The Architecture of Extraction: Building a Bridge Between COBOL and React

The average enterprise rewrite is a graveyard of good intentions. We have spent the last decade watching $3.6 trillion in global technical debt accrue while CTOs continue to sign off on 24-month "Big Bang" migrations that have a 70% failure rate. The bottleneck isn't the destination—React, Next.js, and modern cloud-native architectures are well-understood. The bottleneck is the "archaeology": the thousands of hours spent digging through undocumented COBOL, VB6, or monolithic Java to understand business logic that was written before the current engineering team was born.

The architecture of extraction building a bridge between legacy and modern isn't about manual translation; it's about visual reverse engineering.

TL;DR: Legacy modernization fails because documentation is non-existent (67% of systems); Replay solves this by using video-based extraction to turn real-world user workflows into documented React components and API contracts in days, not years.

The $3.6 Trillion Black Box#

Most legacy systems are treated as black boxes. Input goes in, magic happens, and output comes out. When an organization decides to modernize, they typically choose one of two paths: the "Big Bang" rewrite or the "Strangler Fig" pattern.

The Big Bang approach fails because the business requirements have shifted 100 times since the original code was deployed. The Strangler Fig pattern, while safer, often stalls because the "vines" (the new services) can’t accurately replicate the nuanced, undocumented edge cases of the legacy "tree."

The data is clear: 67% of legacy systems lack any form of updated documentation. Expecting a senior architect to spend 40 hours per screen manually documenting logic is a recipe for talent churn and budget overruns. With Replay, that same screen is documented and extracted in 4 hours.

The Architecture of Extraction: Building a Bridge Without Archaeology#

The traditional modernization workflow is broken. It relies on "interviews" with subject matter experts (SMEs) who have forgotten 40% of the system’s behavior and "code deep-dives" by developers who don't speak the legacy language.

The architecture of extraction building a bridge between these eras requires a shift in perspective. We must treat the User Interface (UI) as the source of truth. Every business rule, every validation logic, and every state transition eventually manifests in the UI. By recording these workflows, we can reverse-engineer the underlying requirements with 100% accuracy.

The Replay Methodology#

Replay doesn't just record a video; it records the state, the network calls, the DOM mutations, and the user intent. It then uses an AI Automation Suite to synthesize this data into clean, modular code.

💰 ROI Insight: Manual reverse engineering costs approximately $150-$200/hour in senior engineering time. Reducing screen extraction from 40 hours to 4 hours saves $5,400+ per screen in labor costs alone.

Step 1: Visual Assessment and Recording#

Instead of reading 10,000 lines of COBOL, a product owner or SME performs the standard business workflow (e.g., "Onboard a New Insurance Policy") while Replay records the session. This captures every "if/then" branch that actually matters to the business.

Step 2: Component Synthesis#

Replay’s engine analyzes the recording to identify patterns. It looks for repeatable UI elements, form structures, and data handling patterns. It then maps these to your organization's Design System (via the Replay Library).

Step 3: Logic Extraction and API Contracting#

The bridge isn't just visual. Replay generates the API contracts required to support the new frontend. It identifies which legacy endpoints were called, what data was sent, and what the expected response format is.

typescript
// Example: Generated React Component from Replay Extraction
// This component preserves the legacy validation logic discovered during recording
import React, { useState } from 'react';
import { TextField, Button, Alert } from '@/components/ui'; 

interface OnboardingProps {
  initialData?: any;
  onComplete: (data: any) => void;
}

export function LegacyPolicyOnboarding({ initialData, onComplete }: OnboardingProps) {
  const [formData, setFormData] = useState(initialData);
  const [error, setError] = useState<string | null>(null);

  // Business logic preserved: Legacy systems often have complex 
  // cross-field validations (e.g., Policy Type vs. Risk Grade)
  const validateLegacyRules = (data: any) => {
    if (data.policyType === 'PREMIUM' && data.riskScore < 700) {
      return "Legacy Rule 402: Premium policies require a risk score > 700";
    }
    return null;
  };

  const handleSubmit = async () => {
    const validationError = validateLegacyRules(formData);
    if (validationError) {
      setError(validationError);
      return;
    }
    // Replay identifies the necessary API shape from network capture
    await fetch('/api/v1/legacy-bridge/onboard', {
      method: 'POST',
      body: JSON.stringify(formData)
    });
    onComplete(formData);
  };

  return (
    <div className="p-6 space-y-4">
      <h2 className="text-xl font-bold">Policy Onboarding</h2>
      {error && <Alert variant="destructive">{error}</Alert>}
      <TextField 
        label="Risk Score" 
        type="number" 
        onChange={(e) => setFormData({...formData, riskScore: e.target.value})} 
      />
      <Button onClick={handleSubmit}>Submit to Legacy Core</Button>
    </div>
  );
}

Challenging the "Clean Slate" Fallacy#

Engineering leaders often fall into the trap of believing a "clean slate" is the only way to pay down technical debt. This is a fallacy. Technical debt isn't just "bad code"—it's the gap between what the software does and what the business needs.

