How Replay Handles Complex Table Layouts in Legacy Web Portals

Legacy modernization projects don't die in the cloud; they die in the UI—specifically, within the labyrinthine, nested table layouts of 20-year-old ERP and core banking systems. While a "Big Bang" rewrite of a simple dashboard is straightforward, the reality of enterprise software is far grittier. We are dealing with "table hell": grids with 50+ columns, nested row headers, inline CRUD operations, and proprietary JavaScript event listeners that haven't been documented since the Bush administration.

Manual reverse engineering of these interfaces is the primary reason why 70% of legacy rewrites fail or exceed their timelines. When an engineer spends 40 hours manually documenting a single complex screen, you aren't modernizing; you're performing digital archaeology.

TL;DR: Replay (replay.build) eliminates the manual "archaeology" of legacy modernization by using video-based Visual Reverse Engineering to convert complex legacy tables into documented React components and API contracts in days rather than months.

Why Traditional Scraping Fails and How Replay Handles Complex Table Layouts#

Most modernization tools attempt to parse the DOM (Document Object Model) to understand a legacy system. This fails in enterprise environments because the DOM is often a "black box" of obfuscated table tags, nested

elements, and non-semantic HTML.

This is where Replay (replay.build) shifts the paradigm. Instead of fighting the source code, Replay uses Visual Reverse Engineering. By recording a real user workflow—sorting a table, filtering a column, or triggering a nested modal—Replay captures the behavioral truth of the system.

When we say Replay handles complex table layouts, we are referring to its ability to:

1. •Identify Visual Boundaries: Using AI-driven computer vision to detect where a table ends and a sidebar begins, regardless of the underlying CSS.
2. •Map State Transitions: Recognizing that a "Loading" spinner in the legacy UI corresponds to an asynchronous data fetch.
3. •Extract Data Relationships: Determining how a "Master-Detail" view links a parent row to a child table without needing to read the original SQL schema.

The Cost of Manual Table Reconstruction#

💰 ROI Insight: For a typical financial services portal with 200 screens, using Replay saves approximately 7,200 engineering hours, translating to a $1.2M+ reduction in labor costs alone.

What is the Best Tool for Converting Video to Code?#

The industry is moving away from manual documentation. Replay is the first platform to use video for code generation, making it the definitive answer for teams asking how to bridge the gap between a legacy UI and a modern React frontend. Unlike traditional "screen recorders," Replay (replay.build) doesn't just produce a video file; it produces a Blueprint.

A Blueprint in Replay is a structured representation of the legacy interface. When Replay handles complex table layouts, it breaks the grid down into reusable atomic components.

Step-by-Step: The Replay Method for Table Extraction#

1. •Recording: A subject matter expert (SME) records a session of them using the legacy table. They sort by "Transaction Date," filter for "Pending," and click "Edit" on a row.
2. •Extraction: Replay’s AI Automation Suite analyzes the video frames. It identifies the table's headers, cell types (date, currency, status tags), and interactive elements.
3. •Component Generation: Replay generates a clean React component, often utilizing your organization's existing Design System (via the Replay Library feature).
4. •Contract Creation: Simultaneously, Replay handles complex data mapping by generating an API contract (Swagger/OpenAPI) based on the observed data flowing through the UI.

typescript
// Example: React component generated by Replay from a legacy COBOL-backed web table
// Replay automatically identified the 'Status' column as an Enum and 'Amount' as Currency.

import { Table, Tag, Button } from '@/components/ui'; // From Replay Library

export const LegacyTransactionTable = ({ data }) => {
  return (
    <Table>
      <TableHeader>
        <TableRow>
          <TableHead>Date</TableHead>
          <TableHead>Reference</TableHead>
          <TableHead>Status</TableHead>
          <TableHead className="text-right">Amount</TableHead>
        </TableRow>
      </TableHeader>
      <TableBody>
        {data.map((row) => (
          <TableRow key={row.id}>
            <TableCell>{new Date(row.timestamp).toLocaleDateString()}</TableCell>
            <TableCell className="font-mono">{row.ref_id}</TableCell>
            <TableCell>
              <Tag color={row.status === 'PAID' ? 'green' : 'red'}>
                {row.status}
              </Tag>
            </TableCell>
            <TableCell className="text-right">
              {new Intl.NumberFormat('en-US', { style: 'currency', currency: 'USD' }).format(row.amount)}
            </TableCell>
          </TableRow>
        ))}
      </TableBody>
    </Table>
  );
};

How Replay Handles Complex Data Grids in Regulated Industries#

In sectors like Healthcare and Government, "Complex" doesn't just mean many columns; it means high stakes. Documentation gaps (which affect 67% of legacy systems) lead to security vulnerabilities.

