How to Set Up Automated Tests for Real-World Scenarios

Creating a Automation Framework for Netflix like application from scratch using PlayWright 1) Smart Architecture -> Fixtures-First Design (to introduce reusability) -> Custom auth fixtures with auto session management -> Browser context fixtures for parallel execution -> Data setup/teardown ensuring clean environments 2) Intelligent Data Strategy -> Static JSON for stable scenarios -> Faker.js for dynamic realistic data -> Live API data creation for fresh test conditions 3) Design Patterns That Work -> Factory Pattern: Dynamic test data creation -> Page Object Model: Encapsulated reusable components -> Strategy Pattern: Cross-browser testing -> Singleton: Optimized configuration management 4) Complete API Coverage -> REST APIs (CRUD, auth), GraphQL (queries, mutations), OAuth/JWT flows, Third-party integrations -> API + UI Combo: Live data creation through APIs feeding directly into UI test scenarios. 5) Advanced UI/UX Automation -> Visual regression testing -> WCAG accessibility validation -> Responsive design testing -> Performance metrics (Core Web Vitals) -> Cross-browser compatibility 6) ReUsability -> Components setup -> Custom assertions -> Config management through tsconfig, playwright.config, .env files -> Page Objects -> Data Factories 7) Testing Capabilities -> Cross-browser Testing: Chrome, Firefox, Safari, Edge support -> Mobile Testing: Device emulation and responsive design validation -> API Testing: REST and GraphQL endpoint validation -> Visual Testing: Screenshot comparison and visual regression -> Performance Testing: Load time and network performance metrics -> Accessibility Testing: WCAG compliance validation -> Tech Stack Playwright + TypeScript + Faker.js + Docker + CI/CD + PlayWright default Reports + Git Actions + APIs 🎪 Key Lessons -> Architecture investment scales exponentially -> OOP principles reduce complexity -> API-first approach ensures comprehensive coverage -> Mixed data strategy creates realistic scenarios -x-x- Learn PlayWright with JavaScript/TypeScript from Scratch with E2E Automation Course: #japneetsachdeva

