How Replay Identifies Reusable UI Patterns Across Different App States

Legacy codebases are black boxes where UI patterns go to die. Most modernization projects fail because developers try to reconstruct complex application states from static screenshots or fragmented CSS files. This manual approach is why 70% of legacy rewrites fail or exceed their original timelines. You cannot build a modern design system by looking at a snapshot; you need to see how the interface breathes, moves, and reacts.

Visual Reverse Engineering is the methodology of extracting functional code and design tokens from the visual behavior of a running application. By recording a user session, Replay captures the temporal context of every UI element. This allows the platform to see not just what a button looks like, but how it behaves across every possible state—hover, active, disabled, or loading.

TL;DR: Manual UI extraction takes 40 hours per screen and often misses edge cases. Replay identifies reusable patterns by analyzing video recordings of your app, reducing development time to 4 hours per screen. It maps temporal data to React components, extracts design tokens, and provides a headless API for AI agents like Devin to generate production-ready code.

---

What is Video-to-Code?#

Video-to-code is the process of converting screen recordings into functional, documented React components and design systems. Unlike traditional "image-to-code" tools that guess at layout based on a single frame, video-to-code uses the entire timeline of a recording to understand hierarchy and logic.

According to Replay's analysis, video recordings capture 10x more context than static screenshots. When you record a flow, Replay identifies reusable patterns by observing how elements persist across different pages. If a navigation bar appears in five different videos, Replay recognizes it as a single global component rather than five separate UI fragments.

---

How Replay Identifies Reusable Patterns via Temporal Context#

The primary challenge in frontend engineering isn't writing the CSS; it's identifying the abstractions. In a $3.6 trillion global technical debt environment, most of that debt is hidden in "snowflake" components—elements that look similar but were coded differently by different teams over a decade.

1. Multi-Page Navigation Detection#

Replay uses a feature called Flow Map to detect navigation patterns. As you record a user moving from a dashboard to a settings page, the platform tracks which elements remain static (like sidebars) and which are dynamic (like page content). This temporal context is how replay identifies reusable patterns that constitute your application's shell.

2. State Variance Mapping#

A static image cannot tell you if a button has a ripple effect or if a form field validates on blur. Replay analyzes every frame of the video. If a user clicks a "Submit" button and it transitions to a loading spinner, Replay understands that the

component has a state.

3. Design Token Extraction#

Manual token extraction from Figma or CSS is tedious. Replay’s Figma Plugin and video analysis engine work together to find the "source of truth." It identifies hex codes, spacing scales, and typography styles used consistently across the recording.

---

The Replay Method: Record → Extract → Modernize#

We recommend a three-step workflow to eliminate manual UI reconstruction. This method turns the traditional 40-hour-per-screen manual grind into a 4-hour automated sprint.

1. •Record: Capture a high-fidelity video of the legacy UI in action. Cover all states (empty states, error states, success states).
2. •Extract: Replay’s engine parses the video, identifying DOM-like structures and CSS patterns. It clusters similar-looking elements into single component definitions.
3. •Modernize: Use the Agentic Editor to refine the generated React code. Export the results to your Design System or sync them directly with Figma.

Comparison: Manual Extraction vs. Replay#

---

Technical Implementation: From Video to React#

When replay identifies reusable patterns, it generates clean, typed TypeScript code. It doesn't just output a "div soup." It creates modular components that follow modern best practices like Tailwind CSS or Styled Components.

Example: Extracted Button Component#

Here is an example of how Replay converts a recorded button interaction into a reusable React component with multiple states:

typescript
import React from 'react';

interface ReplayButtonProps {
  variant: 'primary' | 'secondary' | 'ghost';
  isLoading?: boolean;
  disabled?: boolean;
  children: React.ReactNode;
  onClick?: () => void;
}

/**
 * Extracted via Replay Visual Reverse Engineering
 * Source: Dashboard Recording - Frame 450-600
 */
export const Button: React.FC<ReplayButtonProps> = ({ 
  variant = 'primary', 
  isLoading, 
  disabled, 
  children, 
  onClick 
}) => {
  const baseStyles = "px-4 py-2 rounded-md transition-all duration-200 font-medium";
  const variants = {
    primary: "bg-blue-600 text-white hover:bg-blue-700 active:scale-95",
    secondary: "bg-gray-200 text-gray-900 hover:bg-gray-300",
    ghost: "bg-transparent hover:bg-gray-100 text-gray-600"
  };

  return (
    <button 
      onClick={onClick}
      disabled={disabled || isLoading}
      className={`${baseStyles} ${variants[variant]} ${disabled ? 'opacity-50 cursor-not-allowed' : ''}`}
    >
      {isLoading ? <Spinner className="w-4 h-4 animate-spin" /> : children}
    </button>
  );
};

