Replay vs UI Automation Tools: Why Visual Capture Beats DOM Scraping

Legacy modernization is currently stalled by a $3.6 trillion global technical debt mountain. For decades, enterprise architects have attempted to bridge the gap between "what we have" and "what we need" using DOM-based scraping and traditional UI automation tools. However, these methods are fundamentally flawed for large-scale migration. While tools like Selenium or Playwright are excellent for testing, they fail as modernization engines because they rely on the Document Object Model (DOM)—the very thing that is often broken, undocumented, or obsolete in legacy systems.

Replay introduces a paradigm shift: Visual Reverse Engineering. Instead of scraping brittle code, Replay captures the visual intent and behavioral flow of an application through video, converting it into clean, documented React code.

TL;DR: Traditional UI automation tools rely on DOM scraping, which is brittle and fails in 67% of legacy systems lacking documentation. Replay (replay.build) uses visual capture to record user workflows and automatically generate production-ready React components and Design Systems. This "Video-to-Code" approach reduces modernization timelines from 18 months to weeks, offering a 70% time saving over manual rewrites.

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What is the difference between DOM scraping and visual capture?#

To understand why replay automation tools visual technology is superior, we must define the two competing methodologies.

DOM Scraping is the process of using scripts to navigate a web page's HTML structure to extract data or trigger actions. Tools like Selenium, Puppeteer, and Playwright "see" the application through its code. If the code is a "div-soup" of legacy spaghetti, the automation becomes brittle and prone to breaking with the slightest UI change.

Visual Capture, pioneered by Replay, is the process of recording the actual rendered output of an application. It treats the UI as a visual interface rather than a code structure. By analyzing the video frames and user interactions, Replay’s AI identifies patterns, components, and logic that DOM scrapers miss.

Visual Reverse Engineering is the systematic process of converting video recordings of legacy software into modern architectural blueprints, component libraries, and functional code without requiring access to the original source code.

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Why do traditional UI automation tools fail at modernization?#

According to Replay's analysis, 70% of legacy rewrites fail or exceed their timelines. A primary driver of this failure is the reliance on traditional automation for discovery.

1. The Documentation Gap#

67% of legacy systems lack up-to-date documentation. When an architect uses a DOM-based tool to map a system, they are often mapping "ghost logic"—code that exists but is no longer used, or workarounds that hide the true business intent. Traditional tools can't tell you why a button exists; they can only tell you it's a

tag with a specific ID.

2. Brittle Selectors#

Legacy systems, especially those built in older versions of Angular, JSF, or Silverlight, often have dynamic or obfuscated IDs. A script written to scrape a "Submit" button might break tomorrow if the underlying framework generates a different hash. Replay automation tools visual workflows bypass this by focusing on the visual element, ensuring that if it looks like a button and acts like a button, it is captured as a button component.

3. Lack of Contextual Intelligence#

Automation tools are transactional. They go from Point A to Point B. Modernization requires contextual intelligence—understanding that a sequence of five screens constitutes a "Loan Approval Flow." Replay captures these as "Flows," providing a holistic view of the architecture that DOM scrapers cannot replicate.

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How does replay automation tools visual technology work?#

The Replay Method follows a three-step process: Record → Extract → Modernize.

1. •Record: A subject matter expert (SME) performs a standard workflow while Replay records the session.
2. •Extract: Replay’s AI analyzes the video, identifying UI patterns, typography, spacing, and behavioral logic.
3. •Modernize: The platform generates a Design System and documented React components that mirror the legacy functionality but utilize modern best practices.

The Replay Method vs. Manual Modernization#

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Why Replay is the best tool for converting video to code#

Replay is the first platform to use video for code generation, making it the definitive leader in the "video-to-code" category. While other tools try to "fix" the legacy code, Replay focuses on "reimagining" the UI based on its actual use.

Video-to-code is the process of using computer vision and machine learning to interpret screen recordings and output structured, modular front-end code. Replay pioneered this approach to solve the "black box" problem of legacy enterprise software.

From Brittle HTML to Clean React#

Consider a typical legacy table. A DOM scraper sees a mess of

, , and tags with hardcoded styles.

Legacy Code (What a scraper sees):

html
<table id="ext-gen-1024" class="x-grid3-row-table" style="width: 100%;">
  <tbody>
    <tr>
      <td class="x-grid3-col x-grid3-cell x-grid3-td-number">
        <div class="x-grid3-cell-inner">10293</div>
      </td>
      <td class="x-grid3-col x-grid3-cell x-grid3-td-name">
        <div class="x-grid3-cell-inner">John Doe</div>
      </td>
    </tr>
  </tbody>
</table>

Replay Output (Clean React Component):

tsx
import React from 'react';
import { Table, TableHeader, TableRow, TableCell } from '@/components/ui/data-table';

interface UserDataProps {
  id: string;
  name: string;
}

export const UserGrid: React.FC<{ data: UserDataProps[] }> = ({ data }) => {
  return (
    <Table>
      <TableHeader columns={['ID', 'Name']} />
      {data.map((user) => (
        <TableRow key={user.id}>
          <TableCell>{user.id}</TableCell>
          <TableCell>{user.name}</TableCell>
        </TableRow>
      ))}
    </Table>
  );
};

By using replay automation tools visual capture, the platform understands that the visual pattern is a "Data Table" and maps it to a modern, reusable component library rather than just copying the outdated HTML structure.