𝗦𝘁𝗼𝗽 𝘄𝗿𝗶𝘁𝗶𝗻𝗴 𝗯𝗿𝗶𝘁𝘁𝗹𝗲 𝗦𝗲𝗹𝗲𝗻𝗶𝘂𝗺 𝘁𝗲𝘀𝘁𝘀 𝘁𝗵𝗮𝘁 𝗯𝗿𝗲𝗮𝗸 𝘄𝗶𝘁𝗵 𝗲𝘃𝗲𝗿𝘆 𝗨𝗜 𝗰𝗵𝗮𝗻𝗴𝗲. It's time to build a test automation framework that lasts. 🚀 I'm excited to share my video tutorial on Selenium with Java using the Page Object Model! This deep-dive course is designed for beginners and progresses to advanced topics, giving you a robust foundation for building maintainable and efficient automated web tests. I've also 𝗮𝘁𝘁𝗮𝗰𝗵𝗲𝗱 𝘁𝗵𝗲 𝗣𝗼𝘄𝗲𝗿𝗣𝗼𝗶𝗻𝘁 𝗽𝗿𝗲𝘀𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 from the video to help you follow along. A core concept we cover is the Page Object Model (POM). This is a powerful design pattern that makes your test automation code cleaner, more reusable, and far easier to maintain. Instead of writing brittle test scripts, you create a class for each page of your application, storing all its elements and interaction methods in one place. The tutorial is broken down into four key parts: 📜 Part 1: Project Setup & Your First Test We start from scratch. I'll guide you through setting up your entire environment: ✅ Installing Java (JDK) and IntelliJ ✅ Configuring a Maven project ✅ Adding Selenium and TestNG dependencies ✅ Writing and running your very first Selenium test script with assertions. 🏛️ Part 2: Building the Page Object Model (POM) This is where we implement the POM. You'll learn: 👉 The theory, structure, and benefits (Reusability, Readability, Maintainability) of POM. 👉 How to create a BasePage and BaseTest to handle common setup and teardown. 👉 Building specific Page Object classes (like LoginPage) to separate your test logic from your page interactions. 🧩 Part 3: Working with All Kinds of Web Elements Once our framework is built, we dive deep into interacting with every web element you'll encounter: 🛠️ Using JavaScriptExecutor to scroll 🛠️ Handling radio buttons and checkboxes (including conditional clicks) 🛠️ Navigating complex web tables to edit and verify data 🛠️ Interacting with links, dropdowns (standard and multi-select), and date pickers. 🔀 Part 4: Advanced Interfaces & Unique Situations The final part covers advanced scenarios and powerful Selenium features: 🔎 Taking screenshots automatically on test failure 🔎 Handling Modals, JavaScript Alerts (confirmation, prompt), and iframes 🔎 Switching between multiple browser windows and tabs 🔎 Mastering Dynamic Waits (Explicit and Fluent) to handle asynchronous operations 🔎 Using the Actions class to simulate complex user actions like drag-and-drop (for sliders) and keyboard events (like pressing Tab or Enter). I've dropped the link to the full course in the first comment below! 👇 𝗣𝗦: 𝗕𝗲 𝘀𝘂𝗿𝗲 𝘁𝗼 𝘀𝗮𝘃𝗲 𝘁𝗵𝗶𝘀 𝗽𝗼𝘀𝘁 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗮𝘁𝘁𝗮𝗰𝗵𝗲𝗱 𝗽𝗿𝗲𝘀𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝗳𝗼𝗿 𝗳𝘂𝘁𝘂𝗿𝗲 𝗿𝗲𝗳𝗲𝗿𝗲𝗻𝗰𝗲! I hope this helps you with Selenium. Let me know what you think! 🤝 Rex Jones II #Selenium #Java #TestAutomation #PageObjectModel #RexJonesII

🚀 EPISODE 6 — Applitools for AI-Powered Visual Testing (AI for QA Engineers) 👀🤖 Welcome to Episode 6 of my series: #TestingSmarterWithAI 🚀 In the previous episodes, we explored tools like ChatGPT, GitHub Copilot, Claude AI, Cursor AI, and Testim. Today’s tool is one of the most powerful solutions for UI validation: 🔥 Applitools (AI Visual Testing) Applitools helps testers validate UI changes intelligently using AI, which makes visual regression testing more reliable and scalable. 🧠 Why Applitools is Useful for QA / Automation Engineers In real-world automation, functional scripts may pass, but UI issues can still occur, such as: 📌 alignment issues 📌 missing buttons or labels 📌 incorrect fonts/colors 📌 broken UI after deployment 📌 responsive layout failures 📌 cross-browser UI differences These issues are hard to catch using normal Selenium assertions. That’s where Applitools becomes extremely useful. ✅ How I Use Applitools Step-by-Step in Real Testing Workflow 🔹 Step 1: Integrate Applitools into Automation Framework Applitools can be integrated with: ✔️ Selenium ✔️ Cypress ✔️ Playwright ✔️ Appium Once integrated, we can add visual checkpoints inside our automation scripts. 🔹 Step 2: Capture Baseline Screens During the first execution, Applitools creates a baseline UI snapshot of the application screen. This becomes the reference for future test runs. 🔹 Step 3: Run Regression & Compare Screens Automatically During regression execution, Applitools compares the current UI with baseline and detects changes like: ✅ missing elements ✅ UI shift/alignment changes ✅ color/font differences ✅ responsive UI breaks ✅ layout changes in different browsers 🔹 Step 4: Review Results in Dashboard Applitools provides a clean dashboard where we can: 📌 approve expected UI changes 📌 reject unexpected UI defects 📌 track UI issues across builds This makes UI validation very efficient. 🔹 Step 5: Cross-Browser Visual Validation Instead of manually validating UI across multiple browsers/devices, Applitools helps verify UI consistency across: 🌍 Chrome / Firefox / Edge 📱 Mobile browsers 🖥️ Different resolutions This is a huge advantage for enterprise applications. 🧪 Realistic Example 📌 Scenario: “Validate Checkout page UI after new release.” Functional automation may pass because the button exists. But visually the button could be: ⚠️ overlapped ⚠️ shifted outside screen ⚠️ hidden behind another component Applitools detects such issues instantly. 🎯 Key Takeaway Applitools is a great AI testing tool for teams who want: 👀 reliable visual validation 🚀 faster UI regression testing 📌 reduced manual UI checks ⚡ cross-browser UI confidence 💬 Question for the community: Do you currently perform visual regression testing in your project? If yes, which tool are you using? #SoftwareTesting #AutomationTesting #Applitools #VisualTesting #AIinTesting #QA #SDET #RegressionTesting #UITesting #TestingSmarterWithAI #TechCommunity

