Software Test Automation

AI & LLM Testing, AI-Driven Full Stack Test Automation & Beyond – Engineering Quality at Every Layer

From LLMs to AI Applications, UI to APIs, Databases to Microservices — Empower Your QA Team with Practical Strategies, Code Examples, and Real-World Guidance to Master End-to-End Test Automation.

</> 💡 📊 Mastering Programming & Algorithmic Thinking for SDETs

Algorithmic Thinking for Scalable Test Automation

DSA for Optimizing Test Code

Programming in the World of AI

🖥️ Web UI Automation — From Legacy to Modern Web Apps

Modernizing UI automation for SPAs, micro frontends, and dynamic UIs

🔌 🔧 API & Backend Automation Coverage — Tightly Coupled Legacy APIs to Lightweight, Scalable, Event-Driven Microservices

Testing strategy for layered APIs across SOAP, REST, and event-driven architectures

Automating REST API validations using Java's native HttpClient for custom request/response handling

Testing RESTful services with REST Assured for behavior-driven API automation and schema validation

Validating backend workflows such as SOAP web services, microservices, and batch job triggers

📱🔄 Automating Mobile App Testing — Adapting Test Architecture for Modern Mobile Apps: Native, Hybrid, and Web

Unified test automation for native, hybrid, and responsive web experiences using modern mobile testing tools

📱 Appium for Testing Mobile Web and Native Applications

🗄️⚙️ Database Testing in End-To-End Test Automation — Designing reusable test data layers that work with ORM, JDBC, and NoSQL clients

Adapting test automation for structured, semi-structured, and distributed data systems.

Bridging data validation across transactional SQL, flexible NoSQL, and scalable data lakes.

🗄️ SQL Fundamentals for Test Automation: Oracle, MySQL, PostgreSQL, Microsoft SQL Server

🧾 NoSQL Fundamentals for Test Automation: MongoDB Example

🗄️ Implementing Database Validation Testing in End-To-End Test Automation Framework

🔄⚙️ DEVOPS: CI/CD (Continuous Integration / Continuous Deployment)

— Building an Automation Pipeline That Integrates, Executes, and Delivers Quality at Speed

SVN/ Perforce/ Git/ Bitbucket- Version Control Systems

Maven/Gradle- Build Automation

Jenkins Fundamentals and CI/CD

📈 🧠 SDLC, Agile Testing Methodologies And Test Automation Strategy

Aligning test automation with modern Agile workflows, DevOps, and iterative delivery cycles. Leveraging TDD, BDD, and ATDD in Agile teams to increase test reliability and collaboration

Agile And CI/CD

Developing Test Automation Strategy

Test Automation Standards And Best Practices

Defining consistent automation practices that scale across teams, technologies, and test types. From flaky to flawless: practices that eliminate test debt, false positives, and test maintenance traps

Test Automation Best Practices

Framework- Standards and Guidelines

AI-Driven Test Automation

Smarter, Faster Testing: The Role of AI in Automation

Adopting AI in Test Automation

Testing AI/ML Models for Reliability and Performance

Validating AI Systems for Accuracy, Speed & Stability

Foundations of Model Testing

Types of Testing in AI/ML

Prompt Testing And Evaluation Tools for LLMs

Promptfoo: The Ultimate Guide to Prompt Testing for LLMs

🧬📐 Test Automation Framework Architecture & Evolution

Layered, Pluggable Framework Patterns for Full-Stack QA

Modern automation frameworks are no longer just UI wrappers — they are scalable software systems that must evolve with the product, tech stack, and delivery pipelines. This section explores how SDETs design and adapt frameworks that are:

Modular and reusable across multiple layers (UI, API, DB)
Environment-aware and CI/CD ready
Maintainable over time through abstraction, utility layers, and design patterns
Plug-and-play with tools like Selenium, REST Assured, Playwright, Appium, and more

📌 Learn how real-world teams evolve their test architecture in response to scaling products, shifting tools, and agile demands.

👉 Explore detailed case studies and framework blueprints in the Tech Lab →