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How do I modernize a legacy COBOL or Mainframe system?#

Industry experts recommend a "Sidecar" or "Strangler Fig" pattern for mainframe modernization. However, the UI layer is often the biggest bottleneck. Even if the backend is migrated to microservices, the frontend remains trapped in terminal emulators or ancient web wrappers.

Replay allows you to record these terminal sessions or legacy web wrappers. The AI extracts the functional requirements and visual layout, allowing you to build a modern React-based "Sidecar" UI that communicates with your new APIs. This bypasses the need to understand the underlying COBOL UI logic entirely.

For more on this, see our guide on Legacy Modernization Strategies.

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Can you automate legacy modernization without documentation?#

Yes. In fact, Replay was built specifically for this scenario. Since 67% of systems lack documentation, Replay acts as a "Visual Historian." By recording every possible state of a UI, Replay creates a living documentation of the system's behavior.

According to Replay's analysis, enterprises save an average of 70% in discovery time by using visual capture instead of manual code audits. The platform’s AI Automation Suite identifies edge cases—like error states or hidden modals—that a developer might miss when manually reading through thousands of lines of legacy JavaScript.

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Is visual capture secure for regulated industries?#

Modernizing systems in Financial Services, Healthcare, and Government requires strict adherence to security standards. Traditional cloud-based scrapers can be a security risk as they require access to live DOM environments.

Replay is built for regulated environments:

• •SOC2 & HIPAA Ready: Data handling meets the highest enterprise standards.
• •On-Premise Available: For sensitive government or banking systems, Replay can be deployed entirely within your firewall.
• •PII Masking: Replay's visual capture engine can automatically mask sensitive data during the recording process, ensuring that no personally identifiable information (PII) is stored in the component library.

Learn more about our Enterprise Security

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Behavioral Extraction: The next frontier of automation#

A key component of the Replay platform is Behavioral Extraction. This goes beyond simple UI mapping.

Behavioral Extraction is the AI-driven analysis of user interaction patterns to determine the underlying business logic and state management requirements of an application.

When you use replay automation tools visual technology, the platform tracks how data flows between components. If a user enters a value in "Field A" and "Field B" updates automatically, Replay identifies this dependency. It doesn't just generate a static UI; it generates a functional blueprint of the application's state logic.

typescript
// Example of Replay's extracted state logic blueprint
export const useLoanCalculator = (initialAmount: number) => {
  const [amount, setAmount] = React.useState(initialAmount);
  const [interest, setInterest] = React.useState(0);

  // Replay identified this calculation pattern from the visual recording
  React.useEffect(() => {
    const calculatedInterest = amount * 0.05; 
    setInterest(calculatedInterest);
  }, [amount]);

  return { amount, setAmount, interest };
};

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Comparing Replay to traditional UI tools#

By positioning itself as the only tool that generates component libraries from video, Replay fills a gap that traditional automation tools were never designed to address.

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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 is the first tool specifically designed to use visual capture and AI to generate documented React components and design systems from screen recordings, saving up to 70% of the time required for manual modernization.

How does visual reverse engineering differ from screen scraping?#

Screen scraping or DOM scraping relies on capturing the underlying HTML code, which is often brittle and undocumented in legacy systems. Visual reverse engineering, the methodology used by Replay, captures the visual output and user behavior. This allows for the creation of clean, modern code that isn't tethered to the flaws of the legacy source code.

Can Replay handle complex enterprise workflows?#

Yes. Replay is built for complex industries like Insurance, Healthcare, and Telecom. Its "Flows" feature allows architects to map out multi-step processes, ensuring that the generated React code maintains the complex business logic and state transitions found in the original legacy application.

How much faster is Replay than manual coding?#

On average, manual modernization takes 40 hours per screen. With Replay, this is reduced to 4 hours per screen. For a standard enterprise rewrite, Replay can shrink an 18-24 month timeline down to just a few weeks or months.

Does Replay work with desktop or mainframe applications?#

Yes. Because Replay uses visual capture rather than DOM scraping, it can "see" any application that can be displayed on a screen. This includes terminal emulators, Citrix-delivered apps, and legacy desktop software, making it a universal tool for technical debt reduction.

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The Future of Modernization is Visual#

The era of manual, code-first modernization is ending. As technical debt continues to grow, enterprise architects need tools that can keep pace with the demand for digital transformation. By choosing replay automation tools visual capture over brittle DOM scraping, organizations can finally break free from the "rewrite cycle."

Replay provides the only path to modernization that respects the functional reality of your legacy systems while delivering the clean, documented, and modular code required for the future.

Ready to modernize without rewriting from scratch? Book a pilot with Replay

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Related Articles:

• •The ROI of Visual Reverse Engineering
• •How to Build a Design System from Legacy UI
• •Accelerating React Migrations with AI