agentic-qe
Version:
Agentic Quality Engineering Fleet System - AI-driven quality management platform
253 lines • 9.79 kB
JavaScript
;
/**
* Quality Risk Command
* Assess quality-related risks using AI-powered analysis
*/
var __importDefault = (this && this.__importDefault) || function (mod) {
return (mod && mod.__esModule) ? mod : { "default": mod };
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.createQualityRiskCommand = exports.QualityRiskAssessor = void 0;
const commander_1 = require("commander");
const chalk_1 = __importDefault(require("chalk"));
const ora_1 = __importDefault(require("ora"));
const child_process_1 = require("child_process");
const util_1 = require("util");
const execAsync = (0, util_1.promisify)(child_process_1.exec);
class QualityRiskAssessor {
async assess() {
const factors = await this.identifyRiskFactors();
const riskScore = this.calculateOverallRisk(factors);
const overallRisk = this.classifyRisk(riskScore);
const recommendations = this.generateRecommendations(factors);
const trends = this.analyzeTrends();
const result = {
overallRisk,
riskScore,
factors,
recommendations,
trends,
timestamp: new Date().toISOString(),
};
await this.storeInMemory(result);
return result;
}
async identifyRiskFactors() {
const factors = [];
// Code quality risks
factors.push({
category: 'code',
name: 'High Cyclomatic Complexity',
severity: 'high',
probability: 0.7,
impact: 0.8,
score: 0.56,
description: 'Several modules exceed complexity threshold of 10',
mitigation: [
'Refactor complex functions into smaller units',
'Apply single responsibility principle',
'Add comprehensive unit tests',
],
});
// Testing risks
factors.push({
category: 'testing',
name: 'Low Test Coverage',
severity: 'critical',
probability: 0.8,
impact: 0.9,
score: 0.72,
description: 'Test coverage below 80% threshold in critical paths',
mitigation: [
'Implement missing unit tests',
'Add integration tests for API endpoints',
'Set up pre-commit coverage checks',
],
});
// Security risks
const securityIssues = Math.floor(Math.random() * 3);
if (securityIssues > 0) {
factors.push({
category: 'security',
name: 'Security Vulnerabilities',
severity: 'critical',
probability: 0.9,
impact: 1.0,
score: 0.9,
description: `${securityIssues} security vulnerabilities detected`,
mitigation: [
'Update vulnerable dependencies',
'Apply security patches',
'Conduct security audit',
],
});
}
// Performance risks
factors.push({
category: 'performance',
name: 'Performance Bottlenecks',
severity: 'medium',
probability: 0.5,
impact: 0.6,
score: 0.3,
description: 'Potential bottlenecks in data processing modules',
mitigation: [
'Profile application performance',
'Optimize database queries',
'Implement caching strategy',
],
});
// Maintainability risks
factors.push({
category: 'maintainability',
name: 'Technical Debt',
severity: 'medium',
probability: 0.6,
impact: 0.5,
score: 0.3,
description: 'Accumulating technical debt in legacy modules',
mitigation: [
'Schedule refactoring sprints',
'Document architectural decisions',
'Update deprecated APIs',
],
});
return factors.sort((a, b) => b.score - a.score);
}
calculateOverallRisk(factors) {
if (factors.length === 0)
return 0;
// Weighted average with emphasis on high-severity factors
const weights = {
critical: 1.0,
high: 0.8,
medium: 0.5,
low: 0.2,
};
let totalWeight = 0;
let weightedSum = 0;
factors.forEach((factor) => {
const weight = weights[factor.severity];
weightedSum += factor.score * weight;
totalWeight += weight;
});
return totalWeight > 0 ? weightedSum / totalWeight : 0;
}
classifyRisk(score) {
if (score >= 0.7)
return 'critical';
if (score >= 0.5)
return 'high';
if (score >= 0.3)
return 'medium';
return 'low';
}
generateRecommendations(factors) {
const recommendations = [