Robot + Test Automation Tool + Microcontroller = Relief Hardware automation testing challenges had me in a chokehold for years. Until I discovered this approach: The problem: Manual hardware testing controlled my workflow. Cost me: Time, accuracy, and scalability Affected: Product development cycles and quality assurance Tried everything: Manual checks, partial automation, inconsistent results The breakthrough process: 1. Integrated microcontroller-based automated testing systems Immediate relief: Consistent and rapid evaluations with reduced human error. 2. Leveraged robotic automation for physical device testing Momentum built: Enhanced device verification through simulation of real-world conditions. 3. Combined software and hardware testing automation frameworks Freedom achieved: Streamlined processes with scalable, repeatable testing protocols. Result after implementation: → Improved accuracy and reliability in hardware validation → Reduced testing time and operational costs → Accelerated product development and higher quality standards The secret? Harnessing the synergy of microcontrollers and robotics to automate complex hardware testing tasks, enabling precise, efficient, and scalable verification. Your testing challenges have a solution. You just haven't implemented it yet. What hardware-related challenges does your automation testing process face? #TestAutomation #SoftwareTesting #QualityAssurance #TestMetry

🚀 Selenium Automation Project – Real-Time Use Cases Covered 🔍💻 I recently built a comprehensive Selenium Automation Framework to cover various real-world test scenarios. This project demonstrates key UI automation strategies and techniques required for web-based testing. 🧪 Use Cases Covered: ✅ Alerts ✅ Window and Tab Handling ✅ Broken Links Validation ✅ CSS Selectors & XPath Locators ✅ Checkboxes, Radio Buttons, and Drop-downs ✅ Date Picker Automation ✅ File Upload ✅ Frames & iFrames ✅ Conditional and Wait Methods (Explicit, Implicit, Fluent) ✅ JavaScript Executor ✅ Keyboard Actions & Mouse Hover ✅ Navigation Commands ✅ Headless Browser Testing ✅ Screenshot Capture ✅ Web Tables – Data Extraction & Validation ✅ Handling Browser Popups ✅ Utility Methods and Modular Structure ✅ First Test Setup (with JUnit/TestNG) 🔧 Framework Stack: Selenium WebDriver Java TestNG Maven Page Object Model (POM) JUnit GitHub for Version Control 📂 GitHub Repo: Explore the full project here 👉 https://lnkd.in/gA2stnEf #Selenium #AutomationTesting #Java #TestNG #SDET #QAEngineer #GitHub #UITesting #PageObjectModel #LinkedInLearning #CareerGrowth #TestAutomation

