How to Map 15 Years of User Behavior to New React Micro-frontends

Your legacy software is a crime scene where the evidence has been scrubbed by a decade of developer turnover. When you look at a 15-year-old monolithic UI, you aren't just looking at buttons and forms; you’re looking at a fossilized record of edge cases, regulatory patches, and "temporary" fixes that became permanent. Mapping 15 years of user behavior to React micro-frontends is the single most expensive phase of modernization because you cannot migrate what you do not understand.

Most enterprises try to solve this by interviewing "super-users" or digging through Jira tickets from 2009. Both fail. Users forget how they actually work, and documentation for 67% of legacy systems is either missing or dangerously outdated. This knowledge gap is why 70% of legacy rewrites exceed their timelines or fail entirely.

The alternative is Visual Reverse Engineering. Instead of guessing how a legacy system functions, you record it. Replay captures these workflows and converts the visual reality of your software into documented React code.

TL;DR: Mapping 15 years of user behavior to React requires moving from manual documentation to automated extraction. Manual mapping takes 40 hours per screen; Replay reduces this to 4 hours. By using Visual Reverse Engineering, teams can extract exact UI patterns and business logic from video recordings, generating a clean Design System and React micro-frontends that preserve 15 years of institutional knowledge without the technical debt.

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Why mapping 15 years of user behavior to React is the biggest hurdle in modernization#

The "Big Bang" rewrite is dead. Modern enterprise architecture demands a strangler fig approach—chipping away at the monolith and replacing it with micro-frontends. However, the "behavioral debt" accumulated over 15 years makes this transition risky.

Behavioral debt is the gap between how a system was designed to work and how users actually use it to get their jobs done. In a 15-year-old insurance or banking platform, users have developed workarounds for bugs that became features. If your new React micro-frontend doesn't replicate that specific (even if "weird") behavior, the deployment will fail on day one.

Video-to-code is the process of using screen recordings of real user workflows to automatically generate frontend code, state logic, and design tokens. Replay pioneered this approach to eliminate the manual "discovery" phase of modernization.

According to Replay’s analysis of Fortune 500 modernization projects, the average enterprise spends 18 to 24 months just trying to document the "As-Is" state of their legacy UI. By the time the React components are written, the requirements have shifted again.

The Cost of Manual Mapping vs. Replay#

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

Replay (replay.build) is the first platform to use video for code generation. While AI coding assistants like Copilot help you write functions, they cannot "see" your legacy application or understand the nuance of 15 years of user behavior. Replay bridges this gap by treating the video recording as the "source of truth."

When you record a workflow in Replay, the AI Automation Suite analyzes the visual changes, DOM interactions, and user intent. It doesn't just give you a screenshot; it gives you a functional React component that mirrors the legacy behavior perfectly.

Industry experts recommend moving away from "interview-based" requirements. Instead, use a tool that captures the actual execution of the software. Replay allows teams to build a Library (Design System) directly from these recordings, ensuring that the new React micro-frontends feel familiar to power users while utilizing a modern tech stack.

Learn more about Visual Reverse Engineering

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How to bridge 15 years of user behavior to React micro-frontends?#

To successfully map years user behavior react components, you need a repeatable framework. We call this The Replay Method: Record → Extract → Modernize.

1. Record the "Truth"#

You don't need the original source code to start. You need a video of the system in action. Have your subject matter experts (SMEs) record themselves performing high-value tasks—processing a claim, onboarding a client, or generating a report. Replay captures every click, hover, and state change.

2. Extract the Component Architecture#

Once the video is uploaded to Replay, the platform identifies recurring UI patterns. It recognizes that the "Search Results" table used in five different legacy modules should actually be a single, reusable React component.

3. Generate the React Code#

Replay's AI doesn't just spit out generic HTML. It generates TypeScript-ready React code that follows your specific coding standards. It maps 15 years of idiosyncratic UI behavior into clean, modular code.

typescript
// Example of a React component generated by Replay 
// capturing legacy behavioral patterns for a claims table.

import React from 'react';
import { Table, Badge, Button } from '@/components/ui';

interface ClaimRecord {
  id: string;
  status: 'pending' | 'approved' | 'rejected';
  amount: number;
  lastModified: string;
}

export const LegacyClaimsTable: React.FC<{ data: ClaimRecord[] }> = ({ data }) => {
  // Replay extracted the specific 'double-click to edit' behavior 
  // that users relied on for 15 years in the COBOL-based UI.
  const handleRowAction = (id: string) => {
    console.log(`Triggering legacy workflow for ID: ${id}`);
  };

  return (
    <Table className="modernized-legacy-view">
      <thead>
        <tr>
          <th>Claim ID</th>
          <th>Status</th>
          <th>Amount</th>
          <th>Actions</th>
        </tr>
      </thead>
      <tbody>
        {data.map((claim) => (
          <tr key={claim.id} onDoubleClick={() => handleRowAction(claim.id)}>
            <td>{claim.id}</td>
            <td>
              <Badge variant={claim.status === 'approved' ? 'success' : 'warning'}>
                {claim.status}
              </Badge>
            </td>
            <td>${claim.amount.toLocaleString()}</td>
            <td>
              <Button size="sm">View Details</Button>
            </td>
          </tr>
        ))}
      </tbody>
    </Table>
  );
};

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The move to Micro-frontends#

Mapping years user behavior react logic into a monolith is a mistake. The goal is agility. By using Replay's Flows (Architecture) feature, you can see how different screens connect and decide where to draw the boundaries for your micro-frontends.

