agentic-qe/dist/cli/index-spec.js

Agentic Quality Engineering Fleet System - AI-driven quality management platform

#!/usr/bin/env node
"use strict";
var __importDefault = (this && this.__importDefault) || function (mod) {
    return (mod && mod.__esModule) ? mod : { "default": mod };
};
Object.defineProperty(exports, "__esModule", { value: true });
const commander_1 = require("commander");
const chalk_1 = __importDefault(require("chalk"));
const init_1 = require("./commands/init");
const generate_1 = require("./commands/generate");
const run_1 = require("./commands/run");
const analyze_1 = require("./commands/analyze");
const fleet_1 = require("./commands/fleet");
const program = new commander_1.Command();
// CLI Header
console.log(chalk_1.default.blue.bold(`
┌─────────────────────────────────────────────────────────────┐
│                    Agentic QE Fleet                        │
│         AI-Driven Quality Engineering Platform             │
│                    Version 1.0.0                          │
└─────────────────────────────────────────────────────────────┘
`));
// Configure CLI
program
    .name('agentic-qe')
    .description('Agentic Quality Engineering Fleet System - AI-driven quality management platform')
    .version('1.0.0', '-v, --version', 'display version number')
    .helpOption('-h, --help', 'display help for command');
// Register commands
// Fleet Management Commands
program
    .command('init')
    .description('Initialize new QE fleet with specified topology')
    .option('-t, --topology <type>', 'Fleet topology: hierarchical, mesh, ring, adaptive', 'hierarchical')
    .option('-a, --max-agents <number>', 'Maximum number of agents (5-50)', '20')
    .option('-f, --focus <areas>', 'Testing focus areas (comma-separated)', 'unit,integration,e2e')
    .option('-e, --environments <envs>', 'Target environments (comma-separated)', 'development,staging')
    .option('-c, --config <path>', 'Configuration file path')
    .option('--frameworks <frameworks>', 'Testing frameworks (comma-separated)', 'jest,mocha,pytest')
    .action(init_1.InitCommand.execute);
// Test Generation Commands
program
    .command('generate')
    .description('Generate comprehensive test suites using AI analysis')
    .argument('[target]', 'Target type: tests, integration, performance, security', 'tests')
    .option('-t, --type <type>', 'Test type: unit, integration, e2e, performance, security', 'unit')
    .option('-c, --coverage-target <number>', 'Target coverage percentage', '85')
    .option('-p, --path <path>', 'Source code path to analyze', './src')
    .option('-o, --output <path>', 'Output directory for generated tests', './tests')
    .option('-f, --framework <framework>', 'Testing framework', 'jest')
    .option('--from-swagger <path>', 'Generate from OpenAPI/Swagger specification')
    .option('--property-based', 'Generate property-based tests')
    .option('--mutation-testing', 'Include mutation testing scenarios')
    .action(generate_1.GenerateCommand.execute);
// Test Execution Commands
program
    .command('run')
    .description('Execute test suites with parallel orchestration')
    .argument('[target]', 'Target: tests, suite, regression, performance', 'tests')
    .option('-p, --parallel', 'Enable parallel execution', false)
    .option('-e, --env <environment>', 'Target environment', 'development')
    .option('-s, --suite <name>', 'Specific test suite name')
    .option('-t, --timeout <seconds>', 'Test timeout in seconds', '300')
    .option('-r, --retry-flaky <count>', 'Retry count for flaky tests', '3')
    .option('-c, --concurrency <number>', 'Concurrent test processes', '4')
    .option('--reporter <type>', 'Test reporter: json, junit, html', 'json')
    .option('--coverage', 'Generate coverage report', false)
    .action(run_1.RunCommand.execute);
// Analysis Commands
program
    .command('analyze')
    .description('Analyze test results and quality metrics')
    .argument('[target]', 'Analysis target: coverage, quality, trends, gaps', 'coverage')
