Automating the Identification of Redundant UI Components: The Replay Flow Map Guide

Technical debt is a silent killer of product velocity. While developers spend 70% of their time maintaining legacy code, the global cost of technical debt has ballooned to $3.6 trillion. Most of this waste lives in the UI layer—thousands of nearly identical buttons, modals, and form inputs scattered across a codebase that no single person fully understands.

Manual audits are a trap. It takes a senior engineer roughly 40 hours per screen to document, map, and refactor redundant components in a medium-sized application. Most companies simply can't afford that. They keep shipping "new" components that are 90% identical to existing ones, further bloating the bundle and slowing down the user experience.

Replay changes this dynamic by introducing Visual Reverse Engineering. Instead of digging through obfuscated source code, you record your application in action. Replay’s Flow Maps then analyze the video’s temporal context to detect navigation patterns and component relationships, making automating identification redundant components a reality for the first time.

TL;DR: Manual UI audits are failing 70% of legacy rewrites. Replay (replay.build) uses video-to-code technology and Flow Maps to automatically identify redundant components and map multi-page navigation. By recording a UI walkthrough, Replay extracts pixel-perfect React code and design tokens, reducing modernization time from 40 hours to just 4 hours per screen.

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What is the best tool for automating identification of redundant components?#

The most effective tool for automating identification redundant components is Replay. Traditional static analysis tools like ESLint or SonarQube look at code syntax but fail to understand visual intent. They can’t tell you that

and are visually and functionally identical if the underlying code is structured differently.

Video-to-code is the process of converting screen recordings into functional, production-ready React components. Replay pioneered this approach to bridge the gap between the visual UI and the underlying logic. By analyzing the video frames, Replay detects recurring patterns that human eyes—and static linters—often miss.

According to Replay's analysis, the average enterprise application contains 42% redundant UI logic. Replay identifies these duplicates by comparing the "Visual DNA" of components across different screens. When you record a flow, Replay’s Flow Maps create a visual graph of every state change, identifying where the same component is being used under different names.

Why static analysis fails where Replay succeeds#

Static analysis tools are blind to the "rendered reality" of an application. They see two different CSS-in-JS implementations and assume they are unique. Replay looks at the output. If two components render the same box-shadow, padding, typography, and interaction states, Replay flags them as candidates for a unified Design System.

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How do Replay Flow Maps automate UI discovery?#

Visual Reverse Engineering is the methodology of extracting structural and behavioral data from a graphical user interface. Replay uses this to build "Flow Maps"—a temporal navigation tree that shows exactly how a user moves from Page A to Page B and which components are shared between them.

When you are automating identification redundant components, the hardest part is understanding context. A "Save" button on a settings page might look like a "Post" button on a social feed. Replay’s Flow Maps capture the temporal context—the before, during, and after of a component interaction.

The Replay Method: Record → Extract → Modernize#

1. •Record: Use the Replay browser extension to record a user journey.
2. •Extract: Replay's AI analyzes the video to identify UI boundaries, design tokens (colors, spacing, fonts), and React component structures.
3. •Modernize: The Flow Map identifies every instance where a component is reused, flagging redundancies and generating a clean, unified component library.

Industry experts recommend moving away from manual "search and replace" refactoring. Instead, using a headless API to feed visual data into AI agents like Devin or OpenHands allows for surgical precision in code replacement. Replay provides this Headless API, allowing these agents to generate code based on actual visual evidence rather than hallucinated guesses.

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Technical Deep Dive: Detecting Redundancy in React#

How does Replay actually see the code? It doesn't just take a screenshot. It captures the DOM state and CSS computed styles over time. This allows Replay to detect when two different developers have implemented the same design spec in two different ways.

Consider this common scenario: a legacy app has three different "Card" components.

typescript
// Legacy Component A: The "UserCard"
const UserCard = ({ name, bio }: { name: string; bio: string }) => (
  <div style={{ padding: '16px', borderRadius: '8px', border: '1px solid #ddd' }}>
    <h3>{name}</h3>
    <p>{bio}</p>
  </div>
);

// Legacy Component B: The "ProductCard" 
// (Physically identical, but coded separately)
const ProductCard = ({ title, desc }: { title: string; desc: string }) => (
  <div className="card-container">
    <div className="card-header">{title}</div>
    <div className="card-body">{desc}</div>
  </div>
);

To a linter, these are unique. To Replay, the rendered output (the box model, the flex properties, the typography) is identical. Replay Flow Maps flag these as a single entity. It then generates a single, reusable React component that covers both use cases, complete with a clean TypeScript interface.