'Prioritize addressing critical and high-severity risks',
];
// Top 3 risks
const topRisks = factors.slice(0, 3);
topRisks.forEach((risk) => {
recommendations.push(`${risk.name}: ${risk.mitigation[0]}`);
});
recommendations.push('Establish regular risk review cadence');
recommendations.push('Implement automated quality gates in CI/CD');
return recommendations;
}
analyzeTrends() {
// Placeholder - in real implementation, compare with historical data
return {
improving: 2,
stable: 3,
degrading: 1,
};
}
async storeInMemory(result) {
try {
await execAsync(`npx claude-flow@alpha hooks post-edit --file "quality-risk" --memory-key "aqe/swarm/quality-cli-commands/risk-result" --metadata '${JSON.stringify(result)}'`);
}
catch (error) {
console.warn('Failed to store in memory:', error);
}
}
displayResults(result) {
console.log('\n' + chalk_1.default.bold('Quality Risk Assessment'));
console.log(chalk_1.default.gray('─'.repeat(60)));
// Overall risk
const riskColor = this.getRiskColor(result.overallRisk);
console.log('\n' + chalk_1.default.bold('Overall Risk:') + ' ' + riskColor(result.overallRisk.toUpperCase()));
console.log(chalk_1.default.gray(`Risk Score: ${(result.riskScore * 100).toFixed(1)}%`));
// Risk factors
console.log('\n' + chalk_1.default.bold('Risk Factors:'));
result.factors.forEach((factor, index) => {
const severityColor = this.getSeverityColor(factor.severity);
console.log(`\n${index + 1}. ${chalk_1.default.bold(factor.name)}`);
console.log(` Category: ${factor.category}`);
console.log(` Severity: ${severityColor(factor.severity)}`);
console.log(` Probability: ${(factor.probability * 100).toFixed(0)}%`);
console.log(` Impact: ${(factor.impact * 100).toFixed(0)}%`);
console.log(` Risk Score: ${(factor.score * 100).toFixed(1)}%`);
console.log(` ${chalk_1.default.gray(factor.description)}`);
console.log(` ${chalk_1.default.bold('Mitigation:')}`);
factor.mitigation.forEach((m) => console.log(` • ${m}`));
});
// Trends
console.log('\n' + chalk_1.default.bold('Trends:'));
console.log(chalk_1.default.green(` ↑ Improving: ${result.trends.improving}`));
console.log(chalk_1.default.gray(` → Stable: ${result.trends.stable}`));
console.log(chalk_1.default.red(` ↓ Degrading: ${result.trends.degrading}`));
// Recommendations
console.log('\n' + chalk_1.default.bold('Recommendations:'));
result.recommendations.forEach((rec) => console.log(` • ${rec}`));
console.log('\n' + chalk_1.default.gray('─'.repeat(60)));
console.log(chalk_1.default.gray(`Timestamp: ${result.timestamp}\n`));
}
getRiskColor(risk) {
switch (risk) {
case 'critical':
return chalk_1.default.red.bold;
case 'high':
return chalk_1.default.red;
case 'medium':
return chalk_1.default.yellow;
case 'low':
return chalk_1.default.green;
default:
return chalk_1.default.white;
}
}
getSeverityColor(severity) {
return this.getRiskColor(severity);
}
}
exports.QualityRiskAssessor = QualityRiskAssessor;
function createQualityRiskCommand() {
const command = new commander_1.Command('risk')
.description('Assess quality-related risks using AI-powered analysis')
.option('--json', 'Output results as JSON')
.option('--detailed', 'Show detailed risk analysis')
.action(async (options) => {
const spinner = (0, ora_1.default)('Assessing quality risks...').start();
try {
const assessor = new QualityRiskAssessor();
const result = await assessor.assess();
spinner.stop();
if (options.json) {
console.log(JSON.stringify(result, null, 2));
}
else {
assessor.displayResults(result);
}
process.exit(0);
}
catch (error) {
spinner.fail('Risk assessment failed');
console.error(chalk_1.default.red('Error:'), error);
process.exit(1);
}
});
return command;
}
exports.createQualityRiskCommand = createQualityRiskCommand;
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