How a Global Retailer Modernized 500+ POS Screens in Under 6 Months

Most legacy modernization projects are dead before the first line of code is written. The industry standard for a "Big Bang" rewrite is an 18-24 month timeline with a 70% failure rate. For a global retailer managing 500+ Point of Sale (POS) screens across 4,000 locations, that failure isn't just a budget overrun—it’s a catastrophic business risk.

The $3.6 trillion global technical debt crisis isn't caused by a lack of talent; it's caused by the "archaeology" phase. Engineers spend 60% of their time digging through undocumented COBOL or Delphi codebases just to understand business rules that the original developers took to their retirement.

TL;DR: By shifting from manual code archaeology to visual reverse engineering with Replay, a global retailer bypassed the 18-month "Big Bang" rewrite trap, modernizing 500+ screens into a production-ready React design system in under 6 months.

The Archaeology Tax: Why Manual Rewrites Fail#

The traditional approach to modernization is fundamentally broken. When you ask a team to modernize a legacy POS system, they typically follow a predictable, doomed path:

1. •The Hunt: Searching for documentation that doesn't exist (67% of legacy systems lack it).
2. •The Guess: Reverse-engineering business logic by reading thousands of lines of "spaghetti" code.
3. •The Manual Build: Recreating every UI element from scratch, taking an average of 40 hours per screen.

This retailer was staring down a $25M estimate for a 2-year project. They had 527 unique screens, ranging from inventory lookups to complex split-payment workflows. Using manual methods, they were looking at 21,080 man-hours just for UI parity.

Modernization Methodology Comparison#

The Replay Framework: From Black Box to React Components#

The breakthrough occurred when the architectural team stopped looking at the source code and started looking at the runtime. By using Replay to record real user workflows, the "black box" of the legacy POS became a structured data source.

Instead of 40 hours per screen, the team averaged 4 hours per screen. This 90% reduction in manual effort allowed them to move from assessment to deployment in a single quarter.

Step 1: Visual Recording of Workflows#

The team identified the "Critical Path" workflows: checkout, returns, and inventory adjustments. Using Replay, subject matter experts (SMEs) simply performed these tasks in the legacy environment.

💡 Pro Tip: Don't try to record every edge case in week one. Focus on the "Happy Path" for 80% of your screens to build your core component library first.

Step 2: Automated Component Extraction#

Replay’s engine analyzed the recorded sessions and automatically generated documented React components. This wasn't just "CSS scraping"—it was a functional extraction of the UI state and component hierarchy.

typescript
// Example: Generated POS Action Component from Replay Extraction
// This component was extracted directly from a legacy 'Void Item' workflow
import React, { useState, useEffect } from 'react';
import { Button, Modal, Alert } from '@/components/ui-library';

interface VoidItemProps {
  transactionId: string;
  itemId: string;
  onSuccess: (data: any) => void;
  onCancel: () => void;
}

export const LegacyVoidAction: React.FC<VoidItemProps> = ({ 
  transactionId, 
  itemId, 
  onSuccess, 
  onCancel 
}) => {
  const [isAuthorizing, setIsAuthorizing] = useState(false);
  const [error, setError] = useState<string | null>(null);

  // Business logic preserved from legacy runtime behavior
  const handleVoid = async () => {
    setIsAuthorizing(true);
    try {
      const response = await fetch(`/api/v1/pos/void`, {
        method: 'POST',
        body: JSON.stringify({ transactionId, itemId })
      });
      if (response.ok) {
        onSuccess(await response.json());
      } else {
        setError("Manager override required for this transaction type.");
      }
    } catch (err) {
      setError("Network timeout: Legacy middleware unreachable.");
    } finally {
      setIsAuthorizing(false);
    }
  };

  return (
    <Modal title="Void Item Confirmation" isOpen={true} onClose={onCancel}>
      <div className="p-4">
        <p>Are you sure you want to void item {itemId}?</p>
        {error && <Alert variant="destructive">{error}</Alert>}
        <div className="flex gap-4 mt-6">
          <Button onClick={handleVoid} loading={isAuthorizing}>Confirm Void</Button>
          <Button variant="outline" onClick={onCancel}>Abort</Button>
        </div>
      </div>
    </Modal>
  );
};

Step 3: API Contract Generation#

One of the biggest pain points in retail modernization is the "Middleware Mystery." The legacy POS often communicates with an on-premise server via undocumented protocols.

