MoreRSS

site iconThe Practical DeveloperModify

A constructive and inclusive social network for software developers.
Please copy the RSS to your reader, or quickly subscribe to:

Inoreader Feedly Follow Feedbin Local Reader

Rss preview of Blog of The Practical Developer

CES 2026: My top 5 picks!

2026-01-14 14:13:02

#ces #ces2026 #techtrends | Jigyasa Grover

CES 2026 just wrapped up ... and I can't stop thinking about how the timeline between "impossible" →← "shipping next quarter" is just collapsing! Here are the top 5 things that caught my fancy 🤩 • the LEGO Group bricks that react to how you play with them. Chips smaller than a stud + built-in sensors. Swing a lightsaber & it hums in real-time. No app, no screen. Just intelligent physical play. • Paper batteries already in production w Logitech & Amazon. Biodegradable, non-flammable batteries + zero lithium. If this scales, we're watching a supply chain get rewritten in real time. • Robot vacuum climbing stairs. Roborock's Saros Rover deployed wheel-legs & hopped up 5 steps in 40s while vacuuming each one. The impossible will just become mundane. • Your car's windshield is about to replace the dashboard. BMW Group's full-AR HUD projects navigation exactly where you need it on the road ahead. Not on a screen. On reality. • Your bathroom mirror will diagnose you. Smart mirrors, needle-free injections & ambient health tracking that catches illness before symptoms appear. Healthcare is shifting from reactive to invisible. The pattern? Companies that treated AI as a feature to bolt on are getting lapped by companies rebuilding products, assuming AI exists from day 1. The gap isn't closing. It's accelerating ⚡️ #CES #CES2026 #TechTrends

favicon linkedin.com

CES 2026 just wrapped up ... and I can't stop thinking about how the timeline between "impossible" →← "shipping next quarter" is just collapsing!

Here are the top 5 things that caught my fancy 🤩

• LEGO bricks that react to how you play with them. Chips smaller than a stud + built-in sensors. Swing a lightsaber & it hums in real-time. No app, no screen. Just intelligent physical play.

• Paper batteries already in production w Logitech & Amazon. Biodegradable, non-flammable batteries + zero lithium. If this scales, we're watching a supply chain get rewritten in real time.

• Robot vacuum climbing stairs. Roborock's Saros Rover deployed wheel-legs & hopped up 5 steps in 40s while vacuuming each one. The impossible will just become mundane.

• Your car's windshield is about to replace the dashboard. BMW Group's full-AR HUD projects navigation exactly where you need it on the road ahead. Not on a screen. On reality.

• Your bathroom mirror will diagnose you. Smart mirrors, needle-free injections & ambient health tracking that catches illness before symptoms appear. Healthcare is shifting from reactive to invisible.

The pattern? Companies that treated AI as a feature to bolt on are getting lapped by companies rebuilding products, assuming AI exists from day 1.

The gap isn't closing. It's accelerating ⚡️

The Ultimate Guide to Shopify Cart Debugging: How to Save Hours with Shopify Theme Devtools Cart Panel

2026-01-14 14:12:54

TL;DR: Stop console.logging your cart state. Shopify Theme Devtools gives you a visual cart inspector, history tracking, test automation, and scenario management—all in your browser while developing themes.

Introduction: Why Cart Debugging is Painful

If you've developed Shopify themes, you know the pain:

  • Manually adding products to test cart states
  • Using console.log({{ cart | json }}) to debug
  • Rebuilding complex carts after every page refresh
  • No way to test edge cases like gift-with-purchase items or subscriptions
  • Tracking down which JavaScript is modifying your cart

Shopify Theme Devtools solves all of this with a dedicated Cart Panel that transforms how you debug and test cart functionality.

What is Shopify Theme Devtools?

Shopify Theme Devtools is an open-source, in-browser developer panel for Shopify theme development. Think of it as Chrome DevTools, but specifically designed for Liquid and Shopify.

The Cart Panel is one of its most powerful features—a complete cart management and debugging toolkit that runs directly in your development theme.