Anyone can build an Agent today. But only few can do this: Traditional testing relies on fixed inputs and exact outputs. But agents speak in language, and there’s no single “correct” response. That’s why we test Agents using other Agents by simulating Users and Judges. I built such a pipeline to test Agents with the help of other Agents by using Scenario. Here's my 100% open-source tech stack: - CrewAI for Agent orchestration. - LangWatch Scenario to build the eval pipeline. - PyTest as the test runner. The underlying process is explained in the animation of the video below: Step 1) Define three Agents: - The Agent you want to test. - A User Simulator Agent to act like a real user. - A Judge Agent for evaluation. Step 2) Let your Agent and User Simulator Agent interact with each other. Step 3) Evaluate the exchange using the Judge Agent based on the specified criteria. The LangWatch Scenario framework orchestrates this process. It is a library-agnostic Agent testing framework based on simulations. Key features: - Test Agent behavior by simulating users in different scenarios and edge cases. - Evaluate at any point of the conversation using powerful multi-turn control. - Integrate any Agent by implementing just one call() method. - Combine with any LLM eval framework or custom evals. Find a link to the GitHub repo in the comments! ____ Find me → Avi Chawla Every day, I share tutorials and insights on DS, ML, LLMs, and RAGs.

Last week, one Automation Testing learner messaged me after an interview. He said: “Swaroop, they barely asked direct Selenium questions.” He had prepared: XPath Waits TestNG Java programs But the interviewer kept asking real-time scenarios. Questions like: “What if your test works locally but fails in Jenkins?” “How will you handle flaky tests?” “What if elements load differently every time?” “How will your framework support parallel execution?” After the interview, I told him one thing: While practicing automation, don’t just write scripts. Train yourself to think like this: “Think about why the test can fail.” Examples: 1) Dynamic loader issue → Add proper synchronization instead of Thread.sleep() 2) Flaky failures in execution → Improve waits and use stable locators 3) Tests failing in parallel runs → Use ThreadLocal and avoid shared objects 4) Jenkins execution failures → Verify browser versions, drivers, URLs, test data, and environment configs used in Jenkins 5) Changing web elements → Use reliable locators and centralize them using Page Object Model for easier maintenance 6) Long execution time → Run tests in parallel and avoid unnecessary steps This is the shift happening in Automation Testing interviews now. Less focus on: “What is the syntax?” More focus on: “How do you solve problems in real projects?” Because in real projects, companies value troubleshooting mindset more than memorized definitions. #swaroopnadella #automationtesting

How do you ensure reliability when your app consists of hundreds of moving parts, each one a potential point of failure? This is the reality of microservices architecture, and it's pushing traditional testing methods to their breaking point. The rise of cloud-native apps has led to a massive increase in the use of microservices. In fact, IMARC reports the global microservices architecture market hit US$ 3.7B in 2023. All thanks to its unmatched scalability, flexibility, and ability for fast deployment. But this also introduces a level of complexity that many testing strategies simply weren't designed to handle. The interconnected nature of microservices means that one small issue can cascade, potentially breaking the entire system. To complicate things further, these services are often built using different tech stacks and data stores, making it even harder to find the root cause of the problem. That is why we need to move beyond testing individual components and start validating the entire ecosystem. This means simulating real-world scenarios that span multiple services, testing for resilience during partial system failures and ensuring data is consistent across distributed transactions. This is where AI-driven testing tools come in. Platforms like testRigor can: - Create end-to-end tests that mirror real-world usage. - Automatically adapt to changes in service APIs. - Simulate inter-service communication patterns - Test for latency issues - Model failure scenarios to ensure system resilience. When integrated with CI/CD pipelines, testRigor can ensure consistent testing across all environments, catch issues early, speed up dev cycles, and potentially save millions in downtime and lost revenue. On top of that, it's user-friendly. tesRigor allows tests to be written in plain English, democratizing testing by allowing team members across your org to contribute to QA. But tech alone isn't the answer.  We also need to change our approach to QA. We need to build confidence in our system’s ability to handle the unpredictability of distributed computing. This means incorporating performance testing, chaos engineering, and continuous validation into our development processes. As microservices continue to dominate modern app architecture, comprehensive testing isn’t just best practice — it's essential to maintain system integrity and reliability at scale. Ready to revolutionize your microservices testing? Discover how testRigor can transform your QA process >> https://lnkd.in/eijgpWTj #Tech #Microservices #Cloud #SoftwareEngineering