When you rewrite from scratch, you inevitably miss the "Chesterton’s Fence" of legacy logic. Why was that strange validation rule added in 2004? It was likely to prevent a specific multi-million dollar regulatory fine in the insurance or banking sector. If you don't extract that logic, you'll rediscover its importance the hard way: in production.

⚠️ Warning: Most AI-driven code converters fail because they try to translate code-to-code (e.g., COBOL to Java). This ignores the architectural context. Replay translates Behavior-to-Code, which is the only way to ensure functional parity.

From Black Box to Documented Codebase#

The "Blueprints" feature within Replay acts as the architectural bridge. It provides a visual map of the legacy system’s flows. For an Enterprise Architect, this is the "Holy Grail." You can finally see a visual representation of how a user moves through a 30-year-old mainframe application and how that maps to modern microservices.

Technical Debt Auditing#

Replay provides an automated Technical Debt Audit. By comparing the recorded workflows against the generated code, it identifies:

• •Redundant logic branches that are never hit.
• •Hardcoded values that should be environment variables.
• •Security vulnerabilities in the data flow (critical for SOC2 and HIPAA environments).

Generating E2E Tests Automatically#

One of the highest costs of modernization is regression testing. How do you know the new React app behaves exactly like the old PowerBuilder app?

Replay generates Playwright or Cypress E2E tests based on the recorded session. This ensures that the "bridge" you are building is structurally sound.

typescript
// Generated Playwright Test for Functional Parity
import { test, expect } from '@playwright/test';

test('verify legacy parity: policy onboarding flow', async ({ page }) => {
  await page.goto('/modernized-app/onboard');
  
  // Replay captured these specific interactions from the legacy system
  await page.fill('[data-testid="risk-score"]', '650');
  await page.selectOption('[data-testid="policy-type"]', 'PREMIUM');
  await page.click('text=Submit');

  // Asserting the exact error message discovered in the legacy recording
  const error = page.locator('.alert-destructive');
  await expect(error).toContainText('Legacy Rule 402');
});

Built for the Regulated Enterprise#

We aren't modernizing a weekend hobby project; we are modernizing the systems that run our global economy. Financial services, healthcare, and government agencies cannot afford "move fast and break things."

Replay is architected for these high-stakes environments:

• •SOC2 & HIPAA Ready: Data is encrypted at rest and in transit.
• •On-Premise Deployment: For organizations with strict data residency requirements, Replay can run entirely within your VPC.
• •PII Redaction: Our AI suite automatically identifies and redacts Personally Identifiable Information (PII) during the recording and extraction process.

The Future of Modernization is Understanding#

The era of the 2-year rewrite is over. The future belongs to the "Architecture of Extraction." By using Replay to build a bridge between the legacy past and the cloud-native future, companies can finally stop doing digital archaeology and start doing digital transformation.

You don't need more developers to fix your legacy problem. You need a better way to understand what you already have. Replay provides the map, the tools, and the code to get you there in weeks, not years.

Frequently Asked Questions#

How long does legacy extraction take?#

While a manual rewrite of a complex enterprise module typically takes 18-24 months, Replay reduces the timeline to 2-8 weeks. The extraction of a single complex screen—from recording to documented React component—takes approximately 4 hours, compared to the 40-hour industry average for manual reverse engineering.

What about business logic preservation?#

Replay captures the "truth of the UI." Because it records actual user interactions and the resulting network/data state changes, it identifies business rules that are often missing from documentation. This logic is then encapsulated into the generated React components or documented as API contracts for the backend team.

Does Replay support mainframe or terminal-based systems?#

Yes. If the legacy system can be accessed via a browser (including terminal emulators like 3270 web-based clients), Replay can record the workflow and extract the underlying logic, data structures, and transition states.

Is the generated code maintainable?#

Unlike "black-box" low-code platforms, Replay generates standard React/TypeScript code that follows your organization's specific design system and coding standards. It is "human-readable" and intended to be owned and maintained by your internal engineering team from day one.

---

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