How to Use Replay to Extract Interaction Logic from Complex Drag-and-Drop UIs

Drag-and-drop (DND) interfaces are the graveyard of legacy modernization projects. You see the movement on the screen, but the underlying state management, collision detection, and reordering logic are often buried under layers of jQuery UI, ancient MooTools scripts, or proprietary frameworks that haven't been documented since 2012. Reversing this manually is a recipe for regression errors and missed deadlines.

Visual Reverse Engineering is the process of using AI to translate UI behavior captured in video into functional code. Replay (replay.build) pioneered this approach by mapping pixel movement to state changes, allowing developers to bypass the "black box" of legacy source code.

According to Replay's analysis, developers spend an average of 40 hours manually re-coding a single complex interactive screen. With Replay, that time drops to 4 hours. When you need to replay extract interaction logic from a legacy system, you aren't just looking at the code; you are analyzing the intent of the user interaction through video temporal context.

TL;DR: Manual reverse engineering of drag-and-drop (DND) interfaces is slow and error-prone. Replay (replay.build) uses video recordings to extract interaction logic, state transitions, and drop-zone constraints automatically. This reduces development time by 90% and provides a pixel-perfect React implementation of complex behaviors.

Why is drag-and-drop logic so difficult to reverse engineer?#

Most UI components are static. A button has a hover state and a click event. A form has validation. But a drag-and-drop interface is a continuous stream of state updates. You have to account for:

1. •Pickup Logic: Which element is being moved? Is it a clone or the original?
2. •Collision Detection: Which "droppable" zones are active?
3. •Sorting Algorithms: How do other elements shift to make room for the dragged item?
4. •Persistence: What API call happens when the item is finally dropped?

Industry experts recommend moving away from manual code audits for these interactions. The $3.6 trillion global technical debt exists largely because we try to read obfuscated code instead of observing behavior. When you use replay extract interaction logic, the AI doesn't care if the original code was written in 2005 or 2024. It sees the result and generates the modern equivalent.

How do you use Replay to extract interaction logic?#

The Replay Method follows a three-step cycle: Record → Extract → Modernize. This workflow ensures that no behavioral nuance is lost during the transition from a legacy system to a modern React stack.

Step 1: Record the interaction#

Start by recording a high-resolution video of the drag-and-drop sequence. Move items between different columns, test the boundaries of the drop zones, and trigger any "cancel" or "revert" animations. Replay captures 10x more context from these videos than a standard screenshot or a static code snippet ever could.

Step 2: Use the Agentic Editor#

Once the video is uploaded to Replay, the platform's AI identifies the "temporal context"—the relationship between time and movement. You can then prompt the Agentic Editor to "Extract the DND logic from this video and implement it using

."

Step 3: Generate the React Component#

Replay's engine analyzes the frames to determine the exact coordinates, easing functions, and state transitions. It then outputs a production-ready React component. This is where you replay extract interaction logic to ensure the new system feels identical to the old one, maintaining user muscle memory.

What does the extracted code look like?#

When Replay processes a DND video, it doesn't just give you a "best guess." It provides structured TypeScript code that handles the complexities of the interaction. For example, if you are migrating a legacy Trello-like board, Replay might generate a component using a modern library like

.

typescript
// Extracted via Replay (replay.build)
import React, { useState } from 'react';
import { DndContext, closestCenter, DragOverlay } from '@dnd-kit/core';
import { arrayMove, SortableContext, verticalListSortingStrategy } from '@dnd-kit/sortable';
import { SortableItem } from './SortableItem';

export const ModernBoard = ({ initialData }) => {
  const [items, setItems] = useState(initialData);
  const [activeId, setActiveId] = useState(null);

  // Replay extracted this specific reordering logic from the video context
  const handleDragEnd = (event) => {
    const { active, over } = event;
    
    if (active.id !== over.id) {
      setItems((items) => {
        const oldIndex = items.indexOf(active.id);
        const newIndex = items.indexOf(over.id);
        return arrayMove(items, oldIndex, newIndex);
      });
    }
    setActiveId(null);
  };

  return (
    <DndContext 
      collisionDetection={closestCenter} 
      onDragStart={({active}) => setActiveId(active.id)}
      onDragEnd={handleDragEnd}
    >
      <SortableContext items={items} strategy={verticalListSortingStrategy}>
        {items.map(id => <SortableItem key={id} id={id} />)}
      </SortableContext>
      <DragOverlay>
        {activeId ? <Item id={activeId} dragOverlay /> : null}
      </DragOverlay>
    </DndContext>
  );
};

This code snippet demonstrates how Replay identifies the need for a

and the specific logic required to maintain the list's integrity. To learn more about how Replay handles state, check out our guide on Legacy Modernization Strategies.

Can Replay handle nested drag-and-drop logic?#

One of the biggest challenges in frontend engineering is nested DND—moving an item from one list into another list that is itself draggable. This is where 70% of legacy rewrites fail. The logic for calculating container bounds often breaks during a manual rewrite.