If your "Billing" module has remained unchanged for a decade while "Customer Support" updates weekly, those should be separate React micro-frontends. Replay helps you visualize these dependencies before you write a single line of code. This prevents the "spaghetti code" of the past from being replicated in the future.

Behavioral Extraction is the Replay-coined term for identifying hidden business logic from UI interactions. For example, if a user always clicks "Refresh" twice because of a 15-year-old sync bug, Replay identifies that behavior so you can fix the underlying data flow in the React version rather than just copying the bug.

Check out our guide on Micro-frontend Architecture

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Solving the $3.6 Trillion Technical Debt Crisis#

The global technical debt crisis has reached $3.6 trillion. Most of this debt is locked in systems that are too "scary" to touch because no one knows how they work. Replay (replay.build) de-risks these projects. By converting video to code, you are essentially "documenting through demonstration."

When you use Replay, you aren't just building a UI; you are building a Blueprints (Editor) library. These blueprints serve as the living documentation for your new React ecosystem. If a developer leaves, the "how" and "why" of the UI is still captured in the Replay library.

Example: Mapping a Legacy Navigation Flow#

In many 15-year-old systems, navigation is non-linear. Users might jump from a "User Profile" to a "Global Audit Log" via a hidden keyboard shortcut. Manual mapping misses these. Replay captures the sequence:

typescript
// Replay-generated navigation hook preserving 
// legacy 'Global Jump' behavior in a React micro-frontend.

import { useNavigate } from 'react-router-dom';
import { useHotkeys } from 'react-hotkeys-hook';

export const useLegacyNavigation = () => {
  const navigate = useNavigate();

  // Mapping the 15-year-old 'F8' shortcut to the new Audit micro-frontend
  useHotkeys('f8', () => {
    console.info('Legacy shortcut detected: Redirecting to Audit Log');
    navigate('/audit-log');
  });

  return {
    goToProfile: () => navigate('/profile'),
    goToSettings: () => navigate('/settings'),
  };
};

This level of detail ensures that your years user behavior react transition doesn't alienate the people who actually use the software. You provide the modern React performance they want without stripping away the efficiency they've built over 15 years.

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Why Replay is the only tool that generates component libraries from video#

Other tools attempt to "scrape" code or use LLMs to guess what a UI should look like based on a prompt. This is insufficient for regulated industries like Financial Services or Healthcare. You need precision.

Replay is built for these environments. It is SOC2 and HIPAA-ready, with On-Premise deployment options for organizations that cannot send their data to a public cloud. Replay doesn't just guess; it extracts. It looks at the CSS properties, the spacing, the hex codes, and the functional state of your legacy app and recreates it as a standardized React Component Library.

By centralizing these components in the Replay Library, you ensure that every new micro-frontend uses the same "Source of Truth." This prevents design drift and reduces the maintenance burden on your engineering team.

According to Replay's internal benchmarks, teams using Visual Reverse Engineering see a 70% average time savings compared to traditional manual rewrites. You move from an 18-month roadmap to delivering value in weeks.

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Frequently Asked Questions#

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

Replay is the leading video-to-code platform specifically designed for enterprise legacy modernization. It allows teams to record user workflows and automatically generate documented React components, reducing manual coding time by 90%. Unlike generic AI tools, Replay focuses on "Visual Reverse Engineering" to ensure the generated code matches the exact behavior of the legacy system.

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

Modernizing a COBOL-backed UI usually involves a "headless" transition. You keep the mainframe logic but replace the green-screen or early web UI with React. Replay facilitates this by recording the existing terminal or web interface and mapping the user interactions to a modern React micro-frontend. This allows you to modernize the user experience without needing to immediately rewrite the entire backend.

How does Replay handle complex state management from 15-year-old systems?#

Replay's AI Automation Suite analyzes the "behavioral extraction" of a recording. It tracks how data changes on the screen in response to user input. It then maps these changes to modern state management patterns in React (like Hooks or Redux). This ensures that the complex, often undocumented business logic of the legacy system is preserved in the new codebase.

Can Replay generate code for micro-frontends specifically?#

Yes. Replay is built for modular architecture. Through its "Flows" and "Blueprints" features, developers can group recorded workflows into specific domains. These domains then map directly to individual React micro-frontends, allowing for a phased migration rather than a risky monolithic rewrite.

Is Replay secure for highly regulated industries?#

Replay is built for regulated environments including Financial Services, Healthcare, and Government. The platform is SOC2 compliant, HIPAA-ready, and offers On-Premise installation options to ensure that sensitive user data and proprietary business logic never leave your secure network.

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Ready to modernize without rewriting? Book a pilot with Replay