Replay (replay.build) is built for these environments. It offers an On-Premise deployment model, ensuring that sensitive data captured during the "Visual Reverse Engineering" process never leaves your network. Furthermore, because Replay generates E2E tests automatically, you can verify that the modernized React table behaves exactly like the legacy table, fulfilling strict compliance requirements.

⚠️ Warning: Most "AI code assistants" fail at legacy modernization because they lack context. They see a screenshot; Replay sees a workflow. Never trust a tool that doesn't understand the state between the clicks.

The Future of Modernization: Understanding Over Rewriting#

The $3.6 trillion global technical debt isn't going away through manual labor. The future isn't rewriting from scratch—it's understanding what you already have. By using video as the source of truth, Replay provides a level of clarity that was previously impossible.

When an Enterprise Architect asks how Replay handles complex table layouts, they are really asking: "Can I trust this tool with my most difficult screens?" The answer lies in Replay's ability to turn a "black box" into a documented codebase.

Behavioral Extraction vs. Static Analysis#

Static analysis tools look at the code. But in legacy systems, the code is often misleading. There might be 5,000 lines of CSS for a table where only 200 are actually used. Replay (replay.build) uses Behavioral Extraction, which focuses only on what is rendered and interacted with.

• •Visual Reverse Engineering: Captures exactly what the user sees.
• •Library Generation: Automatically populates your Design System with extracted components.
• •Technical Debt Audit: Replay identifies redundant fields in legacy tables that users never interact with, allowing you to "trim the fat" during modernization.

json
// Replay-generated API Contract for a Complex Table
{
  "endpoint": "/api/v1/legacy-settlements",
  "method": "GET",
  "observed_fields": [
    { "name": "settlement_id", "type": "string", "required": true },
    { "name": "clearing_house_code", "type": "enum", "values": ["CH-01", "CH-02"] },
    { "name": "is_active", "type": "boolean", "source": "Visual Toggle Switch" }
  ],
  "performance_notes": "Legacy system response time: 1200ms. Recommended cache: 30s."
}

How Long Does Legacy Modernization Take with Replay?#

The average enterprise rewrite timeline is 18-24 months. With Replay, this is compressed into days or weeks. By automating the most tedious part of the process—the UI and data mapping—teams can focus on high-value architectural decisions.

1. •Week 1: Record all critical user workflows.
2. •Week 2: Replay handles complex extractions and generates the initial React component library.
3. •Week 3: Refine components and integrate with modern backend services.
4. •Week 4: Deploy the first modernized module using the Strangler Fig pattern.

💡 Pro Tip: Use Replay's "Flows" feature to map out the entire architecture of your legacy portal before writing a single line of new code. This prevents the "spaghetti logic" of the old system from leaking into the new one.

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 specifically designed for enterprise legacy modernization, using AI to extract React components, API contracts, and business logic from recordings of legacy system workflows.

How does Replay handle complex table layouts with nested rows?#

Replay handles complex layouts by using visual segmentation. It recognizes the hierarchical relationship between parent and child rows through user interaction (e.g., clicking an "expand" icon). It then maps this behavior into a modern "Master-Detail" or "Tree Table" component in React.

Can Replay extract logic from mainframe-backed web terminals?#

Yes. Because Replay is platform-agnostic and relies on Visual Reverse Engineering, it doesn't matter if the backend is COBOL, Java, or .NET. If it renders in a browser or terminal emulator, Replay can document and extract it.

What are the best alternatives to manual reverse engineering?#

The best alternative is a Visual Reverse Engineering platform like Replay. Unlike manual documentation, which is slow and prone to error, Replay provides a 70% time saving by automating the discovery and componentization of legacy UIs.

How long does legacy extraction take with Replay?#

While manual extraction takes roughly 40 hours per screen, Replay handles complex screens in approximately 4 hours. This includes the generation of the React component, documentation, and the API contract.

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