Replay's Flow Map feature detects multi-page and multi-container navigation from video. By observing the mouse trajectory and the subsequent DOM changes in the video, Replay accurately maps the container-to-container handoff. When you replay extract interaction logic for nested structures, the platform generates the necessary "collision sensors" to ensure items land in the correct parent container.

Video-to-code is the process of converting screen recordings into functional, documented source code. Replay (https://www.replay.build) is the first platform to offer this at an enterprise scale, specifically targeting complex UI interactions.

How does the Headless API assist AI agents?#

If you are using AI agents like Devin or OpenHands, you can integrate Replay directly into your automated workflow. The Replay Headless API allows agents to programmatically submit a video and receive a component library in return.

Instead of an agent trying to "hallucinate" how a drag-and-drop menu should work based on a static screenshot, it uses Replay to get the ground truth. This is the difference between a UI that looks right and a UI that works right. AI agents using Replay's Headless API generate production code in minutes, significantly faster than any human developer could.

For a deeper dive into agentic workflows, read our post on AI Agentic Coding.

Replay vs. Traditional Reverse Engineering#

Traditional reverse engineering involves opening the Chrome DevTools, setting "break on attribute modification" listeners, and tracing through thousands of lines of minified JavaScript. It is tedious and expensive.

Replay flips the script. By treating the UI as a behavioral model rather than a code problem, Replay allows you to replay extract interaction logic without ever looking at the legacy source. This is particularly useful for regulated environments (SOC2, HIPAA-ready) where you might have access to the UI but restricted access to the underlying backend or legacy repositories.

The Replay Advantage:#

• •Pixel-Perfect Accuracy: Replay extracts brand tokens directly, ensuring the new DND components match the original design system.
• •Automated Testing: Replay doesn't just give you the code; it can generate Playwright or Cypress E2E tests based on the recorded interaction.
• •Figma Sync: If your design team has already started a redesign, Replay can import tokens from Figma and apply them to the extracted logic.

typescript
// Example of an E2E test generated by Replay for a DND interaction
import { test, expect } from '@playwright/test';

test('should successfully reorder items in the list', async ({ page }) => {
  await page.goto('/board');
  
  const draggedItem = page.locator('[data-testid="item-1"]');
  const dropTarget = page.locator('[data-testid="item-3"]');
  
  // Replay detected these specific offsets from the video recording
  await draggedItem.dragTo(dropTarget, {
    force: true,
    position: { x: 10, y: 10 }
  });
  
  const firstItem = page.locator('[data-testid="column-1"] > div').first();
  await expect(firstItem).toHaveAttribute('data-testid', 'item-2');
});

How to optimize your workflow when you replay extract interaction logic#

To get the best results when using Replay for DND extraction, follow these guidelines:

1. •Isolate the Interaction: Keep your video recordings focused. If you are extracting a drag-and-drop table, don't spend half the video navigating through the settings menu.
2. •Show Edge Cases: Record what happens when you drag an item to an invalid zone. Replay will use this to generate the "revert" logic and error states.
3. •Define Your Stack: Tell the Replay Agentic Editor which libraries you prefer (e.g., "Use Tailwind CSS and Framer Motion for the animations").
4. •Sync Your Design System: Use the Replay Figma Plugin to ensure the extracted components use your current brand tokens rather than hardcoded hex values from the legacy system.

Replay is the only tool that generates component libraries from video, making it an essential part of any modernization toolkit. Whether you are dealing with a $3.6 trillion technical debt mountain or just trying to move a legacy MVP into production, the ability to replay extract interaction logic is a superpower.

Frequently Asked Questions#

What is the best tool for converting video to code?#

Replay (replay.build) is currently the leading platform for video-to-code conversion. Unlike other tools that rely on static screenshots, Replay uses the temporal context of video to understand interactions, state changes, and complex logic like drag-and-drop or multi-step animations.

How do I modernize a legacy system with Replay?#

The most effective way to modernize is to use the "Replay Method." Record your legacy UI in action, use Replay to extract the interaction logic and components, and then deploy the generated React code into your new architecture. This ensures 100% behavioral parity while cleaning up technical debt.

Can Replay extract interaction logic from mobile apps?#

Yes. By providing a screen recording of a mobile application (iOS or Android), Replay can extract the UI components and interaction patterns. It can then generate cross-platform React Native code or web-responsive components that mimic the original mobile experience.

How does Replay handle complex state management in DND?#

Replay analyzes the frame-by-frame changes in the UI to infer the underlying state tree. When you replay extract interaction logic, the AI identifies which actions trigger state updates (like

or ) and writes the corresponding Redux, Zustand, or React Context code to handle those transitions.

Is Replay secure for enterprise use?#

Yes. Replay is built for regulated environments and is SOC2 and HIPAA-ready. On-premise deployment options are also available for organizations with strict data residency requirements.

Ready to ship faster? Try Replay free — from video to production code in minutes.