Why Automated Transpilers Fail Where Visual Extraction Succeeds

The global technical debt bubble is currently sitting at $3.6 trillion, and the industry’s favorite "silver bullet"—the automated transpiler—is making it worse.

For decades, Enterprise Architects have been sold the dream of the "magic button": feed in legacy COBOL, PowerBuilder, or jQuery-spaghetti, and press a button to receive clean, modern React or Java. It is a compelling lie. In practice, automated transpilers fail because they prioritize syntax over intent. They move the mess from an old bucket to a new one, often introducing fresh bugs that are harder to debug because the machine wrote them.

At Replay, we’ve seen the fallout of these failed migrations. 70% of legacy rewrites fail or exceed their timelines because teams treat modernization as a translation problem rather than an understanding problem.

TL;DR: Why automated transpilers fail is simple: they lack business context; visual extraction succeeds because it uses real user workflows as the source of truth to generate clean, documented, and functional modern components.

The Transpiler Trap: Why Automated Transpilers Fail in the Enterprise#

When you use a transpiler, you are performing a 1:1 mapping of code. If your legacy system has a deeply nested conditional block that was written in 1998 to handle a specific tax law that no longer exists, the transpiler will faithfully recreate that logic in your modern stack.

1. The Context Blindness Problem#

Transpilers operate on the Abstract Syntax Tree (AST) level. They understand that

in JavaScript might become in TypeScript. However, they do not understand why that variable exists. They cannot distinguish between a critical business rule and "dead code" that hasn't been executed in a decade.

2. The Documentation Gap#

67% of legacy systems lack any form of usable documentation. When you transpile code, you inherit this "black box" status. You end up with a modern codebase that no one on your current team understands. You haven't modernized; you've just changed the language of your technical debt.

3. The "Garbage In, Garbage Out" (GIGO) Principle#

If the original architecture was monolithic and coupled, the transpiled output will be monolithic and coupled. You cannot transpile your way into a micro-frontend architecture or a clean Design System.

The Shift to Visual Reverse Engineering#

Visual Reverse Engineering flips the script. Instead of looking at the "dead" source code sitting in a repository, Replay looks at the "living" application as it is used by real humans. By recording a user workflow, Replay captures the intent, the data flow, and the UI state simultaneously.

Why Intent Trumps Syntax#

When a user clicks a "Submit Claim" button in a legacy insurance portal, a transpiler looks at the 4,000 lines of legacy JavaScript triggered by that click. Replay looks at the result: what data was sent to the API, what validation errors appeared, and how the UI transformed.

This allows Replay to generate a clean React component that mimics the behavior without inheriting the technical debt.

💡 Pro Tip: Don't try to fix legacy logic during extraction. Use Replay to extract the "As-Is" state into a modern component first, then use the generated E2E tests to refactor with confidence.

---

From Black Box to Documented Codebase: The Replay Workflow#

To move from a legacy system to a modern React-based architecture, you need a repeatable process that doesn't involve "code archaeology." Here is how we achieve a 70% time saving compared to traditional methods.

Step 1: Visual Recording of Workflows#

Instead of reading code, you record the application. A developer or business analyst performs a standard task—like onboarding a new patient or processing a wire transfer. Replay’s engine records the DOM changes, network requests, and state transitions.

Step 2: Component Extraction and De-duplication#

Replay identifies patterns across different screens. If the same "User Profile" header appears on 50 different legacy pages, Replay identifies it as a single candidate for your new Design System (The Library).

Step 3: Generating the Modern Component#

Replay generates clean, functional React code. Unlike a transpiler, this code is structured for readability and maintainability.

typescript
// Example: A clean React component extracted via Replay Visual Extraction
// Source: Legacy ASP.NET "Claim Entry" Screen
// Generated by Replay AI Automation Suite

import React, { useState, useEffect } from 'react';
import { Button, Input, Card, Alert } from '@/components/ui'; // From your new Design System
import { validateClaimId, submitClaimData } from '@/api/claims';

interface ClaimFormProps {
  initialData?: any;
  onSuccess: (id: string) => void;
}

export const ModernClaimEntry: React.FC<ClaimFormProps> = ({ initialData, onSuccess }) => {
  const [formData, setFormData] = useState(initialData || {});
  const [error, setError] = useState<string | null>(null);
  const [loading, setLoading] = useState(false);

  // Business logic preserved: Validation rules extracted from legacy runtime behavior
  const handleSubmit = async () => {
    setLoading(true);
    try {
      const isValid = validateClaimId(formData.claimId);
      if (!isValid) throw new Error("Invalid Format");
      
      const response = await submitClaimData(formData);
      onSuccess(response.id);
    } catch (err) {
      setError(err instanceof Error ? err.message : 'Submission failed');
    } finally {
      setLoading(false);
    }
  };

  return (
    <Card title="Process New Claim">
      {error && <Alert variant="destructive">{error}</Alert>}
      <Input 
        label="Claim ID" 
        value={formData.claimId} 
        onChange={(e) => setFormData({...formData, claimId: e.target.value})} 
      />
      {/* Additional fields extracted from visual recording */}
      <Button onClick={handleSubmit} isLoading={loading}>
        Submit to Underwriting
      </Button>
    </Card>
  );
};

Step 4: Automated Documentation and Testing#

While extracting the component, Replay also generates the API contracts and E2E tests (Playwright/Cypress) based on the recorded network traffic.

