"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.confidenceCalibrator = exports.ConfidenceCalibrator = void 0;
const KNOWN_BUG_PATTERNS = [
    {
        pattern: /null.*pointer|NPE|null.*check/i,
        severity: 'critical',
        category: 'null-pointer'
    },
    {
        pattern: /sql.*injection|SELECT.*WHERE.*\+|query.*concat/i,
        severity: 'critical',
        category: 'sql-injection'
    },
    {
        pattern: /password|secret|api.*key.*=.*['"]|token.*=.*['"]/i,
        severity: 'critical',
        category: 'secret-exposure'
    },
    {
        pattern: /eval\(|new.*Function\(|innerHTML\s*=|document\.write/i,
        severity: 'critical',
        category: 'xss'
    },
    {
        pattern: /race.*condition|concurrent.*modif|deadlock|mutex/i,
        severity: 'major',
        category: 'concurrency'
    },
    {
        pattern: /memory.*leak|dispose\(|close\(|gc\./i,
        severity: 'major',
        category: 'resource-leak'
    },
    {
        pattern: /async.*without.*await|unhandled.*promise|catch.*without.*throw/i,
        severity: 'major',
        category: 'async-issues'
    },
    {
        pattern: /try.*without.*catch|catch.*empty|swallow.*exception/i,
        severity: 'minor',
        category: 'error-handling'
    },
    {
        pattern: /any.*type|cast.*any|as.*any/i,
        severity: 'info',
        category: 'type-safety'
    },
    {
        pattern: /console\.(log|debug|warn)/i,
        severity: 'info',
        category: 'logging'
    },
    {
        pattern: /TODO|FIXME|HACK|XXX|BUG:/i,
        severity: 'info',
        category: 'tech-debt'
    },
    {
        pattern: /division.*by.*zero|divide.*0|x\s*\/\s*0/i,
        severity: 'major',
        category: 'arithmetic'
    },
    {
        pattern: /off.*by.*one|index.*length|length.*-\s*1/i,
        severity: 'minor',
        category: 'logic-error'
    },
    {
        pattern: /useEffect.*missing.*dep|dependency.*array/i,
        severity: 'minor',
        category: 'react-hooks'
    },
    {
        pattern: /mutation.*props|props.*change|immutable/i,
        severity: 'minor',
        category: 'immutability'
    },
    {
        pattern: /hardcoded|hard.*coded/i,
        severity: 'minor',
        category: 'hardcoding'
    },
    {
        pattern: /circular.*depend|lazy.*load|circular/i,
        severity: 'major',
        category: 'architecture'
    },
    {
        pattern: /sql.*string|query.*build|string.*concat.*sql/i,
        severity: 'critical',
        category: 'sql-injection'
    },
    {
        pattern: /crypto.*md5|sha1.*encrypt|md5.*hash/i,
        severity: 'critical',
        category: 'crypto'
    },
    {
        pattern: /http.*not.*https|mixed.*content|insecure.*request/i,
        severity: 'major',
        category: 'security'
    },
    {
        pattern: /cookie.*without.*secure|secure.*flag.*false/i,
        severity: 'major',
        category: 'security'
    },
    {
        pattern: /sudo|chmod\s+777|root.*login/i,
        severity: 'critical',
        category: 'security'
    },
    {
        pattern: /catch.*(e|err).*{[\s]*}/i,
        severity: 'minor',
        category: 'error-handling'
    },
    {
        pattern: /setTimeout.*0|setImmediate/i,
        severity: 'info',
        category: 'timing'
    },
    {
        pattern: /double.*click|race.*click|multiple.*submit/i,
        severity: 'minor',
        category: 'ux'
    }
];
const POSITIVE_INDICATORS = [
    { indicator: 'suggestion', weight: 0.15 },
    { indicator: '```suggestion', weight: 0.2 },
    { indicator: 'fix:', weight: 0.1 },
    { indicator: 'fixed code', weight: 0.1 },
    { indicator: 'correct', weight: 0.05 },
    { indicator: 'instead of', weight: 0.05 },
    { indicator: 'should be', weight: 0.05 },
    { indicator: 'best practice', weight: 0.05 }
];
const NEGATIVE_INDICATORS = [
    { indicator: 'maybe', weight: -0.15 },
    { indicator: 'might', weight: -0.1 },
    { indicator: 'possibly', weight: -0.1 },
    { indicator: 'i think', weight: -0.2 },
    { indicator: 'unclear', weight: -0.1 },
    { indicator: '不确定', weight: -0.15 },
    { indicator: 'perhaps', weight: -0.1 },
    { indicator: 'could be', weight: -0.1 },
    { indicator: 'not sure', weight: -0.15 },
    { indicator: 'likely', weight: -0.05 }
];
class ConfidenceCalibrator {
    historicalAccuracies = new Map();
    feedbackHistory = [];
    persistPath = '/tmp/prix_feedback.json';
    feedbackTracker = null;
    constructor(feedbackTracker = null) {
        this.loadPersisted();
        if (feedbackTracker) {
            this.feedbackTracker = feedbackTracker;
        }
        else {
            try {
                const { FeedbackTracker } = require('./feedback-tracker');
                this.feedbackTracker = new FeedbackTracker();
            }
            catch (e) {
                // FeedbackTracker not available, continue without it
            }
        }
    }
    loadPersisted() {
        try {
            if (require('fs').existsSync(this.persistPath)) {
                const data = JSON.parse(require('fs').readFileSync(this.persistPath, 'utf8'));
                if (Array.isArray(data)) {
