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Testing Practitioner Handbook

Testing Practitioner Handbook

By : Renu Rajani
4.5 (19)
Buy this Book
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Testing Practitioner Handbook

Testing Practitioner Handbook

4.5 (19)
By: Renu Rajani
Buy this Book

Overview of this book

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.
Table of Contents (49 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
Lock Free Chapter
1
1. State of Digital Transformation – What Has Changed in the Last Four Years (2013-16)?
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1. State of Digital Transformation – What Has Changed in the Last Four Years (2013-16)?
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Renewed focus on efficiency and effectiveness
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QA and testing transformation focus
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QA and testing transformation drivers
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State of digital maturity
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Spends for digital QA
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Predictions on the level of cloud-based applications
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Increased challenges in mobile and IoT multichannel testing
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Reduction in customer experience testing challenges
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Conclusion
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2. Future of Testing Engagement Models – Are Predictions of Increased QA Spends Justified?
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2. Future of Testing Engagement Models – Are Predictions of Increased QA Spends Justified?
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How is QA effort spread
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QA organizations would follow hybrid QA teams (centralized and decentralized)
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What will be the future of testing engagement models?
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Conclusion
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References
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3. The Benefits of Replacing Testing Subcontractors with Managed Testing Services
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3. The Benefits of Replacing Testing Subcontractors with Managed Testing Services
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Findings from the World Quality Report 2016 on industrialization and testing centers of excellence
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Use of direct subcontractors remains prevalent
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Key challenges associated while working with subcontractors
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How replacing testing subcontractors with managed testing services helps
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Conclusion
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4. Digital Quality Assurance in a Factory Model
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4. Digital Quality Assurance in a Factory Model
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Services factories
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A digital factory model for industrializing digital QA delivery
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Key Elements for Onboarding in DQAF
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Benefits delivered through DQAF model
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Conclusion
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5. Crowdsourcing – Enabling Flexible, On-Demand Testing COEs
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5. Crowdsourcing – Enabling Flexible, On-Demand Testing COEs
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Trends - crowdsourced testing
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What is crowdtesting and how does it work?
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Crowdtesting operating models
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Crowdtesting as part of Testing Center of Excellence (TCOE)
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The benefits of crowdtesting
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Conclusion
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References
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6. Testing Goes an Extra Mile over Weekends
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6. Testing Goes an Extra Mile over Weekends
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Weekend testing – modus operandi
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Advantages
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Disadvantages
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Trends in the use of crowdsourced testing
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How can large IT organizations ride the weekend testing bandwagon?
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Conclusion
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References
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7. Testing in Agile Development and the State of Agile Adoption
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7. Testing in Agile Development and the State of Agile Adoption
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What do agile projects promise compared to traditional waterfall?
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Flavors of agile
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How is testing done in agile sprints?
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Agile in distributed environments
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State of agile adoption – findings from the World Quality Report 2016-2017
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Conclusion
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8. Agile and DevOps Adoption are Gaining Momentum
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8. Agile and DevOps Adoption are Gaining Momentum
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Increased use of agile/DevOps principles
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Increased complexity of testing in the agile landscape
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Challenges cited in setting up agile test COEs
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How is QA transforming to meet the demands of agile/DevOps life cycles
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What is the difference between testing in DevOps and traditional life cycle?
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Conclusion
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9. Does the Rise of DevOps Undermine Agile?
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9. Does the Rise of DevOps Undermine Agile?
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Agile is about speed
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DevOps removes the boundaries between dev, QA, and operations
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Agile versus DevOps
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Conclusion
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10. Role of Automation in DevOps Life Cycle
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10. Role of Automation in DevOps Life Cycle
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The importance of automation in DevOps
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Early integration automation
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Automation – the default practice
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Deployment automation
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Automation – metrics and measurements
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Best practices to adopt early and continuously automate
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Conclusion
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11. Assessing the State of Your DevOps Adoption with DevOps Benchmarking Approach
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11. Assessing the State of Your DevOps Adoption with DevOps Benchmarking Approach
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Why DevOps – the drivers
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Challenges organizations face in implementing DevOps
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DevOps QA benchmarking — why and what?
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DevOps QA benchmarking assessment areas
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Conclusion
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12. Accelerating DevOps – ChatOps is the New Cool
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12. Accelerating DevOps – ChatOps is the New Cool
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DevOps trends from World Quality Report
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ChatOps – How does it work?
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Application of ChatOps as a collaboration platform
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Benefits of ChatOps
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Conclusion
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13. Behavior-Driven Development (BDD) Using Gherkin in Agile/DevOps Environment
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13. Behavior-Driven Development (BDD) Using Gherkin in Agile/DevOps Environment
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Background – Behavior-Driven Development (BDD)
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Gherkin – basic syntax and illustration
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Roles of members involved
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Benefits of using Gherkin
