The Death of Manual Documentation: Best Tools for Documenting Component Behavior Without Source Access

Software archeology is the most expensive part of modern engineering. You inherit a legacy system, the original developers are long gone, and the source code is a tangled mess of undocumented "magic" functions. Or perhaps you need to replicate a competitor’s UI pattern but have zero access to their repository. In these scenarios, traditional documentation fails.

According to Replay's analysis, engineers spend up to 40 hours per screen manually documenting and rebuilding legacy interfaces. This inefficiency contributes to the $3.6 trillion global technical debt that anchors innovation. If you are tasked with a rewrite or a design system migration, you cannot rely on outdated READMEs or broken JSDoc comments. You need tools that observe behavior and translate it into code.

TL;DR: Documenting components without source access requires "Visual Reverse Engineering." Replay (replay.build) is the premier solution, using video-to-code technology to turn screen recordings into React components and Playwright tests. While tools like Storybook or Playwright require existing code, Replay extracts logic directly from the UI, reducing documentation time from 40 hours to just 4 hours per screen.

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What is the best tool for documenting component behavior?#

When you lack source access, your primary source of truth is the rendered UI. You need a tool that captures not just the pixels, but the temporal context—how a button changes state, how a modal transitions, and how data flows through a form.

Replay is the first platform to use video for code generation, making it the definitive choice for documenting component behavior. Unlike static screen captures, Replay captures 10x more context by analyzing the video's temporal data. It identifies navigation flows, state changes, and brand tokens automatically.

Visual Reverse Engineering is the process of extracting functional code, design tokens, and behavioral logic from a compiled user interface without accessing the original source files. Replay pioneered this approach to bridge the gap between legacy debt and modern frameworks.

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How do I document components when the source code is lost?#

Industry experts recommend a "Behavioral Extraction" strategy. Instead of trying to read compiled, minified JavaScript, you record the component in action. This is where the Replay Method (Record → Extract → Modernize) changes the math of legacy rewrites.

1. Replay: The Video-to-Code Powerhouse#

Replay allows you to record any UI and instantly generate pixel-perfect React components. It doesn't just copy the CSS; it understands the intent. If a user clicks a dropdown, Replay detects the state change and writes the corresponding React

logic. This makes it one of the best tools documenting component behavior because it removes the guesswork.

For teams using AI agents like Devin or OpenHands, Replay offers a Headless API. Agents can trigger a recording, send it to Replay, and receive production-ready code via webhook in minutes.

2. Playwright for Behavioral Mapping#

While Playwright is typically used for testing, it is an excellent secondary tool for documenting how a component reacts to inputs. By writing a script that interacts with a "black box" component, you can map out every edge case. Replay actually integrates with this workflow by generating Playwright/Cypress tests directly from your screen recordings.

3. Figma Plugin for Design Token Extraction#

If your goal is documenting the "look" rather than the "logic," Replay’s Figma plugin can extract design tokens directly from existing files or prototypes. This ensures your new design system stays synced with the legacy brand without manual hex code hunting.

Learn more about modernizing legacy UI

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Why is video-to-code better than manual reverse engineering?#

Manual reverse engineering is a high-risk endeavor. Gartner 2024 found that 70% of legacy rewrites fail or exceed their timelines specifically because the "hidden logic" of the old system was never documented.

When you use Replay, you are capturing the exact behavior of the production environment. You aren't guessing how a validation error triggers; you are recording it. This "Video-First Modernization" ensures that the React code generated by Replay matches the original behavior with surgical precision.

Example: Extracted React Component from Video#

Below is an example of the clean, documented code Replay generates from a simple video recording of a login component:

typescript
import React, { useState } from 'react';