Key Features:

  • Real-time cart state inspection
  • Visual cart history with diff tracking
  • Saveable cart scenarios for testing
  • Automated cart validation tests
  • AJAX request interception
  • One-click cart restoration

Getting Started

Installation

npx shopify-theme-devtools init

This adds the Liquid snippet to your theme. The devtools only render on unpublished themes, so your live store is never affected.

Accessing the Cart Panel

Once installed, you'll see a floating devtools panel on your development theme. Click the Cart tab to access all cart debugging features.

Feature 1: Real-Time Cart Inspector

The Problem

Debugging cart state usually means adding {{ cart | json }} to your template, refreshing, copying the JSON, and pasting it into a formatter. Repeat for every change.

The Solution

The Cart Panel shows your complete cart state in a clean, interactive interface:

At a glance, you see:

  • Total items and price
  • Currency and total weight
  • Active discount codes with savings
  • Cart attributes and notes

For each line item:

  • Product thumbnail, title, and variant
  • SKU and quantity
  • Original price vs. discounted price (with percentage saved)
  • Selling plan details for subscriptions

Expandable Item Details

Click any item to reveal:

  • Variant ID, Product ID, and Item Key
  • Vendor and product type
  • Complete line item properties
  • Discount breakdowns by code
  • Selling plan allocation details

Quick Actions:

  • Copy Variant ID, Product ID, or Item Key to clipboard
  • Duplicate item (preserves all properties)
  • Remove item instantly

Example Use Case

You're debugging why a discount isn't applying correctly. Instead of digging through JSON:

  1. Open Cart Panel
  2. Expand the item in question
  3. See the exact discount allocation and compare with expected values
  4. Notice the discount is applying to line_price but your theme is displaying original_line_price

Time saved: 15+ minutes per debugging session

Feature 2: Cart History & Time Travel

The Problem

You've finally reproduced a cart bug after 10 minutes of adding products. You refresh the page to test your fix—and the cart state is gone or changed.

The Solution

Cart History automatically tracks every cart change with timestamps and visual diffs.

What gets tracked:

  • Items added (green)
  • Items removed (red)
  • Quantity changes (orange with old→new values)
  • Attribute modifications
  • Note changes
  • Discount code applications

One-Click Restoration

See a historical cart state you need? Click Restore and the Cart Panel:

  1. Clears your current cart
  2. Re-adds all items with their exact properties
  3. Restores cart attributes and notes
  4. Maintains selling plan allocations

The entire process takes ~2 seconds.

Example Use Case

You're testing a "free gift at $100" promotion:

  1. Build a cart worth $95
  2. Add a $10 item → gift appears
  3. Test your Liquid display logic
  4. Realize you need to test the $95 state again
  5. Click Restore on the $95 history entry
  6. Continue testing

Time saved: 5-10 minutes per cart rebuild

Feature 3: Cart Scenarios (Saved Cart States)

The Problem

You have 8 different cart configurations you need to test:

  • Empty cart
  • Single item
  • Multiple items
  • Items with properties (personalization)
  • Subscription items
  • Gift-with-purchase items
  • Mixed cart with discounts
  • Maximum quantity cart

Rebuilding these manually for every test cycle is exhausting.

The Solution

Cart Scenarios let you save, name, and instantly load predefined cart states.

Creating a Scenario

  1. Build your desired cart state
  2. Click ScenariosSave Current Cart
  3. Name it (e.g., "GWP Test - $100 threshold")
  4. The scenario saves all items, quantities, properties, attributes, and notes

Loading a Scenario

  1. Click Scenarios
  2. Select your saved scenario
  3. Choose to clear cart first or add to existing
  4. Cart is populated instantly

Scenario Editor

Need to tweak a scenario without rebuilding the cart?