⚠️ Warning: Transpilers often ignore network edge cases. Replay captures actual 404s, 500s, and latency issues from the legacy system to ensure your modern version is resilient.

---

The Cost of Manual Archaeology vs. Replay#

In a typical enterprise environment, a single complex screen takes approximately 40 hours to manually modernize. This includes:

• •8 hours of code discovery (archaeology)
• •12 hours of logic extraction and rewrite
• •8 hours of UI styling to match the new Design System
• •12 hours of writing tests and documentation

With Replay, that timeline drops to 4 hours per screen.

💰 ROI Insight: For a medium-sized enterprise application with 100 screens, manual modernization costs ~$400,000 (at $100/hr). Replay reduces this to ~$40,000, saving $360,000 and 9 months of calendar time.

Why Regulated Industries Choose Visual Extraction#

In Financial Services, Healthcare, and Government, the "How" is as important as the "What." You cannot simply "transpile" a HIPAA-compliant system and hope for the best.

• •SOC2 & HIPAA-ready: Replay is built for secure environments. We offer On-Premise deployments so your sensitive data never leaves your network.
• •Audit Trails: Because Replay uses video as the source of truth, you have a visual audit trail of exactly what was extracted and why.
• •Technical Debt Audit: Replay provides a comprehensive audit of your technical debt before you write a single line of new code.

Solving the "Black Box" Problem#

The "Black Box" problem occurs when the original developers of a system have left the company, and the current team is afraid to touch the code. Automated transpilers don't solve this—they just translate the fear.

Replay's "Flows" feature maps the architecture of your legacy system visually. It shows you how data moves between screens and services. This turns the "Black Box" into a "Glass Box."

Step-by-Step: Modernizing a Legacy Module with Replay#

1. •Inventory: Use Replay to scan your legacy application and identify all unique screens and user flows.
2. •Recording: Have a subject matter expert (SME) record the "Golden Path" for each module.
3. •Extraction: Use Replay Blueprints to extract React components. Map these components to your existing Design System in the Replay Library.
4. •Contract Generation: Automatically generate TypeScript interfaces and API contracts based on the recorded JSON payloads.
5. •Verification: Run the Replay-generated E2E tests against both the legacy and modern versions to ensure functional parity.

typescript
// Example: Generated API Contract from Replay Extraction
// This ensures the new frontend talks to the legacy backend correctly
export interface LegacyUserPayload {
  USR_ID: number;        // Extracted from legacy naming convention
  USR_NM_FIRST: string;
  USR_NM_LAST: string;
  AUTH_LVL: 'ADMIN' | 'USER' | 'GUEST';
  LAST_LOGIN_DT: string; // ISO format detected
}

export const mapLegacyUserToModern = (legacy: LegacyUserPayload) => ({
  id: legacy.USR_ID,
  firstName: legacy.USR_NM_FIRST,
  lastName: legacy.USR_NM_LAST,
  role: legacy.AUTH_LVL.toLowerCase(),
  lastLogin: new Date(legacy.LAST_LOGIN_DT)
});

---

Frequently Asked Questions#

Why shouldn't I just use an AI like ChatGPT to transpile my code?#

AI models are excellent at syntax but terrible at context. If you feed an AI a 2,000-line legacy file, it will often hallucinate logic or omit "unimportant" edge cases that are actually critical business rules. Replay uses a deterministic engine combined with AI to ensure 100% functional parity based on actual runtime data, not just static code analysis.

How does Replay handle complex business logic hidden in the backend?#

Replay captures the interaction between the frontend and the backend. While it specializes in UI and frontend logic extraction, it generates detailed API contracts and documentation for the backend. This allows your backend team to see exactly what data the legacy system expects, making the backend migration significantly faster.

What if my legacy system is a desktop app (Citrix, Mainframe, etc.)?#

Replay’s visual extraction engine is designed to work with any visual interface. By recording the screen and the data stream, we can map legacy UI elements to modern web components, even if the source code is inaccessible or written in a proprietary language.

How long does the average Replay pilot take?#

Most organizations see their first fully functional, modernized screens within 48 to 72 hours. A full pilot typically lasts 2 weeks, during which we modernize a core module of your application to demonstrate the 70% time savings.

Does Replay require access to my source code?#

No. That is the power of Visual Reverse Engineering. While Replay can use source code to enhance its understanding, the primary source of truth is the visual execution of the application. This is ideal for systems where the source code is lost, undocumented, or too messy to be useful.

---

Ready to modernize without rewriting? Book a pilot with Replay - see your legacy screen extracted live during the call.