                    this.feedbackHistory = data.map((item) => ({
                        pattern: item.pattern || '',
                        helpful: item.helpful || false,
                        timestamp: item.timestamp || Date.now()
                    }));
                    this.rebuildHistoricalAccuracies();
                }
            }
        }
        catch (e) {
            // Start fresh if persistence fails
        }
    }
    persist() {
        try {
            require('fs').writeFileSync(this.persistPath, JSON.stringify(this.feedbackHistory.slice(-1000)));
        }
        catch (e) {
            // Persistence failure is non-fatal
        }
    }
    rebuildHistoricalAccuracies() {
        const patternMap = new Map();
        for (const entry of this.feedbackHistory) {
            const accuracies = patternMap.get(entry.pattern) || [];
            accuracies.push(entry.helpful ? 1 : 0);
            patternMap.set(entry.pattern, accuracies);
        }
        for (const [pattern, accuracies] of patternMap) {
            this.historicalAccuracies.set(pattern, accuracies);
        }
    }
    recordFeedback(pattern, helpful) {
        this.feedbackHistory.push({ pattern, helpful, timestamp: Date.now() });
        const accuracies = this.historicalAccuracies.get(pattern) || [];
        accuracies.push(helpful ? 1 : 0);
        this.historicalAccuracies.set(pattern, accuracies);
        this.persist();
    }
    calibrate(aiReportedConfidence, comment, contextTokens, maxContextTokens, severity, teamId, repoSlug, patternType, filename) {
        const factors = this.calculateFactors(comment, contextTokens, maxContextTokens, severity, teamId, repoSlug, patternType, filename);
        let score;
        if (aiReportedConfidence !== undefined) {
            const deBiased = this.removeLLMBias(aiReportedConfidence);
            score = this.combineWithFactors(deBiased, factors);
        }
        else {
            score = this.computeFromFactorsOnly(factors);
        }
        score = Math.max(0, Math.min(100, score));
        return {
            score: Math.round(score),
            factors,
            reasoning: this.generateReasoning(factors, score)
        };
    }
    calculateFactors(comment, contextTokens, maxContextTokens, severity, teamId, repoSlug, patternType, filename) {
        const patternMatchScore = this.calculatePatternMatch(comment);
        const contextRichness = Math.min(1, contextTokens / Math.max(1, maxContextTokens * 0.5));
        const historicalAccuracy = this.calculateHistoricalAccuracy(comment);
        const severityMatchesKnownBug = severity
            ? this.matchesKnownBugPattern(comment, severity)
            : this.matchesAnyKnownBugPattern(comment);
        const hasExplicitEvidence = this.hasExplicitEvidence(comment);
        const { teamAcceptanceRate, patternTypeAccuracy } = this.calculateTeamMetrics(teamId, repoSlug, patternType, filename);
        return {
            patternMatchScore,
            contextRichness,
            historicalAccuracy,
            severityMatchesKnownBug,
            hasExplicitEvidence,
            teamAcceptanceRate,
            patternTypeAccuracy
        };
    }
    calculateTeamMetrics(teamId, repoSlug, patternType, filename) {
        if (!this.feedbackTracker || !teamId || !repoSlug) {
            return { teamAcceptanceRate: 0.5, patternTypeAccuracy: 0.5 };
        }
        let teamAcceptanceRate = 0.5;
        let patternTypeAccuracy = 0.5;
        if (patternType && filename) {
            teamAcceptanceRate = this.feedbackTracker.getPatternAcceptanceRate(patternType, teamId, repoSlug);
            patternTypeAccuracy = this.feedbackTracker.getFilenameAcceptanceRate(filename, teamId, repoSlug);
        }
        return { teamAcceptanceRate, patternTypeAccuracy };
    }
    calculatePatternMatch(comment) {
        const lowerComment = comment.toLowerCase();
        let score = 0.5;
        for (const { indicator, weight } of POSITIVE_INDICATORS) {
            if (lowerComment.includes(indicator.toLowerCase())) {
                score += weight;
            }
        }
        for (const { indicator, weight } of NEGATIVE_INDICATORS) {
            if (lowerComment.includes(indicator.toLowerCase())) {
                score += weight;
            }
        }
        if (lowerComment.includes('why this matters')) {
            score += 0.1;
        }
        if (lowerComment.includes('production') ||
            lowerComment.includes('production environment')) {
            score += 0.05;
        }
        return Math.max(0, Math.min(1, score));
    }
    calculateHistoricalAccuracy(comment) {
        const lowerComment = comment.toLowerCase();
        for (const [pattern, accuracies] of this.historicalAccuracies) {
            if (lowerComment.includes(pattern.toLowerCase())) {
                const avg = accuracies.reduce((a, b) => a + b, 0) / accuracies.length;
                return avg;
            }
        }
        const relevantFeedback = this.feedbackHistory.filter(f => f.pattern
            .split(' ')
            .some(word => word.length > 4 && lowerComment.includes(word.toLowerCase())));