  • Add/remove items by variant ID
  • Modify quantities
  • Add line item properties
  • Set cart attributes
  • Include cart notes

Import/Export

Share scenarios with your team:

// Exported scenario file
{
  "name": "GWP Test Cart",
  "items": [
    { "variant_id": "12345678", "quantity": 2, "properties": { "_is_gwp": "true" } }
  ],
  "attributes": { "gift_message": "Happy Birthday!" },
  "note": "Test order - do not fulfill"
}

Example Use Case

Your QA team needs to test 12 different cart states for a new promotion:

  1. Developer creates all 12 scenarios
  2. Exports as JSON file
  3. QA imports into their devtools
  4. QA can now test all 12 states in under a minute

Time saved: Hours of manual cart building across team members

Feature 4: Automated Cart Tests

The Problem

Cart validation logic is complex. Gift-with-purchase items need specific properties. Quantity limits must be enforced. Bundles require companion products. How do you catch these issues before they reach production?

The Solution

Cart Tests let you define validation rules that run automatically against your cart state.

Four Rule Types

1. Property Dependency Rules

"If item has property X, it must also have properties Y and Z"

IF item has property "_is_gwp" = "true"
THEN item MUST have properties: "_gwp_price", "_gwp_source", "_gwp_campaign"

Use cases:

  • Gift-with-purchase validation
  • Personalization requirements
  • Pre-order expected ship dates
  • Custom product data integrity

2. Field Value Rules

"If item field equals X, then another field must equal Y"

IF item product_type = "Gift Card"
THEN item quantity MUST equal 1

Use cases:

  • Gift card quantity limits
  • Digital product shipping flags
  • SKU requirements
  • Subscription validation

3. Cart Composition Rules

"If cart contains item X, cart must also contain item Y"

IF cart contains item with product_type = "Electronics"
THEN cart MUST contain item with product_type = "Warranty"

Use cases:

  • Required accessories
  • Bundle completeness
  • Warranty requirements
  • Cross-sell validation

4. Quantity Rules

"Item/cart quantities must meet min/max/multiple constraints"

SCOPE: per-item
MAX: 10
(No item can have quantity > 10)
SCOPE: cart-total
FILTER: product_type = "Sample"
MAX: 3
(Maximum 3 sample products in cart)

Use cases:

  • Per-item limits
  • Cart maximums
  • Bulk order minimums (B2B)
  • Sample product limits
  • Pack quantity enforcement (multiples of 6)

Pre-Built Templates

Don't want to configure from scratch? Choose from 13 pre-built templates:

  • [Property] GWP Validation
  • [Property] Personalization Check
  • [Property] Pre-order Validation
  • [Field] Gift Card Qty = 1
  • [Field] Subscription Valid
  • [Field] Digital Products Check
  • [Field] SKU Required
  • [Composition] Warranty Required
  • [Composition] Bundle Check
  • [Qty] Max Per Item (10)
  • [Qty] Cart Max (50 items)
  • [Qty] Pack of 6 Only
  • [Qty] Samples Max 3

Auto-Run Tests

Enable Auto-run and tests execute automatically whenever your cart changes. Failed items are highlighted with a red border directly in the cart display.

Test Results

  • Summary shows pass/fail count
  • Failed tests show detailed error messages
  • Specific items causing failures are identified
  • First 5 failures displayed with "+N more" indicator

Example Use Case

You're implementing a gift-with-purchase promotion:

  1. Create a test: "GWP items must have _gwp_price property"
  2. Enable auto-run
  3. Add a GWP item to cart
  4. Test immediately fails—missing required property
  5. Fix your GWP logic to include the property
  6. Test passes automatically
  7. Ship with confidence

Time saved: Catching bugs before they reach production = priceless

Feature 5: Quick Cart Actions

Add Items Instantly

No need to browse to product pages. Enter a variant ID and quantity, click Add, and the item is in your cart.

Variant ID: 12345678901234
Quantity: 2
[Add]

Apply Discount Codes

Test discount logic directly from the panel without going through checkout:

Discount Code: SAVE20
[Apply]

Cart Permalink

Need to share a specific cart state? Click Link to copy a permalink:

https://yourstore.com/cart/12345678:2,87654321:1

Export Cart JSON

Click Export to download your complete cart state as JSON for documentation or bug reports.

