web-perf-mcp/dist/runner/analyzer.d.ts

MCP Server that audits the web page for finding the bottlenecks and CPU profiling using Lighthouse and Puppeteer

import type { CPUProfile, CPUProfileAnalysis, PerformanceMetrics } from './types';
import { SourceMapResolver } from './resolver.js';
declare class CPUProfileAnalyzer {
    sourceMapResolver: SourceMapResolver;
    private nodeById;
    private analysisResults;
    analyzeCPUProfile(cpuProfilePath: string, traceEventsPath: string): Promise<CPUProfileAnalysis>;
    loadAuditReport(reportPath: string): Promise<PerformanceMetrics>;
    analyzeAuditReport(reportPath: string): Promise<PerformanceMetrics>;
    analyzeCPUProfileData(cpuProfile: CPUProfile): Promise<void>;
    private resolveSourceMapsForTopFunctions;
    processSamplesSpeedscope(samples: number[], timeDeltas: number[], startTime: number): {
        collapsedSamples: number[];
        sampleTimes: number[];
    };
    calculateTotalTimesSpeedscope(nodeById: Map<number, any>): void;
    shouldIgnoreFunction(callFrame: any): boolean;
    getDisplayName(callFrame: any): string;
    calculateTotalTimes(nodeMap: Map<number, any>, nodes: any[]): void;
    getSeverity(percentage: number): string;
    getFileNameFromUrl(url: string): string;
    generateFlamegraphData(): Promise<any>;
    private generateCallStackAnalysis;
    private identifyHotPaths;
    private buildFunctionHierarchy;
    private createVisualSummary;
    private findDeepestCallStacks;
    private findMostFrequentCallPaths;
    private buildCallPath;
    private findChildFunctions;
    private isLeafFunction;
    private analyzeExecutionPattern;
    generate(flamegraphData?: any): CPUProfileAnalysis;
}
export default CPUProfileAnalyzer;