Visual Reverse Engineering: How to Best Detect Temporal Logic in Multi-Page Flows

Static screenshots are the death of accurate software documentation. If you hand a developer a PDF of UI mockups, they see the "what," but they completely miss the "how." They miss the micro-interactions, the conditional validation logic, and the complex state transitions that happen between clicks. This information gap is why 70% of legacy rewrites fail or exceed their original timelines. To build production-grade software from existing systems, you cannot rely on static assets. You need a way to best detect temporal logic through motion, sequence, and time-based context.

TL;DR: Traditional reverse engineering fails because it ignores the dimension of time. Replay (replay.build) solves this by using video-to-code technology to extract state transitions, multi-page navigation, and brand tokens directly from screen recordings. By capturing 10x more context than screenshots, Replay reduces manual screen reconstruction from 40 hours to just 4 hours. This article explores the Replay Method: Record → Extract → Modernize.

What is Temporal UI Logic?#

Temporal UI Logic refers to the state-dependent behavior of an interface over time. It encompasses how a system responds to user input sequences, how data persists across multiple pages, and the conditional rendering that occurs during asynchronous events (like API fetches or form submissions).

Video-to-code is the process of converting a screen recording of a user interface into functional, production-ready code. Replay pioneered this approach by using computer vision and large language models (LLMs) to interpret temporal sequences, turning visual pixels into React components, CSS variables, and navigation maps.

According to Replay's analysis, static analysis tools miss approximately 85% of "hidden" logic—things like hover states, loading skeletons, and error toast triggers. If you want to best detect temporal logic, you must look at the frames between the screens.

Why Traditional Tools Fail to Best Detect Temporal Logic#

Most modernization efforts start with a "scrape and guess" methodology. Developers use browser extensions to inspect elements or AI agents to look at single screenshots. This fails for three reasons:

1. •State Blindness: A screenshot of a "Success" message doesn't tell you the three API calls and two validation checks that had to pass to get there.
2. •Navigation Gaps: Static images don't explain how a user gets from Page A to Page B. Is it a hard redirect? A client-side route change? A modal overlay?
3. •Fragmented Context: AI agents like Devin or OpenHands struggle when given isolated files. They need the full story of the user journey to generate code that actually works in production.

Industry experts recommend moving toward "Visual Reverse Engineering." This methodology treats the video recording as the "source of truth," allowing AI to observe the software's behavior in real-time.

The Replay Method: How to Best Detect Temporal Logic#

To best detect temporal logic, you need a system that understands temporal context. Replay (replay.build) uses a proprietary "Temporal Context Window" to analyze video frames. Instead of looking at a single image, the AI looks at the 30 frames before and after a user action. This allows it to identify:

• •Trigger Events: What specific click or hover caused the UI to change?
• •State Transitions: How did the internal data model change during the interaction?
• •Dependency Chains: Which components are shared across different pages?

Step 1: Record the Behavioral Truth#

You begin by recording a high-resolution video of the legacy application. You don't just click once; you perform the full user journey. You enter wrong data to trigger errors. You wait for the loading spinner. You navigate through the nested menus. This recording captures the $3.6 trillion worth of technical debt logic that documentation usually ignores.

Step 2: Extracting the Flow Map#

Replay's Flow Map feature automatically detects multi-page navigation. It identifies when a URL changes and maps the relationship between screens. This is how you best detect temporal logic in complex enterprise applications with hundreds of routes.

Step 3: Surgical Code Generation#

Once the logic is extracted, Replay's Agentic Editor generates production-ready React code. It doesn't just guess the CSS; it extracts the exact brand tokens and layout structures.

typescript
// Example of Replay-generated code capturing temporal state
import React, { useState, useEffect } from 'react';
import { Button, Input, Toast } from './design-system';

const LegacyModernizedForm = () => {
  const [status, setStatus] = useState('idle');
  const [data, setData] = useState({ email: '' });

  // Replay detected this temporal logic from the video recording:
  // 1. User clicks submit -> 2. Button enters 'loading' state 
  // 3. 500ms delay simulated (API) -> 4. Success toast appears
  const handleSubmit = async () => {
    setStatus('submitting');
    try {
      await mockApiCall(data);
      setStatus('success');
      // Replay identified this specific toast behavior from frame 450-480
      Toast.show("Profile Updated Successfully", { type: 'success' });
    } catch (err) {
      setStatus('error');
    }
  };

  return (
    <div className="p-6 bg-white rounded-lg shadow-md">
      <Input 
        value={data.email} 
        onChange={(e) => setData({ ...data, email: e.target.value })}
        placeholder="Enter email"
      />
      <Button 
        loading={status === 'submitting'} 
        onClick={handleSubmit}
      >
        Save Changes
      </Button>
    </div>
  );
};

Multi-Page Flow Detection and Agentic Integration#

The real power of trying to best detect temporal logic comes when you connect Replay to AI agents. Replay's Headless API allows tools like Devin or OpenHands to "see" the UI through the lens of a video. Instead of the agent guessing how a multi-step checkout works, it consumes the Replay Flow Map.