Feature 6: Network Request Tracking

The Problem

Something is modifying your cart unexpectedly. Is it a third-party app? A theme script? A Shopify feature?

The Solution

The Cart Panel intercepts and logs all cart-related AJAX requests:

Tracked endpoints:

  • /cart.js
  • /cart/add.js
  • /cart/update.js
  • /cart/change.js
  • /cart/clear.js

For each request, you see:

  • HTTP method and status
  • Request/response timing
  • Request body and headers
  • Response data
  • Source identification (which script made the request)

Request Blocking

Found a rogue script modifying your cart? Block requests by source to isolate the issue:

  1. Identify the problematic request
  2. Click Block Source
  3. Future requests from that script are prevented
  4. Continue debugging without interference

Best Practices

1. Create Scenario Libraries

Build a comprehensive set of scenarios for your store:

├── Basic States
│   ├── Empty cart
│   ├── Single item
│   └── Multiple items
├── Edge Cases
│   ├── Max quantity (per item)
│   ├── Max items (cart limit)
│   └── Zero-price items
├── Features
│   ├── Gift with purchase
│   ├── Subscription items
│   ├── Personalized items
│   └── Pre-order items
└── Promotions
    ├── Percentage discount
    ├── Fixed amount discount
    ├── Free shipping threshold
    └── BOGO promotion

2. Write Tests for Business Rules

Document your business logic as automated tests:

Business Rule Test Type Configuration
Gift cards qty = 1 Field Value product_type = "Gift Card"quantity = 1
GWP has tracking Property Dependency _is_gwp = true → requires _gwp_source
Electronics need warranty Cart Composition product_type = "Electronics" → requires product_type = "Warranty"
Max 3 samples Quantity cart-total, max: 3, filter: product_type = "Sample"

3. Use History for Regression Testing

  1. Build the cart state for your bug
  2. Fix the bug
  3. Use History to restore the original state
  4. Verify the fix
  5. Save as a scenario for future regression testing

4. Share Scenarios with Your Team

  • Export scenarios as JSON
  • Commit to your repository
  • Import on each developer's machine
  • Everyone can test the same edge cases

5. Enable Auto-Run Tests During Development

Keep tests running automatically while you code. Instant feedback when something breaks.

Comparison: Before vs. After

Task Without Devtools With Cart Panel
Inspect cart state Add Liquid, refresh, copy JSON, format Click Cart tab
Rebuild specific cart 5-10 min manual work 2 seconds (scenario load)
Test 10 cart states 50-100 minutes 5 minutes
Track cart changes Custom logging code Automatic history
Validate GWP logic Manual testing Automated tests
Find rogue cart scripts Console debugging Request tracking
Share cart states Screenshots, instructions JSON export

Common Questions

Does this work on live stores?

No. The devtools only render on unpublished themes for security.

Does it modify my theme code?

It adds a single Liquid snippet that conditionally loads the devtools JavaScript.

Can I use it with any Shopify plan?

Yes. It works with Basic, Shopify, Advanced, and Plus plans.

Is it free?

Yes. Shopify Theme Devtools is open source.

Conclusion

The Cart Panel in Shopify Theme Devtools transforms cart debugging from a tedious, time-consuming task into a streamlined workflow. Whether you're:

  • Debugging a discount issue
  • Testing gift-with-purchase logic
  • Validating subscription cart behavior
  • Building complex promotional carts
  • Catching cart validation bugs

...you'll save hours of development time.

Get started:

npx shopify-theme-devtools init

Resources

Tags: #shopify #shopifythemes #shopifydevelopment #liquid #ecommerce #webdevelopment #javascript #debugging #devtools #tutorial

Inside Git: How It Works and the Role of the .git Folder

2026-01-14 14:09:29

For many developers, Git feels like a magical incantation. We type git add . followed by git commit -m "fixed stuff", push it to a remote server, and hope for the best. When it works, it’s fantastic. When it breaks, it feels like trying to defuse a bomb while blindfolded.

