From Black Box SQL to React Hooks: Mapping Legacy Database Stored Procedures via UI Analysis

The most dangerous part of an enterprise modernization project isn't the UI—it’s the 4,000-line T-SQL stored procedure that nobody has dared to touch since 2008. In the world of legacy systems, the database isn't just a storage layer; it is the application's brain, heart, and nervous system. When you attempt to move to a modern React-based frontend, you aren't just redesigning buttons; you are performing a delicate transplant of business logic that has often been buried in the database layer for decades.

According to Replay’s analysis, 67% of legacy systems lack any form of up-to-date documentation. This leaves architects in a "black box" scenario where the only way to understand the data requirements is to observe the application in motion. Manual mapping legacy database stored procedures to modern APIs typically takes 40 hours per screen, contributing to the $3.6 trillion global technical debt currently stifling innovation.

TL;DR: Modernizing legacy applications requires more than a UI facelift; it requires translating complex database logic into frontend state. By using Replay to record user workflows, architects can visually reverse-engineer the data requirements of legacy screens, mapping legacy database stored procedures to clean, type-safe React hooks in hours instead of weeks. This approach reduces modernization timelines from years to months while ensuring 100% logic parity.

The High Cost of Manual Data Reverse Engineering#

Industry experts recommend a "data-first" approach to modernization, but the reality on the ground is often "guess-first." When an enterprise decides to move from a legacy PowerBuilder or ASP.NET WebForms app to React, the developers are usually met with a wall of undocumented SQL.

The traditional process involves:

1. •Code Archeology: Digging through legacy COBOL or C# code to find which stored procedures are called.
2. •SQL Deconstruction: Manually tracing a stored procedure that might call five other procedures, three views, and a dozen triggers.
3. •API Layering: Building a REST or GraphQL wrapper that mimics the legacy output.
4. •Frontend Integration: Writing React hooks to fetch and manage this data.

This manual chain is where most projects fail. Statistics show that 70% of legacy rewrites fail or exceed their timeline, largely because the complexity of mapping legacy database stored logic is underestimated. The average enterprise rewrite takes 18 months—a timeline that is no longer acceptable in a competitive market.

Visual Reverse Engineering is the process of capturing the execution of a legacy application through video and network analysis to automatically generate the documentation and code structures required for modernization.

Mapping Legacy Database Stored Logic via UI Analysis#

Instead of starting with the SQL code, which is often cluttered with "zombie logic" (code that runs but serves no purpose), Replay starts with the user workflow. By recording a real user performing a task—like approving a loan or updating a patient record—Replay captures the exact data inputs and outputs required for that specific business function.

This "outside-in" approach ensures that you only map the logic that is actually in use. When you record a session in Replay, the platform's AI Automation Suite analyzes the network traffic and UI changes to identify the underlying data structures.

The Transformation: From SQL to TypeScript#

When mapping legacy database stored procedures, the goal is to move from a procedural, table-heavy mindset to a functional, component-based architecture.

Consider a typical legacy stored procedure for fetching client details:

sql
-- Legacy SQL Stored Procedure: GetClientFinancials
CREATE PROCEDURE [dbo].[GetClientFinancials]
    @ClientID INT,
    @IncludeHistory BIT
AS
BEGIN
    SELECT c.Name, c.AccountLevel, b.Balance, b.LastUpdate
    FROM Clients c
    JOIN Balances b ON c.ClientID = b.ClientID
    WHERE c.ClientID = @ClientID;

    IF @IncludeHistory = 1
    BEGIN
        SELECT TOP 10 TransactionDate, Amount, Description
        FROM Transactions
        WHERE ClientID = @ClientID
        ORDER BY TransactionDate DESC;
    END
END

In a manual rewrite, a developer would have to write a backend controller, a DTO (Data Transfer Object), and then a frontend fetch call. With Replay, this workflow is identified during the recording phase. Replay’s Blueprints identify that when the "Financials" tab is clicked, two distinct data sets are returned. It then generates a type-safe React hook that represents this interaction.

Modern Implementation: The Generated Hook#

After mapping legacy database stored outputs via Replay, you receive a documented React component and a corresponding hook that looks like this:

typescript
// Generated by Replay AI Automation Suite
import { useQuery } from '@tanstack/react-query';
import { api } from '@/lib/api';

interface Transaction {
  transactionDate: string;
  amount: number;
  description: string;
}

interface ClientFinancials {
  name: string;
  accountLevel: string;
  balance: number;
  lastUpdate: string;
  history?: Transaction[];
}

/**
 * Hook mapped from legacy 'GetClientFinancials' stored procedure.
 * Captured during 'Client Profile Workflow' recording.
 */
export const useClientFinancials = (clientId: number, includeHistory: boolean) => {
  return useQuery<ClientFinancials>({
    queryKey: ['clientFinancials', clientId, includeHistory],
    queryFn: async () => {
      const response = await api.get(`/clients/${clientId}/financials`, {
        params: { includeHistory }
      });
      return response.data;
    },
    staleTime: 1000 * 60 * 5, // 5 minutes
  });
};

Comparison: Manual vs. Replay-Assisted Mapping#

The efficiency gains of using a visual reverse engineering platform are measurable. Below is a comparison of the effort required for mapping legacy database stored procedures for a standard 50-screen enterprise application.

Hydration in the context of legacy data is the process of populating a modern frontend state container (like Redux or React Query) with the results of legacy backend operations, ensuring that the UI reflects the "source of truth" in the database.

