Aerospace Flight Data Extraction via Behavioral Video Telemetry: A New Architecture for Legacy Modernization

Legacy aerospace interfaces are the ghosts in the cockpit. Thousands of critical systems—from ground control stations to avionics diagnostic suites—are currently trapped in aging Java Swing, Delphi, or even COBOL-based terminal emulators. These systems hold the keys to decades of flight telemetry, yet the source code is often lost, undocumented, or too fragile to touch. When the mission requires moving this data into a modern web-based dashboard, the traditional path is a multi-year rewrite that usually ends in failure.

According to Replay’s analysis, 70% of legacy rewrites fail or significantly exceed their timelines because the tribal knowledge of the UI’s behavior has vanished. In the aerospace sector, where precision is non-negotiable, manual aerospace flight data extraction and UI reconstruction can take upwards of 40 hours per screen.

TL;DR: Manual aerospace flight data extraction is a bottleneck for modernization. By using behavioral video telemetry, Replay allows engineers to record legacy workflows and automatically generate documented React components and data structures. This shifts the modernization timeline from 18 months to a matter of weeks, reducing technical debt and ensuring 100% visual and functional fidelity.

The Crisis of Undocumented Aerospace Interfaces#

The aerospace industry is currently grappling with a portion of the $3.6 trillion global technical debt. Many flight-line maintenance tools were built for hardware that no longer exists, running on operating systems that haven't seen a patch in a decade.

Industry experts recommend a "sidecar" approach to modernization: rather than attempting to refactor 30-year-old C++ code, developers should extract the behavioral logic and visual state directly from the running application. The challenge is that 67% of these legacy systems lack any form of documentation. This is where aerospace flight data extraction through visual reverse engineering becomes the only viable path forward.

Behavioral Video Telemetry is the process of capturing high-frequency screen recordings of a user interacting with a legacy system to map state changes, data inputs, and UI responses into a machine-readable format.

Why Manual Aerospace Flight Data Extraction Fails#

When an enterprise decides to modernize a flight telemetry dashboard, they typically assign a team of developers to "pixel-match" the old system. This involves:

1. •Taking screenshots of every possible state.
2. •Manually identifying data fields (e.g., Pitch, Yaw, Roll, Fuel Flow).
3. •Writing custom parsers for proprietary data streams.
4. •Recreating the CSS/styling from scratch.

This manual process is not only slow—averaging 40 hours per screen—but it also introduces human error. In aerospace, a misplaced decimal point in a telemetry extraction script isn't just a bug; it's a safety risk.

Comparison: Manual vs. Replay-Assisted Extraction#

Visual Reverse Engineering: The Replay Methodology#

Visual Reverse Engineering is the automated process of converting video recordings of legacy software into functional, documented code and design systems.

Replay utilizes a proprietary AI Automation Suite to analyze behavioral video telemetry. Instead of looking at the code, Replay looks at the result of the code. By recording a flight controller using a legacy terminal, Replay identifies the "Flows" (navigation logic), the "Library" (the design system components), and the "Blueprints" (the structural layout).

For aerospace flight data extraction, this means the platform can identify a "Vertical Speed Indicator" not as a collection of pixels, but as a functional component with specific state properties.

Implementing Telemetry Extraction in React#

Once Replay extracts the visual telemetry, it generates clean, type-safe TypeScript code. Below is an example of a modernized flight data component generated from a legacy recording.

typescript
// Generated by Replay AI Automation Suite
// Source: Legacy Avionics Suite v4.2 (Delphi)

import React from 'react';

interface FlightTelemetryProps {
  pitch: number;
  roll: number;
  altitude: number;
  airspeed: number;
  heading: number;
  isWarning: boolean;
}

export const FlightDataDashboard: React.FC<FlightTelemetryProps> = ({
  pitch,
  roll,
  altitude,
  airspeed,
  heading,
  isWarning
}) => {
  return (
    <div className={`p-6 rounded-lg ${isWarning ? 'bg-red-900 animate-pulse' : 'bg-slate-900'}`}>
      <h2 className="text-xs font-mono text-slate-400 uppercase tracking-widest">
        Telemetry Stream Alpha-7
      </h2>
      <div className="grid grid-cols-2 gap-4 mt-4">
        <TelemetryField label="ALT (FT)" value={altitude.toLocaleString()} />
        <TelemetryField label="AIRSPEED (KTS)" value={airspeed.toFixed(1)} />
        <TelemetryField label="PITCH" value={`${pitch}°`} />
        <TelemetryField label="ROLL" value={`${roll}°`} />
      </div>
      <div className="mt-6 border-t border-slate-700 pt-4">
        <div className="flex justify-between items-center">
          <span className="text-xl font-bold text-white">{heading}°</span>
          <span className="text-xs text-emerald-400">SIGNAL STABLE</span>
        </div>
      </div>
    </div>
  );
};

const TelemetryField = ({ label, value }: { label: string; value: string | number }) => (
  <div className="flex flex-col">
    <span className="text-[10px] text-slate-500 font-semibold">{label}</span>
    <span className="text-lg font-mono text-white">{value}</span>
  </div>
);