The key to moving from blind memorization to true mastery lies in understanding what happens beneath the surface. Git isn't just a list of commands; it is a beautifully designed system for managing information. By peeling back the layers, we can build a mental model of how Git actually "thinks."

Our journey begins at the hidden heart of your repository: the .git folder.

How Git Works Internally

Before diving into the folder structure, we need to correct a common misconception. Many people believe Git stores data as a diff—a series of changes recording only which lines were added or removed.

Git doesn't do this. Instead, Git thinks in snapshots.

Every time you commit, Git takes a "picture" of what all your files look like at that exact moment and stores a reference to that snapshot. To stay efficient, if a file hasn't changed, Git doesn't store the file again; it simply links back to the previous, identical version it already has.

Understanding the .git Folder

If you open your project folder in a file explorer, you might not see it at first. It’s usually hidden because it is crucial that you do not manually mess with its contents.

The .git Folder is your repository.

Everything outside of this folder is just your "working directory"—the temporary sandbox where you edit your current files. The .git folder is the database where Git stores every version of every file, the entire commit history, and all your branches.

Important Note: If you delete the .git folder, you lose your project's entire history, leaving only the "current" version of the files you see on your screen.

While there are many files inside, these three are the most critical for understanding internals:

  • objects/: The heart of the database. It stores all the content of your files and your history.
  • refs/: This directory stores pointers (references) into the object data, such as branches (heads) and tags.
  • HEAD: A simple text file that tells Git which branch you are currently working on.

The Big Three: Blobs, Trees, and Commits

Git is essentially a key-value data store. You put data in, and Git gives you a unique key to retrieve it later.

The key is a Hash—a 40-character string (SHA-1) generated based on the content. If the content changes even slightly, the hash changes completely. This ensures data integrity: if the hash is the same, you can trust the data is unchanged.

Git stores three main types of objects in the objects/ folder:

1. The Blob (Binary Large Object)

A Blob is the simplest object; it just stores the content of a file. Crucially, a Blob does not know the file's name or where it lives in your project. It only knows the raw data.

Pro-tip: If you have two different files (README.md and intro.txt) that both contain the exact text "Hello World," Git only stores one Blob.

2. The Tree

If Blobs store content, Trees store structure. A Tree object acts like a directory. It contains a list of entries pointing to:

  • Blobs (files) along with their filenames.
  • Other Trees (subdirectories).

3. The Commit

The Commit object is the wrapper that ties everything into a snapshot in time. It contains:

  • A pointer to the top-level Tree (the project root).
  • Metadata: Author, timestamp, and the commit message.
  • A pointer to the Parent Commit (the snapshot that came before it).

How Git Tracks Changes (The 3-Step Flow)

Understanding these objects unlocks the mystery of the "Staging Area." Let’s track what happens when you save a new file to history.

Step 1: The Working Directory

You create style.css. Right now, this file only exists in your working directory. Git’s database doesn't know it exists yet.

Step 2: The Staging Area (git add)

When you run git add style.css, Git:

  1. Compresses the content into a Blob.
  2. Calculates the hash and stores it in .git/objects.
  3. Updates the Index (the staging area), noting that for the next snapshot, style.css should point to that specific Blob hash.

Step 3: The Commit (git commit)

When you run git commit -m "Added Styles", Git freezes the stage:

  1. It creates a Tree object to represent the directory structure.
  2. It creates a Commit object pointing to that Tree and the previous commit.
  3. It moves your current Branch pointer (e.g., main) to this new commit hash.

👉 Follow, Like & Share if this helped you to understand Git internals

Headless vs. Real Browser Testing: The Strategic Guide for Modern QA Teams

2026-01-14 14:08:33

In the fast-paced world of software development, the choice between headless and real browser testing is more than a technical decision - it's a strategic one that impacts your release velocity, product quality, and team efficiency. Each method serves a distinct purpose in the testing lifecycle, and understanding their nuanced strengths and limitations is crucial for any QA professional or development lead. Drawing from years of scaling automated testing frameworks, I've seen teams thrive by strategically blending both approaches, not by dogmatically choosing one over the other.