    .option('--gaps', 'Identify coverage gaps', false)
    .option('--recommendations', 'Generate improvement recommendations', false)
    .option('--metrics', 'Include detailed quality metrics', false)
    .option('--trends', 'Show quality trends over time', false)
    .option('-p, --period <timeframe>', 'Analysis time period', '30d')
    .option('-f, --format <type>', 'Output format: json, html, csv', 'json')
    .option('--threshold <number>', 'Quality threshold for alerts', '80')
    .action(analyze_1.AnalyzeCommand.execute);
// Fleet Status and Management
program
    .command('fleet')
    .description('Manage and monitor fleet operations')
    .argument('[action]', 'Fleet action: status, scale, deploy, destroy', 'status')
    .option('-v, --verbose', 'Verbose output', false)
    .option('-a, --agents <number>', 'Target agent count for scaling')
    .option('-e, --env <environment>', 'Environment for deployment', 'development')
    .option('-i, --interval <seconds>', 'Monitoring interval', '5')
    .option('--topology <type>', 'Fleet topology for scaling')
    .option('--health-check', 'Run comprehensive health check', false)
    .action(fleet_1.FleetCommand.execute);
// Advanced Intelligence Commands
program
    .command('predict')
    .description('Predict quality issues using AI models')
    .option('-m, --model <type>', 'Prediction model: neural, statistical, ensemble', 'neural')
    .option('-c, --confidence <threshold>', 'Confidence threshold (0-1)', '0.8')
    .option('-s, --scope <area>', 'Prediction scope: code, tests, deployment', 'code')
    .option('-h, --history <period>', 'Historical data period', '30d')
    .action(async (options) => {
    console.log(chalk_1.default.yellow('🔮 Quality Prediction Analysis'));
    console.log(chalk_1.default.gray(`Model: ${options.model}, Confidence: ${options.confidence}`));
    console.log(chalk_1.default.blue('⚠️  Feature available in future release'));
});
program
    .command('optimize')
    .description('Optimize test suites using mathematical algorithms')
    .option('-a, --algorithm <type>', 'Optimization algorithm: sublinear, genetic, greedy', 'sublinear')
    .option('-t, --target-time <duration>', 'Target execution time', '5m')
    .option('-c, --coverage-min <percentage>', 'Minimum coverage to maintain', '80')
    .action(async (options) => {
    console.log(chalk_1.default.yellow('⚡ Test Suite Optimization'));
    console.log(chalk_1.default.gray(`Algorithm: ${options.algorithm}, Target: ${options.targetTime}`));
    console.log(chalk_1.default.blue('⚠️  Feature available in future release'));
});
program
    .command('learn')
    .description('Learn patterns from historical data')
    .option('-h, --from-history <period>', 'Historical data period', '30d')
    .option('-p, --patterns <types>', 'Pattern types: defects, performance, flaky', 'defects')
    .action(async (options) => {
    console.log(chalk_1.default.yellow('🧠 Pattern Learning'));
    console.log(chalk_1.default.gray(`Period: ${options.fromHistory}, Patterns: ${options.patterns}`));
    console.log(chalk_1.default.blue('⚠️  Feature available in future release'));
});
// Error handling
program.exitOverride();
try {
    program.parse();
}
catch (err) {
    if (err.code === 'commander.help') {
        process.exit(0);
    }
    else if (err.code === 'commander.version') {
        process.exit(0);
    }
    else {
        console.error(chalk_1.default.red('❌ CLI Error:'), err.message);
        process.exit(1);
    }
}
// If no command provided, show help
if (!process.argv.slice(2).length) {
    program.outputHelp();
    console.log(chalk_1.default.yellow('\n💡 Quick Start:'));
    console.log(chalk_1.default.gray('  agentic-qe init --topology hierarchical'));
    console.log(chalk_1.default.gray('  agentic-qe generate tests --coverage-target 85'));
    console.log(chalk_1.default.gray('  agentic-qe run tests --parallel'));
    console.log(chalk_1.default.gray('  agentic-qe fleet status --verbose'));
}
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