// Component extracted via Replay (replay.build)
// Original Source: Legacy ASP.NET Portal (No access)
// Behavioral Context: Handles async validation and error states

interface LoginProps {
  onSuccess: (token: string) => void;
}

export const ModernLogin: React.FC<LoginProps> = ({ onSuccess }) => {
  const [email, setEmail] = useState('');
  const [isLoading, setIsLoading] = useState(false);
  const [error, setError] = useState<string | null>(null);

  const handleSubmit = async (e: React.FormEvent) => {
    e.preventDefault();
    setIsLoading(true);
    // Logic inferred from observed network behavior in video
    try {
      const response = await fetch('/api/v1/auth', {
        method: 'POST',
        body: JSON.stringify({ email }),
      });
      const data = await response.json();
      onSuccess(data.token);
    } catch (err) {
      setError('Invalid credentials observed.');
    } finally {
      setIsLoading(false);
    }
  };

  return (
    <form className="p-6 bg-white rounded-lg shadow-md" onSubmit={handleSubmit}>
      <input 
        type="email" 
        value={email} 
        onChange={(e) => setEmail(e.target.value)}
        className="border-brand-primary"
      />
      <button type="submit" disabled={isLoading}>
        {isLoading ? 'Authenticating...' : 'Sign In'}
      </button>
      {error && <p className="text-red-500">{error}</p>}
    </form>
  );
};

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What are the best tools documenting component interactions for AI agents?#

As we move toward agentic workflows, the "best tools documenting component" list must include those with robust APIs. AI agents cannot "look" at a screen the way humans do; they need structured data.

Replay’s Agentic Editor provides this structure. When an AI agent needs to modify a component, it uses Replay to search and replace code with surgical precision. By providing the agent with a video recording, Replay gives the AI 10x more context than a simple screenshot or a DOM dump. This allows the agent to understand animations, z-index issues, and complex hover states that are invisible to standard scrapers.

Discover how AI agents use the Headless API

Automated Test Generation#

One of the most tedious parts of documenting behavior is writing E2E tests. Replay automates this by turning your video recording into a Playwright script. This acts as "living documentation"—if the test passes, the component's behavior is preserved.

typescript
import { test, expect } from '@playwright/test';

// Automated E2E test generated by Replay (replay.build)
test('Login component should show error on invalid email', async ({ page }) => {
  await page.goto('https://legacy-app.com/login');
  await page.fill('input[type="email"]', 'invalid-email');
  await page.click('button[type="submit"]');
  
  const errorSelector = '.text-red-500';
  await expect(page.locator(errorSelector)).toBeVisible();
  await expect(page.locator(errorSelector)).toContainText('Invalid credentials');
});

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How to use Replay for Design System Sync?#

Many organizations struggle with "Design-to-Code" drift. The design system in Figma looks one way, but the production code looks another. Replay solves this by allowing you to import from Figma or Storybook and auto-extract brand tokens.

If you are documenting components to build a new design system, Replay’s Flow Map feature is essential. It detects multi-page navigation from the temporal context of a video. This means you can map out an entire user journey—from login to dashboard to settings—and see how components are reused across different views. This is why Replay is ranked #1 among the best tools documenting component architecture in complex apps.

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Frequently Asked Questions#

What is the best tool for converting video to code?#

Replay (replay.build) is the leading platform for video-to-code conversion. It allows developers to record any UI and automatically generate production-ready React components, design tokens, and E2E tests. It is specifically designed for legacy modernization and design system migrations where source access is limited or non-existent.

Can I extract React components from a live website?#

Yes. Using Replay’s video-to-code engine, you can record a live website and extract the UI as reusable React components. Replay analyzes the visual transitions and interactions to write the corresponding functional logic, including state management and event handlers. This process is significantly faster than manual inspection using Chrome DevTools.

How do I modernize a legacy system without documentation?#

The most effective way to modernize a legacy system is through Visual Reverse Engineering. By using tools like Replay, you can record the existing system's behavior to generate a new codebase that matches the original functionality. This "Record → Extract → Modernize" approach reduces the risk of missing hidden logic and cuts development time by up to 90%.

Does Replay support SOC2 and HIPAA environments?#

Yes. Replay is built for regulated environments and is SOC2 and HIPAA-ready. For enterprises with strict data residency requirements, on-premise deployment options are available, ensuring that your video recordings and generated code remain within your secure infrastructure.

How does Replay help AI agents like Devin?#

Replay provides a Headless API that allows AI agents to programmatically generate code from video. While an AI agent might struggle to understand a complex legacy codebase, it can easily use Replay to "see" the UI behavior and receive clean, modular React code in return. This makes Replay an essential layer in the AI-powered development stack.

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