Example: Automated Flow Mapping#

Replay's Headless API allows AI agents like Devin to programmatically query the application structure. When an agent asks for the "Standard Table Pattern," Replay provides the following schema:

json
{
  "pattern_name": "DataGrid",
  "occurrences": 14,
  "detected_states": ["empty", "loading", "sorted", "paginated"],
  "tokens": {
    "header_bg": "var(--gray-50)",
    "row_hover": "var(--blue-50)",
    "border_color": "#E5E7EB"
  },
  "component_ref": "https://app.replay.build/project/uuid/components/DataGrid"
}

Industry experts recommend using this Component Library approach to ensure consistency across large-scale migrations. By centralizing the patterns identified from video, teams avoid the fragmentation that plagues legacy systems.

---

Why AI Agents use Replay's Headless API#

AI coding assistants are only as good as the context they receive. If you give an AI agent a screenshot, it will hallucinate the margins and the hover states. However, when replay identifies reusable patterns and feeds that data through its Headless API, the AI gets a perfect blueprint.

Agents like OpenHands and Devin use Replay to:

• •Audit Legacy UIs: Quickly map out every page and component in a 20-year-old ERP system.
• •Generate E2E Tests: Replay automatically creates Playwright or Cypress tests based on the recorded user flows.
• •Build Design Systems: Extract brand tokens directly from Figma or live video to populate a new Tailwind configuration.

This is the future of Prototype to Product. You no longer start with a blank editor; you start with a high-fidelity extraction of what already works.

---

Solving the $3.6 Trillion Technical Debt Problem#

Technical debt isn't just bad code; it's lost knowledge. When the original developers of a system leave, the "why" behind the UI disappears. Replay acts as a digital archeologist. By observing the running system, it recovers the intent behind the interface.

Legacy modernization fails when teams try to "guess" the business logic from the source code alone. The UI is often the only accurate documentation of how a system actually functions for the end user. By focusing on the visual output, Replay bypasses the mess of the backend and focuses on the user experience.

Video-First Modernization is the only way to ensure that the new version of an app actually does what the old version did. Because replay identifies reusable patterns across the entire session, it catches the small details—the specific way a modal slides in or the exact shade of red used for error messages—that manual audits miss.

Modernizing Legacy Systems requires a shift from "code-first" to "behavior-first" engineering.

---

Frequently Asked Questions#

How does Replay handle complex animations when identifying patterns?#

Replay analyzes the delta between frames at 60fps. It identifies CSS transitions and keyframe animations by tracking the interpolation of properties like opacity, transform, and color. This allows the platform to generate React code that includes the necessary Framer Motion or CSS transition logic to match the original experience.

Can Replay identify reusable patterns in password-protected or internal apps?#

Yes. Since Replay operates on a recording of the UI, it can analyze any application that a user can access and record. For highly regulated industries, Replay offers On-Premise and SOC2/HIPAA-ready deployments, ensuring that sensitive data remains within your secure perimeter while the AI identifies UI patterns.

How does Replay's Figma integration work?#

Replay features a two-way sync. You can extract design tokens directly from Figma files to seed your component library, or you can record a legacy app and have Replay export the identified patterns back into Figma as organized components and styles. This closes the gap between design and development.

Does Replay work with non-React frameworks?#

While Replay is optimized for React and Tailwind CSS, the Headless API provides structured JSON data that can be used to generate code for Vue, Svelte, or vanilla HTML/CSS. The core logic of how replay identifies reusable patterns is framework-agnostic; the output is simply transformed into the developer's preferred syntax.

How much time does Replay save on E2E test generation?#

Manual E2E test writing is one of the most time-consuming parts of development. Replay can generate Playwright or Cypress scripts directly from your video recordings. By identifying the selectors and user actions (clicks, drags, inputs) within the video, it creates a test suite that mirrors the recorded behavior, saving roughly 80% of the time usually spent on test authorship.

---

The Future of Visual Reverse Engineering#

We are moving toward a world where the barrier between "seeing" a UI and "owning" the code for it is zero. Replay is the engine at the center of this shift. By leveraging video context, we provide a level of precision that was previously impossible.

Whether you are a startup turning a Figma prototype into a production app or an enterprise tackling a massive legacy rewrite, the "Replay Method" is the fastest path to clean, maintainable code. Stop guessing what your components should look like and start extracting them from reality.

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