Understanding the Core Technologies

Before diving into comparisons, it's essential to define what we're discussing. At its heart, this is a choice between a visible interface and raw, automated efficiency.

What is Headless Browser Testing?

Headless browser testing runs automated scripts against a browser engine that operates without a graphical user interface (GUI). Think of it as the browser's brain working in the dark: it loads pages, executes JavaScript, and interacts with the DOM, but it does not paint pixels on a screen.

This approach leverages the same underlying engines (like Chromium or WebKit) as their headed counterparts but skips the computationally expensive step of visual rendering. It's primarily driven via command-line interfaces or automation tools like Puppeteer, Playwright, or Selenium with headless flags. Its primary virtue is speed; by forgoing the GUI, tests can run significantly faster, often 2x to 15x quicker than in a full browser.

What is Real (Headed) Browser Testing?

Real browser testing, sometimes called "headed" testing, is what most users intuitively understand. It involves automating or manually interacting with a full, visible browser instance - the complete application with tabs, address bars, and developer tools.

This method provides the highest fidelity to the actual user experience because it tests the application in the exact same environment a customer uses. Every pixel is rendered, every CSS animation plays, and every GPU-accelerated effect is processed. It's the gold standard for validating visual correctness and complex interactive behavior.

Head-to-Head: A Practical Comparison for Decision-Makers

Choosing the right tool requires a clear view of the trade-offs. The following table summarizes the key differences, which I've validated across countless projects.

Table: Strategic Comparison of Headless vs. Real Browser Testing

Aspect Headless Browser Testing Real Browser Testing
Primary Strength Speed & Resource Efficiency Visual Fidelity & Realism
Test Execution Speed Very Fast (No UI rendering) Slower (Full rendering required)
Resource Consumption Low CPU/Memory High CPU/Memory/GPU
Visual Debugging Limited or none; relies on logs & screenshots Full capability; use of DevTools and live inspection
Real User Simulation Low (Programmatic interaction only) High (Mirrors actual user interaction)
Ideal Use Case Early-stage functional checks, CI/CD pipelines, API/unit testing Visual validation, cross-browser/device QA, final user-acceptance
Debugging Ease Challenging; requires interpreting console output Straightforward; visual context aids immediate diagnosis

When to Embrace Headless Testing: The Need for Speed

Headless testing excels in environments where rapid, repetitive feedback is paramount. Based on my experience, here are its strongest applications:

CI/CD Pipeline Integration: In continuous integration environments, where tests run on every commit, speed is non-negotiable. Headless tests provide fast feedback to developers without bogging down the pipeline.

Large-Scale Regression & Smoke Suites: When you need to verify that core functionalities work after a change, running hundreds of headless tests quickly can provide essential confidence before deeper, slower testing begins.

Unit and Integration Testing of UI Logic: For developers writing unit tests that involve DOM manipulation or JavaScript execution, a headless browser offers a lightweight, realistic environment without the overhead of a full UI.

API and Backend-Focused Validation: If the test's goal is to ensure data flows, form submissions, or network requests work correctly, the visual layer is irrelevant. Headless mode is perfectly suited.

When to Demand Real Browser Testing: The Uncompromising Eye

Despite the allure of speed, some testing imperatives demand the full, visual browser. You cannot compromise here:

Visual and UI Regression Testing: Subtle layout shifts, font rendering issues, z-index problems, and broken animations are almost impossible to catch headlessly. Real browsers are mandatory.

Cross-Browser and Cross-Device Compatibility: A website can pass all headless Chrome tests but fail spectacularly in Safari or Firefox due to rendering engine differences. Only testing on real, headed versions of these browsers reveals these issues.

Complex User Interaction Flows: Testing drag-and-drop, hover states, file uploads, or complex gestures often requires the precise event timing and rendering that only a real browser provides.

Client-Side Performance Profiling: Tools like Chrome DevTools' Performance panel, which are critical for diagnosing runtime jank or slow script execution, require a headed browser.

