Masterclass Software Quality Engineering | AI Testing

Install Apache Maven by downloading 3.9.6 zip archive, unzip it, and place the bin in a folder. Set Maven home variable, add it to PATH, and verify with mvn -v.

Install Visual Studio Code on Windows 11, configure projects, and install Java-related extensions like Maven, debugger, and GitHub actions, enabling continuous testing and integration for Java-based test automation.

Explore ai agents as orchestrators that coordinate large language models, prompts, and tools to automate tasks, route workflows, and deliver integrated frontend and database interactions.

Use ai agents to generate and critique a bank cash-withdrawal user story, verify it against the definition of ready, ensure quality criteria, and publish to Jira.

Demonstrates generating an automated test with copilot and playwright in agent mode, using the page object model to navigate, select departures, find flights, and pick the cheapest option.

Explore modern branching strategies by embracing trunk-based development or GitHub flow, and avoid the mess of master with release and developer branches.

Reveal the silo paradox in agile teams, where the three amigos—developers, quality engineers, and ops—outside the core team slow information flow and decision making, despite rapid delivery cadence.

Reframe environments away from isolated handoffs between development, integration, and production; emphasize collaboration and fast feedback to support continuous testing from development to production while reducing long-lived environments and costs.

Establish end-to-end traceability from requirements to production by linking user stories, tests, commits, deployments, feature flag activations, and defects with automated reports and CI/CD checks.

Keep environments lean to balance cost and speed, using validation testing and automated quality policies, and follow a simple git flow with main line, features, and PRs to production.

Balance feature-by-feature deployment with direct production pushes to reduce wait times and risk. Implement feature flags, dark launches, and automated quality gates to deliver value safely.

Explore shift left testing with test driven development, validating code locally, deploying to Azure feature environments, and running automated Postman, unit, Lighthouse, and JMeter tests.

Shift left concepts extend beyond testing to all agile life-cycle phases, using user insights, operation feedback, and preventive automation, including test driven development, linters, the test pyramid, and chaos engineering.

Shift left improves team morale and quality via early defect detection and automation, reduces burnout, and keeps a full regression running, boosting time to market, integrity, and organizational competitive advantage.

Discover how the bottom-up testing approach validates every layer from unit tests to UI and performance tests, using rest assured tests, Postman, k six tests, JMeter, and CI/CD pipelines.

Integrate quality policies across the CI/CD pipeline to ensure code, builds, and deployments meet checks at every intermediate step, enabling shift left in continuous delivery.

Demonstrates how quality policies enable reliable builds, code and test quality, ci/cd verifications, deployment checks, and infrastructure tests, including pom.xml validations and postman and chef tests.

Automate a UI test scenario once and run it across Chrome, Firefox, Opera, Safari, Edge, and iOS, Android, and Windows devices, enabling shift left and continuous delivery.

Reuse everything as code to streamline GitHub Actions workflows, duplicating yaml jobs like lighthouse checks to score 90, and reuse requires and dependencies for faster testing and deployment.

Foster a built in quality mindset to enable shift left through ready and done definitions, discovery and design sprints, automated deployment, monitoring, and 100% unit test coverage.

Explore shift-left practices that prevent defects by integrating testing and quality engineering into devops pipeline. Follow pre-integration through monitoring, including unit tests, linting, static analysis, security checks, and performance validation.

Demonstrates an AI agent that automatically creates tests from a story, using Flow Wise to generate acceptance tests, BDD scenarios, and Selenium test code.

Explore flow wise ai, a drag-and-drop orchestration tool to build agents and applications with prompts, llm chains, and customer support workflows.

Install flowwise locally by following the official docs, install Node.js and npm, run mpx flow will start, then open localhost:3000 to access flowwise and the agent marketplace with premade agents.

Build and orchestrate an AI agent with prompt chaining, using a supervisor and worker nodes, a ChatGPT wrapper, and OpenAI API keys, run locally on localhost port 3000.

Leverage fire crawl to transform a website into memory via vector embeddings and a vector store, enabling retrieval augmented generation to generate automated Playwright tests from Blaze Demo.

Validate the playwright MCP server install within Visual Studio Code and explore its toolbox. Create end-to-end tests, including selecting the cheapest flight, using copilot and the page object model.

Avoid the ice cream cone antipattern that overvalues UI tests and slows feedback. Prioritize fast, local unit tests to reduce cost and flakiness, avoiding browser-based automation.

Unit tests are the foundation of quality and fast delivery; they test small, isolated methods with self-checking assertions, aiming for high coverage and reserving complex interactions for integration tests.

Explore how unit tests provide fast, affordable validations inside an application, demonstrated with a basic calculator in Java, using maven test for pre-build validation in VS Code.

After unit testing, create integration tests to verify connectivity to RESTful APIs, databases, queues, and file systems, without validating business logic, using mocks or services marked by the owning team.

Design decoupled automated testing with versioned scripts, data, and configurations managed as code, using page object models, modular methods, and tags for mobile and CI/CD ready suites, infrastructure as code.