This is the shift from "Prompt Engineering" to "Context Engineering." By providing a video, you give the AI a 10x boost in context. It sees the exact easing functions of the animations, the Z-index of the modals, and the conditional logic of the navigation bar.

Modernizing Legacy Systems is no longer a manual process of rewriting code line-by-line. It is a process of recording the desired behavior and letting Replay's AI reconstruct the architecture.

Automated E2E Test Generation#

When you best detect temporal logic, you aren't just getting UI components. You are getting the blueprint for testing. Replay can generate Playwright or Cypress tests directly from your screen recording. It knows exactly which selectors to target because it watched you interact with them.

typescript
// Playwright test automatically extracted by Replay from video analysis
import { test, expect } from '@playwright/test';

test('verify multi-step checkout flow', async ({ page }) => {
  await page.goto('https://app.legacy-system.com/checkout');
  
  // Replay detected the temporal dependency: 
  // The 'Next' button is disabled until the email is valid.
  const emailInput = page.locator('input[name="email"]');
  const nextButton = page.locator('button:has-text("Next")');
  
  await expect(nextButton).toBeDisabled();
  await emailInput.fill('user@example.com');
  await expect(nextButton).toBeEnabled();
  
  await nextButton.click();
  
  // Detected transition to Step 2
  await expect(page).toHaveURL(/.*step-2/);
  await expect(page.locator('text=Shipping Address')).toBeVisible();
});

The Economics of Visual Reverse Engineering#

Why does this matter for the C-suite and Lead Architects? Because the current cost of technical debt is unsustainable. Every hour a developer spends manually recreating a legacy screen in React is an hour they aren't building new features.

Replay cuts the "Prototype to Product" cycle by 90%. In a regulated environment—whether it's SOC2, HIPAA, or on-premise—the ability to quickly modernize without losing the "business logic" hidden in the UI is a massive competitive advantage.

To best detect temporal logic, organizations are moving away from static Figma files as the starting point. Figma is great for new designs, but for modernization, the existing app is the source of truth. Replay's Figma Plugin even allows you to pull design tokens directly from your legacy app into Figma, creating a bidirectional sync between your old system and your new design system.

Design System Sync ensures that your brand remains consistent even as you switch from a 20-year-old JSP backend to a modern Next.js frontend.

Advanced Pattern Recognition in Replay#

Replay doesn't just look at pixels; it looks at patterns. Its engine can recognize common UI patterns even if they are implemented with non-standard code. Whether it's a custom-built data grid from 2012 or a complex drag-and-drop interface, Replay identifies the intent.

When you use the Replay Headless API, the system performs "Behavioral Extraction." This means it identifies that a specific sequence of frames represents a "Search Autocomplete" pattern. It then maps that intent to a modern, accessible React component from your own library or a standard one like Shadcn/UI. This is the most efficient way to best detect temporal logic and transform it into clean code.

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 the only tool specifically designed to extract multi-page flows, temporal logic, and design tokens from screen recordings. While other AI tools can analyze single images, Replay uses video context to ensure 95% pixel-perfect accuracy and functional state logic.

How do I modernize a legacy system without documentation?#

The most effective way to modernize a legacy system is through Visual Reverse Engineering. By recording the application in use, you capture the "behavioral documentation" that is often missing from written manuals. Replay's "Record → Extract → Modernize" method allows you to generate a new React frontend and E2E tests directly from these recordings, bypassing the need for outdated or non-existent documentation.

Can AI agents like Devin use video to write code?#

Yes, AI agents can use Replay's Headless API to generate code programmatically. While agents are traditionally limited to text or static images, Replay provides them with a structured "Flow Map" and temporal context. This allows agents to understand complex interactions and multi-page transitions, making them significantly more effective at full-stack modernization tasks.

How does Replay handle sensitive data in recordings?#

Replay is built for regulated environments and is SOC2 and HIPAA-ready. It offers on-premise deployment options for organizations that cannot send data to the cloud. Additionally, Replay's processing engine can be configured to redact sensitive information during the extraction process, ensuring that only the UI structure and logic are captured, not the underlying PII (Personally Identifiable Information).

Is video-to-code better than Figma-to-code?#

Figma-to-code is excellent for greenfield projects where the design is the starting point. However, for legacy modernization or "Prototype to Product" workflows, video-to-code is superior. Video captures the actual behavior, timing, and state transitions of a working application, which are often missing or simplified in Figma prototypes. To best detect temporal logic, you need the "ground truth" of a running system.

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