Final Pre-Release Validation: Before a major launch, the final sanity check must happen in an environment that mirrors the end user's. There is no substitute.

Crafting a Hybrid Testing Strategy: The Expert Blueprint

The most effective teams I've worked with don't choose sides; they build a pyramid of quality that leverages both methods strategically. Here's a practical framework:

1. Foundation: Unit & Headless Integration Tests

Begin with a broad base of fast, headless tests. These should cover all critical user journeys, API endpoints, and business logic. Run this suite with every single build in your CI/CD pipeline. Its goal is to provide developers with instant feedback - typically within minutes.

2. Middle Layer: Focused Real-Browser Regression

Build a more selective suite of tests that run in real browsers. This suite focuses on visually complex components, critical conversion paths (like checkouts), and high-traffic pages. Run this suite nightly or on demand before staging deployments.

3. Apex: Manual & Exploratory Real-Browser Testing

The top of the pyramid is reserved for manual exploratory testing, usability reviews, and final visual acceptance in real browsers across the full matrix of supported devices and browsers. This is where human judgment catches what automation misses.

Managing this hybrid workflow efficiently is key. A unified test management platform like Tuskr can be instrumental here, as it allows teams to organize, schedule, and track results from both manual and automated tests - whether headless or headed - in a single dashboard, providing clear visibility into overall quality.

Key Implementation Considerations and Tools

Modern Tools Bridge the Gap: Frameworks like Playwright and Puppeteer have minimized the differences between headless and headed modes. You can often write a test once and run it in both configurations simply by toggling a launch flag.

Debugging Headless Tests: While challenging, you can mitigate debugging pains. Always configure your headless runs to capture screenshots or videos on failure. Increase logging verbosity and integrate with reporting tools that aggregate logs and assets for analysis.

Infrastructure Matters: Running a large real-browser test grid requires significant resources. Many teams turn to cloud-based platforms (like BrowserStack or Sauce Labs) that provide managed grids of real browsers and devices, eliminating the maintenance burden.

Conclusion: A Balanced Philosophy

The debate between headless and real browser testing is not about finding a winner. It's about applying the right tool for the right job at the right time. Headless testing is your engine for speed and efficiency, enabling agile development practices and rapid iteration. Real browser testing is your guardian of user experience, ensuring that what you ship is not just functional but polished and reliable.

Adopt a hybrid, layered strategy. Let headless tests be your first line of defense, catching functional regressions quickly and cheaply. Reserve the power of real browser testing for validating the visual and interactive integrity that defines quality in the user's eyes. By mastering both, you equip your team to deliver superior software at the pace the market demands.

The iOS Safari Full-Height Video Fix That Actually Works (After 4 Hours of Everything That Doesn't)

2026-01-14 14:05:31

If you've tried to make a full-screen hero video work on iOS Safari, you've probably spent hours reading the same recycled advice that doesn't actually solve the problem. I just burned an afternoon on this, so let me save you the pain.

The problem: You want a background video that fills the entire screen on an iPhone. The bottom keeps getting cut off, or there's a gap, or the content below the fold is hidden behind Safari's toolbar. You Google it. You find 50 articles. None of them work.

What the internet tells you to try:

  • 100vh — Too tall. Safari calculates this based on the viewport with toolbars hidden, not what the user actually sees.
  • 100svh — The "small viewport height" that's supposed to fix this. Doesn't work reliably. Tried it. Multiple times. Different ways.
  • 100dvh — The "dynamic viewport height" that updates as toolbars show and hide. Causes layout jank and still didn't solve our problem.
  • 100lvh — The "large viewport height." Gets closer but still came up short on our iPhone 16 Pro Max.
  • -webkit-fill-available — Only works on WebKit, breaks Chrome, doesn't work when nested, and half the implementations out there are wrong anyway.
  • JavaScript solutions using window.innerHeight — Same problem. innerHeight gives you the current visible height, which is the short one. You're back where you started.
  • env(safe-area-inset-bottom) with viewport-fit=cover — Useful for padding content away from the notch and home bar, but doesn't fix the fundamental height issue.