Replay's AI Automation Suite monitored the network traffic during the recording sessions to generate OpenAPI (Swagger) specifications. This allowed the backend team to build modern wrappers around legacy APIs without guessing the payload structures.

⚠️ Warning: Many legacy systems use non-standard headers or session-based state that is easily missed by manual documentation. Always use automated traffic capture to ensure 100% contract fidelity.

yaml
# Generated API Contract for POS Inventory Lookup
openapi: 3.0.0
info:
  title: Legacy POS Proxy API
  version: 1.0.0
paths:
  /inventory/lookup:
    get:
      summary: Extracted from 'Scan Item' workflow
      parameters:
        - name: store_id
          in: query
          required: true
          schema:
            type: string
        - name: sku
          in: query
          required: true
          schema:
            type: string
      responses:
        '200':
          description: Successful lookup
          content:
            application/json:
              schema:
                type: object
                properties:
                  price: {type: number}
                  stock_level: {type: integer}
                  is_taxable: {type: boolean}

Scaling to 500+ Screens: The "Library" Strategy#

A global retailer cannot afford 500 unique codebases. The "Replay Library" feature allowed the architects to identify common patterns across the 500+ screens.

They discovered that while the screens looked different, they shared a core set of 42 functional components (Numpads, SKU inputs, Payment selectors). By extracting these into a centralized Design System, the team achieved a "Flywheel Effect":

• •Screens 1-50: 10 hours per screen (Building the library)
• •Screens 51-200: 4 hours per screen (Reusing components)
• •Screens 201-527: 1.5 hours per screen (Assembly only)

💰 ROI Insight: The retailer saved an estimated $12.4M in developer salaries and avoided an additional $4M in "opportunity cost" by launching 18 months ahead of the original schedule.

Handling Regulated Environments#

In the retail sector, PCI-DSS compliance and SOC2 requirements are non-negotiable. The retailer could not send sensitive transaction data to a public cloud. Replay’s On-Premise deployment option allowed the team to run the entire extraction engine within their own VPC.

• •Data Masking: Sensitive customer PII was masked during the recording process.
• •Audit Trails: Every extracted component was linked back to the original video recording, providing a 1:1 "Source of Truth" for compliance audits.

Solving the "Documentation Gap"#

The most significant long-term benefit wasn't the code—it was the knowledge. 67% of legacy systems fail because the people who understand them leave the company.

By using Replay, the retailer created a "Visual Documentation" portal. If a new developer needs to understand how the complex "Tax-Exempt Bulk Sale" logic works, they don't look at a 200-page PDF. They watch the Replay recording that generated the code.

• •Visual Traceability: Click a line of code to see the exact UI state it handles.
• •Automated Technical Debt Audit: Replay identified dead code paths that were never triggered during any recorded user workflow, allowing the team to prune 30% of the legacy logic that was no longer needed.

The Results: A Modernized Enterprise#

By month six, the retailer had:

1. •Fully Migrated UI: 527 screens converted to a high-performance React Native application.
2. •Automated Testing: 1,200+ E2E tests generated automatically from the recording sessions.
3. •Zero Downtime: Because the logic was extracted from the runtime, the new system behaved exactly like the old one, requiring zero retraining for store associates.

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Frequently Asked Questions#

How long does legacy extraction take with Replay?#

While a manual rewrite takes 40+ hours per screen, Replay reduces this to an average of 4 hours. For most enterprises, a pilot project covering 10-20 core screens can be completed in just 2 weeks.

What about business logic preservation?#

Replay doesn't just "guess" the logic. It captures the state changes and API interactions during real user sessions. This ensures that the generated code reflects how the system actually behaves, not just how it was intended to behave 20 years ago.

Can Replay handle mainframe or terminal-based systems?#

Yes. As long as there is a visual interface (Web, Desktop, or Terminal Emulator), Replay can record the workflow and extract the underlying structure into modern web components.

Is it compatible with our existing CI/CD?#

Absolutely. Replay generates standard React/TypeScript code and OpenAPI specs that integrate directly into your existing GitHub, GitLab, or Jenkins pipelines.

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