        if (relevantFeedback.length === 0) {
            return 0.5;
        }
        const accuracy = relevantFeedback.filter(f => f.helpful).length / relevantFeedback.length;
        return accuracy;
    }
    matchesKnownBugPattern(comment, severity) {
        const lowerComment = comment.toLowerCase();
        for (const { pattern, severity: patternSeverity } of KNOWN_BUG_PATTERNS) {
            if (pattern.test(lowerComment) && patternSeverity === severity) {
                return true;
            }
        }
        return false;
    }
    matchesAnyKnownBugPattern(comment) {
        const lowerComment = comment.toLowerCase();
        for (const { pattern } of KNOWN_BUG_PATTERNS) {
            if (pattern.test(lowerComment)) {
                return true;
            }
        }
        return false;
    }
    hasExplicitEvidence(comment) {
        const explicitPhrases = [
            'this will crash',
            'this causes',
            'this leads to',
            'results in',
            'fails when',
            'breaks when',
            'error when',
            'crash if',
            'exception if',
            'undefined behavior',
            'undefined is',
            'will throw',
            'will fail'
        ];
        const lowerComment = comment.toLowerCase();
        return explicitPhrases.some(phrase => lowerComment.includes(phrase));
    }
    removeLLMBias(reportedConfidence) {
        if (reportedConfidence >= 95) {
            return 75;
        }
        if (reportedConfidence >= 85) {
            return 70;
        }
        if (reportedConfidence >= 70) {
            return 62;
        }
        if (reportedConfidence >= 60) {
            return 55;
        }
        return reportedConfidence * 0.9;
    }
    combineWithFactors(baseScore, factors) {
        const weights = {
            base: 0.25,
            pattern: 0.2,
            context: 0.1,
            historical: 0.15,
            knownBug: 0.05,
            teamAcceptance: 0.15,
            patternAccuracy: 0.1
        };
        let score = baseScore * weights.base;
        score += factors.patternMatchScore * 100 * weights.pattern;
        score += factors.contextRichness * 100 * weights.context;
        score += factors.historicalAccuracy * 100 * weights.historical;
        if (factors.severityMatchesKnownBug) {
            score += 10 * weights.knownBug;
        }
        if (factors.hasExplicitEvidence) {
            score += 5;
        }
        score += factors.teamAcceptanceRate * 100 * weights.teamAcceptance;
        score += factors.patternTypeAccuracy * 100 * weights.patternAccuracy;
        return score;
    }
    computeFromFactorsOnly(factors) {
        const weights = {
            pattern: 0.3,
            context: 0.15,
            historical: 0.2,
            knownBug: 0.15,
            teamAcceptance: 0.12,
            patternAccuracy: 0.08
        };
        let score = 50;
        score += factors.patternMatchScore * 50 * weights.pattern;
        score += factors.contextRichness * 50 * weights.context;
        score += factors.historicalAccuracy * 50 * weights.historical;
        if (factors.severityMatchesKnownBug) {
            score += 10 * weights.knownBug;
        }
        if (factors.hasExplicitEvidence) {
            score += 5;
        }
        score += factors.teamAcceptanceRate * 50 * weights.teamAcceptance;
        score += factors.patternTypeAccuracy * 50 * weights.patternAccuracy;
        return score;
    }
    generateReasoning(factors, score) {
        const reasons = [];
        if (factors.patternMatchScore > 0.7) {
            reasons.push('strong pattern match');
        }
        else if (factors.patternMatchScore < 0.4) {
            reasons.push('weak pattern match');
        }
        if (factors.contextRichness > 0.8) {
            reasons.push('rich context');
        }
        else if (factors.contextRichness < 0.3) {
            reasons.push('limited context');
        }
        if (factors.historicalAccuracy > 0.7) {
            reasons.push('historically accurate');
        }
        else if (factors.historicalAccuracy < 0.4 &&
            factors.historicalAccuracy !== 0.5) {
            reasons.push('historically unreliable');
        }
        if (factors.severityMatchesKnownBug) {
            reasons.push('matches known bug pattern');
        }
        if (factors.hasExplicitEvidence) {
            reasons.push('has explicit evidence');
        }
        if (factors.teamAcceptanceRate > 0.6) {
            reasons.push('high team acceptance');
        }
        else if (factors.teamAcceptanceRate < 0.3 &&
            factors.teamAcceptanceRate !== 0.5) {
            reasons.push('low team acceptance');
        }
        if (factors.patternTypeAccuracy > 0.6) {
            reasons.push('matches accepted patterns');
        }
        return reasons.length > 0
            ? `Calibrated based on: ${reasons.join(', ')}`
            : 'Calibrated using default heuristics';
    }
}
exports.ConfidenceCalibrator = ConfidenceCalibrator;
exports.confidenceCalibrator = new ConfidenceCalibrator();
//# sourceMappingURL=confidence.js.map