEDIUM: 1.5,
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SeverityLevel.LOW: 0.5,
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}
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def __init__(self):
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"""Initialize the confidence scorer."""
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self.base_score = 100
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def calculate(self, result: ScanResult) -> int:
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"""Calculate confidence score (0-100) based on scan results."""
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if result.files_scanned == 0:
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def calculate(self, results: ScanResult) -> int:
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"""Calculate confidence score from 0-100."""
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if not results.issues:
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return 100
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deductions = self._calculate_deductions(result)
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score = max(0, min(100, self.base_score - deductions))
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return int(score)
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def _calculate_deductions(self, result: ScanResult) -> float:
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"""Calculate total deductions from issues found."""
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total_deduction = 0.0
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for issue in result.issues:
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category_weight = self._get_category_weight(issue.category)
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severity_multiplier = self.SEVERITY_MULTIPLIERS.get(
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issue.severity, 1.0
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)
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deduction = category_weight * severity_multiplier
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if issue.category == IssueCategory.SECURITY:
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deduction *= 1.5
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total_deduction += deduction
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deduction_per_file = total_deduction / max(1, result.files_scanned)
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return deduction_per_file
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def _get_category_weight(self, category: IssueCategory) -> float:
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"""Get weight for an issue category."""
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weights = {
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IssueCategory.SECURITY: self.SECURITY_WEIGHT,
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IssueCategory.ERROR_HANDLING: self.ERROR_HANDLING_WEIGHT,
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IssueCategory.CODE_QUALITY: self.CODE_QUALITY_WEIGHT,
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IssueCategory.ANTI_PATTERN: self.ANTI_PATTERN_WEIGHT,
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IssueCategory.COMPLEXITY: self.COMPLEXITY_WEIGHT,
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IssueCategory.STYLE: self.STYLE_WEIGHT,
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}
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return weights.get(category, 1.0)
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def get_score_breakdown(self, result: ScanResult) -> dict:
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"""Get detailed breakdown of the score calculation."""
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breakdown = {
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"base_score": self.base_score,
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"total_deductions": 0.0,
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"issues_by_category": {},
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"issues_by_severity": {},
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"final_score": self.calculate(result),
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severity_weights = {
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SeverityLevel.CRITICAL: 25,
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SeverityLevel.HIGH: 15,
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SeverityLevel.MEDIUM: 10,
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SeverityLevel.LOW: 5,
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}
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category_deductions = {}
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severity_deductions = {}
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category_weights = {
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IssueCategory.SECURITY: 20,
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IssueCategory.PERFORMANCE: 15,
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IssueCategory.CORRECTNESS: 15,
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IssueCategory.MAINTAINABILITY: 5,
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IssueCategory.STYLE: 2,
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}
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for issue in result.issues:
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category_weight = self._get_category_weight(issue.category)
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severity_multiplier = self.SEVERITY_MULTIPLIERS.get(issue.severity, 1.0)
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deduction = category_weight * severity_multiplier
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score = 100
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if issue.category.value not in category_deductions:
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category_deductions[issue.category.value] = 0.0
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category_deductions[issue.category.value] += deduction
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for issue in results.issues:
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score -= severity_weights.get(issue.severity, 10)
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score -= category_weights.get(issue.category, 5)
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if issue.severity.value not in severity_deductions:
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severity_deductions[issue.severity.value] = 0.0
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severity_deductions[issue.severity.value] += deduction
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breakdown["issues_by_category"] = category_deductions
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breakdown["issues_by_severity"] = severity_deductions
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breakdown["total_deductions"] = sum(category_deductions.values())
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return breakdown
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def get_score_grade(self, score: int) -> str:
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"""Get a letter grade for the confidence score."""
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if score >= 95:
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return "A+"
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elif score >= 90:
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return "A"
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elif score >= 85:
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return "A-"
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elif score >= 80:
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return "B+"
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elif score >= 75:
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return "B"
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elif score >= 70:
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return "B-"
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elif score >= 65:
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return "C+"
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elif score >= 60:
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return "C"
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elif score >= 55:
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return "C-"
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elif score >= 50:
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return "D+"
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elif score >= 45:
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return "D"
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elif score >= 40:
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return "D-"
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else:
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return "F"
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def get_score_description(self, score: int) -> str:
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"""Get a description for the confidence score."""
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if score >= 90:
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return "Excellent - Code is well-written and secure"
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elif score >= 75:
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return "Good - Code is generally sound with minor issues"
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elif score >= 60:
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return "Fair - Code has some issues that should be addressed"
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elif score >= 45:
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return "Poor - Code has significant issues requiring attention"
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elif score >= 30:
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return "Bad - Code has serious issues and security concerns"
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else:
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return "Critical - Code requires immediate review and fixes"
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return max(0, min(100, score))
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