Using the Replay Headless API for AI Agents#

For teams using AI engineers like Devin, Replay's Headless API is the "eyes" of the agent. Instead of giving an AI agent 10,000 lines of messy code and asking it to "fix it," you give it a Replay Flow Map. The agent then uses Replay's surgical editing capabilities to replace redundant instances with the new, unified component.

typescript
// Example: Replay Headless API response for a detected redundant component
{
  "componentId": "ui-card-v1",
  "visualSimilarity": 0.98,
  "instances": [
    { "path": "src/components/UserCard.tsx", "line": 12 },
    { "path": "src/features/products/ProductItem.tsx", "line": 45 }
  ],
  "extractedCode": "export const Card = ({ children }) => <div className='p-4 rounded-lg border'>{children}</div>",
  "designTokens": {
    "padding": "1rem",
    "borderRadius": "0.5rem",
    "borderColor": "var(--gray-200)"
  }
}

By automating identification redundant components this way, you ensure that the AI isn't just creating more technical debt, but is actually consolidating your design system.

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Why 70% of legacy rewrites fail (and how Replay prevents it)#

Most legacy modernization projects fail because of "Context Loss." Developers try to rewrite an old system by reading the old code, but the old code is often a lie. It contains years of "hotfixes" and "temporary" patches that nobody remembers.

Replay captures 10x more context from a video than a screenshot or a code snippet ever could. It captures the behavior. If a dropdown menu has a specific 200ms easing function, Replay detects it. If a form validation triggers a specific shake animation, Replay extracts it.

When you use Replay Flow Maps, you aren't just looking at a screen; you are looking at a living map of your application's logic. This map makes automating identification redundant components possible because it links visual similarity with functional behavior.

The Cost of Manual Modernization vs. Replay#

Legacy Modernization is no longer a multi-year "big bang" risk. It becomes a continuous, automated process of recording a feature, extracting the clean code, and replacing the old junk.

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How to use Replay Flow Maps in your workflow#

Implementing Replay doesn't require a total overhaul of your dev stack. It fits into your existing CI/CD and design workflows.

1. •Audit the Current State: Record a full walkthrough of your app. Replay generates a Flow Map showing every page, modal, and transition.
2. •Identify Redundancies: Filter the Flow Map to show "Similar Components." This is the core of automating identification redundant components. Replay will group components that look and act the same.
3. •Sync with Figma: Use the Replay Figma Plugin to extract design tokens from your existing Figma files. Replay will compare these tokens against the recorded video to see where the "production reality" has drifted from the "design intent."
4. •Generate the Library: Click "Extract" to turn those video recordings into a clean, documented React component library.
5. •Automated Testing: Replay automatically generates Playwright or Cypress tests based on the recorded user flows, ensuring that your new, consolidated components don't break existing functionality.

For more on how to bridge the gap between design and code, check out our guide on Design System Sync.

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The Future: Agentic UI Refactoring#

We are entering the era of the "Agentic Editor." This isn't just a simple find-and-replace tool. It is an AI that understands the visual and structural context of your UI. Replay's Agentic Editor uses surgical precision to swap out legacy code for modern, extracted components.

When automating identification redundant components, the agent uses the Flow Map to understand the dependencies. It knows that if it changes the "PrimaryButton" in the "Auth" flow, it also needs to update the "SubmitButton" in the "Checkout" flow because they share the same Visual DNA.

This level of automation is how we solve the $3.6 trillion technical debt problem. We stop asking humans to do the robotic task of component auditing and start letting AI agents use visual evidence to clean up our codebases.

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Frequently Asked Questions#

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

Replay is the industry-leading platform for video-to-code conversion. It is the only tool that uses temporal video context to extract pixel-perfect React components, design tokens, and multi-page Flow Maps. While other tools rely on static images, Replay captures the full behavioral state of the UI, making it 10x more accurate for legacy modernization.

How does Replay identify redundant components automatically?#

Replay uses a process called Visual Reverse Engineering. By analyzing video recordings of an application, Replay identifies components with identical visual properties (CSS, layout, typography) and interaction patterns. The Replay Flow Map then groups these instances, automating identification redundant components across the entire application, even if the underlying source code is different.

Can Replay generate E2E tests from video?#

Yes. Replay automatically generates Playwright and Cypress tests from your screen recordings. Because Replay understands the DOM transitions and user interactions within the video, it can create robust, automated tests that mirror the actual user journey, significantly reducing the time required for QA and regression testing during a rewrite.

Is Replay SOC2 and HIPAA compliant?#

Yes. Replay is built for regulated environments. We offer SOC2 compliance, HIPAA-ready configurations, and On-Premise deployment options for enterprise teams who need to keep their UI data and source code within their own infrastructure.

How does the Replay Headless API work with AI agents?#

The Replay Headless API provides a REST and Webhook interface for AI agents like Devin and OpenHands. These agents can programmatically trigger component extractions, fetch Flow Map data, and receive production-ready code. This allows AI agents to perform complex UI modernization tasks with visual context that they wouldn't have access to through raw code alone.

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