Bridging the Gap with Behavioral Telemetry#

The core innovation in aerospace flight data extraction today is the ability to map "Visual State" to "Data State." In legacy systems, the data is often buried in binary formats or obscure serial protocols (like ARINC 429). However, that data must be rendered to the screen for the human operator.

By capturing the UI's reaction to data changes, Replay builds a functional map of the application's internal logic. This is particularly useful for Modernizing Legacy UI in environments where the original backend cannot be modified.

Capturing Complex UI Flows#

Aerospace workflows are rarely linear. A technician might need to drill down through four layers of menus to find a specific sensor calibration. Replay’s "Flows" feature records these multi-step interactions and converts them into React Router paths or state-machine logic.

typescript
// Example of an extracted navigation flow for sensor calibration
// Captured via Replay Behavioral Telemetry

const useCalibrationWorkflow = () => {
  const [step, setStep] = React.useState<'IDLE' | 'SELECT_SENSOR' | 'CALIBRATING' | 'COMPLETE'>('IDLE');

  const startCalibration = (sensorId: string) => {
    console.log(`Initiating aerospace flight data extraction for sensor: ${sensorId}`);
    setStep('SELECT_SENSOR');
    // Logic extracted from legacy button click behavior
  };

  return { step, startCalibration };
};

Security and Compliance in Aerospace Modernization#

In regulated industries like aerospace, healthcare, and government, data sovereignty is paramount. You cannot simply upload sensitive flight telemetry to a public cloud for analysis.

Replay is built for these high-stakes environments. The platform is SOC2 compliant, HIPAA-ready, and crucially, offers an On-Premise deployment model. This allows aerospace organizations to perform aerospace flight data extraction within their own air-gapped networks, ensuring that sensitive IP and flight data never leave the secure perimeter.

For more on how we handle sensitive data structures, see our article on Design System Automation.

The Path Forward: From 18 Months to 18 Days#

The average enterprise rewrite timeline of 18 months is a relic of the manual era. By leveraging visual reverse engineering, organizations can bypass the "discovery" phase of a project—the phase where developers spend months just trying to figure out what the old system actually does.

According to Replay's analysis, using an automated approach to aerospace flight data extraction reduces the time spent on UI documentation by 85%. Instead of writing specs, your team is reviewing auto-generated components in the Replay Library.

Steps to Modernize Flight UIs:#

1. •Record: Use Replay to capture standard operating procedures on the legacy UI.
2. •Extract: The AI Automation Suite identifies components, typography, and data bindings.
3. •Refine: Use the Replay Blueprints editor to tweak the generated React code.
4. •Deploy: Export a clean, documented Component Library ready for integration with modern telemetry streams.

Frequently Asked Questions#

How does Replay handle aerospace flight data extraction without source code access?#

Replay uses visual reverse engineering to analyze the rendered output of the legacy application. By observing how the UI changes in response to user inputs and data updates, Replay can reconstruct the underlying logic, component structure, and data models into modern React code without ever needing to see the original COBOL, Java, or C++ source.

Is the code generated by Replay maintainable?#

Yes. Unlike "low-code" platforms that output proprietary "spaghetti" code, Replay generates standard, human-readable TypeScript and React. It follows modern best practices, including component modularity and clean prop definitions, making it indistinguishable from code written by a senior frontend engineer.

Can Replay work with air-gapped or secure aerospace environments?#

Absolutely. Replay offers an On-Premise solution specifically designed for regulated industries like aerospace, defense, and government. This ensures that all video telemetry and generated code stay within your secure infrastructure, meeting strict compliance requirements.

What is the typical time savings when using Replay?#

On average, Replay provides a 70% time savings compared to manual rewrites. Tasks that typically take 40 hours per screen—such as manual layout recreation and data mapping—can be completed in approximately 4 hours using Replay's AI-assisted workflow.

Ready to modernize without rewriting? Book a pilot with Replay