Testing Practitioner Handbook Front Cover

Testing Practitioner Handbook

  • Length: 350 pages
  • Edition: 1
  • Publisher:
  • Publication Date: 2017-03-22
  • ISBN-10: B06XSXSLF8
  • Sales Rank: #2795802 (See Top 100 Books)
Description

Gain insights into the latest technology and business trends within testing domains

About This Book

  • This book covers the latest trends that every Testing and QA professional should keep up-to-date with given the advancements in digital technologies.
  • Master cutting-edge testing techniques for emerging areas such as IOT, Machine Learning, Cognitive.
  • Best practices for Testing and Quality Assurance within several industry domains.

Who This Book Is For

This book is targeted at those working in the QA and Testing areas. The book does not cover testing basics, which QA professional are already familiar with—for example, writing a test plan or test case, and so on.

What You Will Learn

  • Understand the TCOE model, managed services, the structure of testing in Agile/DevOps engagements, factory models, and crowdsourcing
  • Implement testing processes, practices, and automation tools in the Agile/DevOps life cycle
  • Adapt to current technologies in social media, mobile, analytics and the Cloud
  • Leverage cognitive intelligence/machine-learning, robotics, and the Internet of Things in testing
  • How key industries/domains (consumer products and retail, energy and utilities, healthcare, telecom, and automotive) adapt to digital transformation
  • Future directions for the QA industry, consulting careers, testing profession, and professionals

In Detail

The book is based on the author`s experience in leading and transforming large test engagements and architecting solutions for customer testing requirements/bids/problem areas. It targets the testing practitioner population and provides them with a single go-to place to find perspectives, practices, trends, tools, and solutions to test applications as they face the evolving digital world.

This book is divided into five parts where each part explores different aspects of testing in the real world. The first module explains the various testing engagement models. You will then learn how to efficiently test code in different life cycles. The book discusses the different aspects of Quality Analysis consideration while testing social media, mobile, analytics, and the Cloud. In the last module, you will learn about futuristic technologies to test software.

By the end of the book, you will understand the latest business and IT trends in digital transformation and learn the best practices to adopt for business assurance.

Style and approach

This book is a compilation of the latest business and IT trends in digital transformation & Tools and Best Practices that QA professionals need to adopt for business assurance.

Table of Contents

Chapter 1. State of Digital Transformation – What Has Changed in the Last Four Years (2013-16)?
Chapter 2. Future of Testing Engagement Models – Are Predictions of Increased QA Spends Justified?
Chapter 3. The Benefits of Replacing Testing Subcontractors with Managed Testing Services
Chapter 4. Digital Quality Assurance in a Factory Model
Chapter 5. Crowdsourcing – Enabling Flexible, On-Demand Testing COEs
Chapter 6. Testing Goes an Extra Mile over Weekends
Chapter 7. Testing in Agile Development and the State of Agile Adoption
Chapter 8. Agile and DevOps Adoption are Gaining Momentum
Chapter 9. Does the Rise of DevOps Undermine Agile?
Chapter 10. Role of Automation in DevOps Life Cycle
Chapter 11. Assessing the State of Your DevOps Adoption with DevOps Benchmarking Approach
Chapter 12. Accelerating DevOps – ChatOps is the New Cool
Chapter 13. Behavior-Driven Development (BDD) Using Gherkin in Agile/DevOps Environment
Chapter 14. Automating Configuration Management for DevOps Test Environments
Chapter 15. Automated Test Data Management in the DevOps Environment
Chapter 16. Testing in DevOps Life Cycle Using Microservices Architecture
Chapter 17. Automated Test Environments for DevOps
Chapter 18. Service Virtualization as an Enabler of DevOps
Chapter 19. Best Practices in Identifying Regression Test Cases
Chapter 20. Accessibility Test Automation in DevOps Environment
Chapter 21. Performance Tuning of Java Applications
Chapter 22. Testing Mobile Applications – Key Challenges and Considerations
Chapter 23. Testing Analytics Applications – What Has Changed in SMAC World
Chapter 24. Migrating Applications to Cloud Environments – Key Testing Considerations
Chapter 25. How Should a Tester Adapt to Cloud – Call for Change of Mindset among Testers
Chapter 26. On-Demand Performance Testing on Self-Service Environments
Chapter 27. Quality Assurance for Digital Marketing Initiatives
Chapter 28. Security Dashboard for the Board
Chapter 29. Applying Robotic Automation to Mobile Applications Testing
Chapter 30. Key Considerations in Testing Internet of Things (IoT) Applications
Chapter 31. Algorithmic Business – In Need of Model-Based Testing
Chapter 32. Making Testing Adaptive, Interactive, Iterative, and Contextual with Cognitive Intelligence
Chapter 33. FinTech – A New Disruptor in Industry and Implications for Testing and QA
Chapter 34. Blockchain Technology – Assuring Secure Business
Chapter 35. Technologies for Digital Supply Chains and QA Considerations
Chapter 36. Potential Innovations in eHealth-Care – Implications for Testing and QA
Chapter 37. Trends in the Global Automotive Sector – Implications for Testing and QA
Chapter 38. Digital Transformation in Consumer Products and Retail Sector – QA Considerations
Chapter 39. Digital Transformation Trends in Energy and Utilities – QA Considerations
Chapter 40. Smart Energy and Smart Grids – in Need of Effective Testing
Chapter 41. Testing Airline Digital Applications – Case for Responsive Design
Chapter 42. Orthogonal Array Testing (OAT) – an Application in Healthcare Industry
Chapter 43. Future of Consulting in the Era of Digital Disruption
Chapter 44. Future of Testing in the Digital World
Chapter 45. Future of Testing – Career Opportunities
Chapter 46. Robotics and Machine Learning Combined with Internet of Things – What Could This Mean for Indian Services Industries

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