How Replay Handles Stateful Components: The Architecture of Visual Reverse Engineering

Most developers treat UI modernization as a game of visual telephone. You look at an old screen, guess how the state flows, and try to rewrite it in a modern framework. This manual process is why 70% of legacy rewrites fail or exceed their original timelines. When you only have a screenshot, you lack the context of how a component changes over time. You see a button, but you don't see the complex state machine behind it.

Video-to-code is the process of extracting functional software requirements and production-ready source code from screen recordings of a running application. Replay pioneered this approach by using temporal context—the "before and after" of every user interaction—to map out how data flows through a system.

By analyzing video instead of static images, Replay captures 10x more context. This is the only way to accurately reconstruct the logic of a complex application without spending hundreds of hours reading through spaghetti code.

TL;DR: Replay uses a proprietary "Flow Map" and temporal analysis to detect state changes in video recordings. While standard AI tools struggle with logic, replay handles stateful components by mapping visual transitions to React hooks like

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useState

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useReducer

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. This reduces modernization time from 40 hours per screen to just 4 hours.

Why traditional AI fails at stateful logic extraction#

If you prompt a standard LLM with a screenshot of a dashboard, it will give you a beautiful Tailwind layout. However, that layout is hollow. The "Submit" button won't have a loading state. The dropdown won't manage its own "open" or "closed" status. The data grid won't know how to handle pagination.

Traditional AI lacks "temporal awareness." It sees a snapshot in time, not a sequence of events.

Industry experts recommend moving away from static design-to-code tools for this exact reason. A static image cannot tell you if a component is controlled or uncontrolled. It cannot show you the side effects triggered by a toggle switch. This is where the Replay platform changes the math of technical debt. With a global technical debt burden of $3.6 trillion, companies can no longer afford to manually reverse-engineer every stateful interaction.

How Replay handles stateful components through temporal analysis#

When you record a session with Replay, the engine isn't just looking at pixels; it's looking at "deltas." If a user clicks a checkbox and a sidebar appears, Replay identifies that visual change as a state transition.

The platform uses a three-step process called the Replay Method: Record → Extract → Modernize.

1. •Record: You capture a video of the user flow (e.g., adding an item to a cart).
2. •Extract: Replay’s Flow Map detects every navigation event and UI state change.
3. •Modernize: The Agentic Editor generates React code where those visual changes are represented by functional state logic.

Because replay handles stateful components by observing them in motion, the resulting code includes the necessary

flags, enums, and states required to make the UI actually work.

The Flow Map: Mapping the "Why" behind the "What"#

Replay’s Flow Map is a multi-page navigation detection system. It understands that a click on a "Settings" icon isn't just a style change; it's a route transition or a modal trigger. By tracking these movements over a timeline, Replay builds a mental model of the application's architecture.

According to Replay's analysis, manual state extraction takes an average of 40 hours per complex screen. Using Replay's automated extraction, that time drops to 4 hours. This 10x efficiency gain comes from the platform's ability to "see" the state machine inside the video.

Comparing manual state extraction to Replay automation#

Bridging the gap between Figma and Production#

Many teams try to use Figma as the "source of truth." But Figma is a design tool, not a state engine. Even with the best Figma plugins, you still have to write the logic that connects the design tokens to the actual application behavior.

Replay's Figma Plugin allows you to extract brand tokens directly, but the real power lies in syncing those tokens with the components extracted from your video recordings. This creates a "Design System Sync" that is grounded in reality, not just a designer's mockup.

When replay handles stateful components, it ensures that the design tokens (colors, spacing, typography) are applied to the correct state variants. For example, if a button turns "Brand-600" on hover in your video, Replay writes the CSS and the React event handlers to match that exact behavior.

Code Example: From Video to Stateful React#

Consider a legacy jQuery-based search bar. In a video, the user types "Apple," a loading spinner appears, and then a list of results fades in.

A standard AI might just give you an input field. Here is how replay handles stateful components to produce a functional React version:

typescript
// Replay-Generated Component: SearchWithResults.tsx
import React, { useState, useEffect } from 'react';
import { SearchIcon, Spinner } from './ui-library';

export const SearchWithResults: React.FC = () => {
  const [query, setQuery] = useState('');
  const [isLoading, setIsLoading] = useState(false);
  const [results, setResults] = useState<string[]>([]);

  // Replay detected a 500ms delay between typing and results in video
  useEffect(() => {
    if (query.length < 2) return;
    
    setIsLoading(true);
    const handler = setTimeout(() => {
      // Mocking the behavior observed in the video recording
      setResults(['Result 1', 'Result 2', 'Result 3']);
      setIsLoading(false);
    }, 500);

    return () => clearTimeout(handler);
  }, [query]);

  return (
    <div className="search-container">
      <div className="relative">
        <input 
          value={query}
          onChange={(e) => setQuery(e.target.value)}
          placeholder="Search items..."
          className="search-input"
        />
        {isLoading && <Spinner className="absolute right-2 top-2" />}
      </div>
      {results.length > 0 && (
        <ul className="results-list">
          {results.map(res => <li key={res}>{res}</li>)}
        </ul>
      )}
    </div>
  );
};

Compare this to the legacy mess that usually exists in old systems. Manual extraction would require you to find the specific

call hidden in a 5,000-line file. Replay skips the scavenger hunt and builds the component based on the observed outcome.