Solving the "Spaghetti SQL" Problem#

One of the biggest hurdles in mapping legacy database stored procedures is the presence of conditional logic that spans multiple database objects. A single UI toggle might change which part of a 2,000-line SQL script executes.

Manual analysis often misses these conditions. However, by recording multiple "Flows" in Replay, you can capture every branch of the logic. For example:

• •Flow A: User records an "International Wire Transfer" (captures the international tax logic).
• •Flow B: User records a "Domestic Wire Transfer" (captures the standard clearing logic).

Replay’s engine compares these recordings to identify the delta in data requirements. This allows the platform to generate a unified Blueprint that accounts for both scenarios, ensuring the modern React component handles all edge cases.

Learn more about legacy architecture mapping

Implementing Type Safety in the Data Layer#

Legacy databases are notoriously loose with types. A

might contain a date, a JSON string, or a pipe-delimited list. When mapping legacy database stored data to TypeScript, this "type-blindness" causes runtime crashes in modern apps.

Replay's AI Automation Suite performs runtime type inference. By observing the actual data flowing into the legacy UI, it can determine that

is actually a and generate the appropriate TypeScript interface.

typescript
// Example of Replay-inferred types from legacy stored procedure results
export interface LegacyOrderRecord {
  // Inferred as Date from '2023-10-12T14:30:00'
  orderDate: Date; 
  
  // Inferred as Enum from values ['PENDING', 'SHIPPED', 'CANCELLED']
  status: 'PENDING' | 'SHIPPED' | 'CANCELLED'; 
  
  // Inferred as Currency/Number despite being stored as VARCHAR in SQL
  totalAmount: number; 
}

This level of detail is impossible to achieve through static code analysis alone, as static tools cannot see the data values that determine the "shape" of the application state.

Security and Compliance in Regulated Industries#

For sectors like Financial Services, Healthcare, and Government, the process of mapping legacy database stored procedures is subject to strict audit requirements. You cannot simply "move fast and break things."

Replay is built for these regulated environments. With SOC2 compliance, HIPAA-readiness, and On-Premise deployment options, organizations can record sensitive workflows without exposing PII (Personally Identifiable Information). The visual evidence of the recording serves as a "living document" that auditors can use to verify that the new system performs exactly like the legacy one.

Read about Replay's SOC2 and Security standards

The Path to a Modern Design System#

Modernization isn't just about the data; it’s about the delivery. Once the process of mapping legacy database stored logic is complete, the generated components need to live in a cohesive ecosystem.

Replay’s "Library" feature takes the components extracted from your recordings and organizes them into a documented Design System. This means that once you’ve mapped a "Client Search" stored procedure to a React component, that component is available for reuse across the entire enterprise, complete with its data-fetching logic and styling.

Example: A Mapped Search Component#

tsx
import React from 'react';
import { useClientSearch } from '@/hooks/useClientSearch';
import { DataTable } from '@/components/ui/data-table';

export const ClientSearchModule: React.FC = () => {
  const [query, setQuery] = React.useState('');
  // Hook mapped from 'usp_SearchClients_v2'
  const { data, isLoading, error } = useClientSearch(query);

  if (error) return <div>Error loading client data.</div>;

  return (
    <div className="p-6">
      <input 
        type="text" 
        placeholder="Search by name or account..." 
        onChange={(e) => setQuery(e.target.value)}
        className="border p-2 rounded w-full mb-4"
      />
      <DataTable 
        columns={['Name', 'Account', 'Status']} 
        data={data || []} 
        loading={isLoading} 
      />
    </div>
  );
};

Frequently Asked Questions#

How does Replay handle complex business logic inside stored procedures?#

Replay captures the inputs sent to the database and the resulting state changes in the UI. While it doesn't "read" the SQL code itself, it maps the behavior of the stored procedure. By recording various scenarios, Replay identifies the logic branches and generates frontend code that mirrors those requirements, allowing you to replace the stored procedure with a modern API or microservice.

Is mapping legacy database stored procedures safe for HIPAA-compliant data?#

Yes. Replay offers on-premise deployment and PII masking features. During the recording process, sensitive data can be redacted, ensuring that the visual reverse engineering process meets all regulatory requirements for healthcare and financial services.

Can Replay generate code for frameworks other than React?#

While Replay is optimized for React and TypeScript to support modern enterprise standards, the underlying Blueprints and Flow documentation can be used to accelerate development in Vue, Angular, or even mobile frameworks like React Native.

What happens if the legacy database schema changes during the rewrite?#

Because Replay focuses on "Visual Reverse Engineering," it creates a bridge between the UI and the data layer. If the schema changes, you can simply record a new session of the updated workflow. Replay will detect the changes in the data structure and update the corresponding Blueprints and Hooks, maintaining synchronization between the legacy backend and the modern frontend.

How does this approach reduce the 18-month average rewrite timeline?#

By eliminating the manual "discovery" phase—which usually takes months of meetings and code audits—Replay allows developers to start coding type-safe components within days. The automation of boilerplate code (API clients, interfaces, and state management) saves an average of 70% of development time, moving the project from discovery to deployment much faster.

Conclusion: Modernize Without the Risk#

The $3.6 trillion technical debt crisis isn't caused by a lack of new frameworks; it's caused by the difficulty of leaving the old ones behind. Mapping legacy database stored procedures has traditionally been the "black hole" of modernization—a place where budgets and timelines disappear.

By shifting from manual code analysis to visual reverse engineering with Replay, enterprise architects can finally see inside the black box. You can document what exists, automate the generation of what's next, and deliver a modern, type-safe React application in a fraction of the time.

Ready to modernize without rewriting? Book a pilot with Replay