I tried all of these. I tried combining them. I tried the "triple fallback" approach with CSS custom properties. I probably went through 10-12 iterations over three or four hours. The video kept coming up short on taller phones.

What actually worked:

.hero {
  min-height: calc(100lvh + 60px);
}

That's it. Make it too tall on purpose. Then adjust your content positioning to account for it — we bumped bottom-positioned elements from bottom: 15% to bottom: 25% on mobile so they sit comfortably in the visible area on initial load.

Is this elegant? No. Does it feel like a hack? Absolutely. But here's the thing: users don't see your CSS. They see whether your hero video fills their screen or looks broken. "Too tall" means they scroll past it by a few pixels and never notice. "Too short" means the first thing they see is a janky, cut-off hero that makes your site look amateur.

The web development community keeps chasing spec-compliant solutions that Apple keeps breaking with every iOS release. Meanwhile, the simple answer — just add some extra height and adjust your content — isn't anywhere in the search results because it doesn't feel like a "real" solution. But it ships. It works across devices. And it took 30 seconds to implement after we stopped trying to do it the "right" way.

If you're stuck on this problem, stop fighting Safari's viewport quirks. Make your hero too tall, push your content into the visible area, and move on. You've got better things to build.

I'm not claiming this is the best solution — just the one that actually worked after a frustrating afternoon. If you've found something cleaner that reliably works across iOS devices, drop it in the comments. I'd genuinely love to be proven wrong on this one.

That should do it. Good luck — hopefully it helps some people and maybe someone does have a better answer buried somewhere.

Inside Dark Web Monitoring: How Data Leaks Are Identified Responsibly

2026-01-14 14:02:01

Understanding Dark Web Leak Monitoring (Reality vs Myth)

When people hear “dark web monitoring”, they often assume hacking, buying databases, or digging through stolen data.

In real-world defensive security work, none of that happens.

Practically, dark web monitoring is threat watching and signal analysis.

Security researchers treat the dark web as one more intelligence surface—similar to Twitter, Telegram, GitHub, or paste sites—where threat actors publicly announce what they claim to have.

The job is not to access data, but to evaluate the claim.

Step 1: Monitor for Leak Claims

Researchers passively monitor underground forums, leak boards, and breach channels in read-only mode.

Monitoring is keyword-driven:

  • Brand and company names
  • Domains
  • Industry terms
  • Keywords like database, leak, dump, breach

Goal: Detect claims of leaked data — not verify content.

Step 2: Capture Claim Metadata

When a claim appears, only high-level details are recorded:

  • Target organization or sector
  • Claimed record count
  • Country or region
  • Data type mentioned
  • Claimed file format

No interaction.

No data access.

Step 3: Filter Noise Quickly

Most claims are discarded early due to:

  • Unrealistic record counts
  • Poor industry understanding
  • Reposted or recycled breaches
  • Generic or low-effort descriptions

Only plausible claims move forward.

Step 4: Review Structure (Not Data)

If masked samples are shared, researchers examine:

  • Column names
  • Field relevance to the organization
  • Regional and industry consistency

Focus: Does the schema make sense?

Not: Who the data belongs to.

Step 5: OSINT Cross-Check

Claims are cross-checked using open sources:

  • Previous breach disclosures
  • News and regulatory reports
  • Similar historical incidents

This avoids false alerts and misinformation.

Step 6: Assess Risk Scenarios

Researchers evaluate how the data could be abused:

  • Telecom metadata → SIM swap, OTP interception
  • Email + phone → phishing and smishing
  • Identity fields → impersonation

This drives advisories, not exploitation.

Step 7: Responsible Sharing

Findings are shared as:

  • High-level summaries
  • Awareness posts
  • Security advisories

Raw data is never accessed, downloaded, or published.

Hard Boundaries

Researchers do not:

  • Buy leaked data
  • Download databases
  • Contact sellers
  • Validate real user identities

Summary

Dark web leak monitoring is signal analysis, not data access.

The work focuses on early detection, risk evaluation, and responsible communication—nothing more.