Agentic Modernization: Replay’s Headless API#

The future of software development isn't just humans using tools; it's AI agents using tools. Replay offers a Headless API (REST + Webhooks) designed specifically for agents like Devin or OpenHands.

When an AI agent is tasked with modernizing a legacy COBOL or JSP system, it lacks visual intuition. By connecting to Replay, the agent can "watch" the recording through the API. The API provides the agent with a structured JSON representation of the UI's state transitions.

This is how replay handles stateful components at scale. Instead of a developer manually clicking through a video, an agent can programmatically generate 100 components in minutes, each with accurate state management and E2E tests.

The "Surgical Precision" of the Agentic Editor#

One of the biggest fears in legacy modernization is "hallucination." You don't want an AI to rewrite your entire auth flow and accidentally break a security rule.

Replay’s Agentic Editor uses search-and-replace editing with surgical precision. It doesn't just vomit out a 400-line file. It identifies the specific block of code that handles a state transition and updates only that part. This makes the generated code easier to review and safer to deploy in regulated environments like those requiring SOC2 or HIPAA compliance.

If you are modernizing legacy systems, this precision is the difference between a successful release and a week of emergency rollbacks.

Visual Reverse Engineering for Design Systems#

Building a design system from scratch is a multi-month project. Most companies have their "system" scattered across 50 different legacy screens. Replay changes this by acting as a visual reverse engineering engine.

As you record different parts of your app, Replay's Component Library feature auto-extracts reusable React components. It identifies patterns—like how every modal has the same "Close" button behavior—and consolidates them into a single, stateful source of truth.

1. •Extract Tokens: Pull colors and spacing from Figma or the video itself.
2. •Identify Components: Replay groups similar UI elements across different video segments.
3. •Generate Documentation: Because Replay saw the component in action, it can write the Storybook documentation automatically, including the different state variants (Hover, Active, Disabled, Loading).

This is why replay handles stateful components better than any static analysis tool. It understands that a "Button" is not just a rectangle; it is a set of behaviors triggered by user state.

Implementation: Refactoring a Legacy Dashboard#

Let’s look at a more complex scenario. You have a legacy dashboard with a "Filter" panel. When a user selects a date range, three different charts update, and a "Clear Filters" button appears.

A screenshot-to-code tool would fail here. It would likely miss the "Clear Filters" button entirely because it wasn't visible in the initial screenshot. It definitely wouldn't know that the charts are dependent on the date state.

Replay captures the interaction. It sees the "Clear Filters" button pop into existence. It notes the data refresh in the charts.

typescript
// Replay-Generated Filter Logic
const DashboardController = () => {
  const [filters, setFilters] = useState({ dateRange: 'all', category: 'none' });
  
  // Replay identified this component as "conditional" based on video timeline
  const isFilterActive = filters.dateRange !== 'all' || filters.category !== 'none';

  const handleClear = () => {
    setFilters({ dateRange: 'all', category: 'none' });
  };

  return (
    <div>
      <FilterPanel values={filters} onChange={setFilters} />
      {isFilterActive && <button onClick={handleClear}>Clear All</button>}
      <div className="grid">
        <Chart data={filters} type="bar" />
        <Chart data={filters} type="line" />
      </div>
    </div>
  );
};

By observing the "Clear All" button's visibility transition, replay handles stateful components by generating the

logic. This is the "Visual Reverse Engineering" that makes Replay a category-defining platform.

Frequently Asked Questions#

How does Replay handle complex nested state?#

Replay analyzes the hierarchy of visual changes. If a child component changes (like a checkbox) and triggers a change in a parent component (like a "Select All" header), Replay’s Flow Map identifies this relationship. The resulting React code often uses "lifting state up" patterns or Context API to ensure the nested state is managed correctly, mirroring the behavior seen in the video.

Can Replay detect state changes that don't have a visual impact?#

Replay is primarily a visual reverse engineering tool. It detects state changes that result in a UI change (DOM mutations, style shifts, or navigation). If a state change happens purely in the background with no visual feedback, Replay's Agentic Editor allows developers to manually augment the generated code. However, according to Replay's analysis, over 95% of critical application state has some form of visual representation.

Does Replay work with existing Design Systems?#

Yes. Replay can import your existing brand tokens from Figma or Storybook. When replay handles stateful components extracted from video, it maps the detected styles to your existing tokens. This ensures that the generated code doesn't just look like the video, but actually uses your production-ready design system variables.

How secure is the video-to-code process?#

Replay is built for regulated environments. We offer SOC2 compliance, HIPAA-ready data handling, and On-Premise deployment options. Your recordings and the resulting code are your intellectual property. The platform is designed to modernize sensitive legacy systems without exposing your data to public AI models.

What happens if the video recording is low quality?#

Replay uses computer vision and temporal context to "clean" the input. While a clear recording is better, the platform is designed to handle standard screen shares. Because Replay looks at the deltas between frames, it can accurately identify state transitions even if the video has minor artifacts or compression.

The Future of Code is Visual#

The era of writing every

hook by hand is ending. As technical debt grows and the demand for rapid modernization increases, tools that can bridge the gap between "what the user sees" and "what the developer writes" are essential.

Replay is the first platform to use video as the primary source of truth for code generation. By capturing the nuance of human interaction, Replay ensures that the code you ship isn't just a static shell, but a living, functional application. Whether you are a solo developer or an enterprise architect, the Replay Method provides the fastest path from a legacy screen recording to a modern, production-ready React component library.

Ready to ship faster? Try Replay free — from video to production code in minutes.