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Conclusion
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14. Automating Configuration Management for DevOps Test Environments
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14. Automating Configuration Management for DevOps Test Environments
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Background
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Types of test environments
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Potential solutions for automated configuration management
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The benefits of automating configuration management
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Conclusion
15
15. Automated Test Data Management in the DevOps Environment
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15. Automated Test Data Management in the DevOps Environment
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Background
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TDM in DevOps environment – key challenges
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Automated TDM solution for DevOps environment
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Typical TDM services and TDM architecture
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Benefits of automated TDM
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Best practices in TDM
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Conclusion
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16. Testing in DevOps Life Cycle Using Microservices Architecture
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16. Testing in DevOps Life Cycle Using Microservices Architecture
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What is microservices architecture?
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Testing in agile/DevOps life cycle using Microservices Architecture
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Performance testing of Microservices
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Monitoring Microservices
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Conclusion
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17. Automated Test Environments for DevOps
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17. Automated Test Environments for DevOps
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Test Environment Management – key challenges
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Test environment automation approach for DevOps
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Benefits of test environment automation
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Test environment metrics to consider in release management
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Test environment automation tools
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Conclusion
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18. Service Virtualization as an Enabler of DevOps
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18. Service Virtualization as an Enabler of DevOps
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Service virtualization and DevOps
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Role of service virtualization in DevOps
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Service virtualization – research input
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Service virtualization automation tools used in DevOps
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Conclusion
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19. Best Practices in Identifying Regression Test Cases
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19. Best Practices in Identifying Regression Test Cases
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Background – software regression testing
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Software regression process
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How should one choose test cases for regression?
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Conclusion
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20. Accessibility Test Automation in DevOps Environment
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20. Accessibility Test Automation in DevOps Environment
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Background – Accessibility (AX)
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AX and DevOps
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AX test automation in DevOps
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Standard AX tools
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Conclusion
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21. Performance Tuning of Java Applications
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21. Performance Tuning of Java Applications
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Performance bottlenecks – key challenges and solutions
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Java performance tuning tools
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Conclusion
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22. Testing Mobile Applications – Key Challenges and Considerations
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22. Testing Mobile Applications – Key Challenges and Considerations
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User expectations
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Key challenges encountered in testing mobile applications
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Recommendations to enhance mobile applications usability
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Conclusion
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23. Testing Analytics Applications – What Has Changed in SMAC World
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23. Testing Analytics Applications – What Has Changed in SMAC World
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Understanding your customers, gathering data and analyzing it
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Testing the data
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Testing the BI/BA applications
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How is testing done differently for big data/Hadoop applications?
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Conclusion
24
24. Migrating Applications to Cloud Environments – Key Testing Considerations
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24. Migrating Applications to Cloud Environments – Key Testing Considerations
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Need for validating applications for cloud migration
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Key testing focus areas in cloud migration of applications
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Key challenges in validation during cloud migration of applications
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Application migration validation – a holistic approach
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Conclusion
25
25. How Should a Tester Adapt to Cloud – Call for Change of Mindset among Testers
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25. How Should a Tester Adapt to Cloud – Call for Change of Mindset among Testers
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What must testers prepare for when testing applications on cloud
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Conclusion
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26. On-Demand Performance Testing on Self-Service Environments
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26. On-Demand Performance Testing on Self-Service Environments
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On-demand performance testing environments — key challenges and solutions
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Need for a cloud platform to build end-to-end performance testing
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On-demand self-service environments for carrying out performance testing
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Key scenarios for on-demand performance testing – proposed architecture
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Conclusion
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27. Quality Assurance for Digital Marketing Initiatives
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27. Quality Assurance for Digital Marketing Initiatives
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Evolution of digital marketing
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Challenges of implementing digital marketing
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Need for quality focus in digital marketing initiatives
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QA of digital marketing applications – key validations
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Conclusion
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28. Security Dashboard for the Board
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28. Security Dashboard for the Board
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Why security threats need to be monitored and reported?
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What should be monitored and reported?
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Specific metrics to be reported in dashboard
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Consequences of security lapses
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Key challenges in implementing a dashboard
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Conclusion
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29. Applying Robotic Automation to Mobile Applications Testing
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29. Applying Robotic Automation to Mobile Applications Testing
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Software robot and their applicability
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The benefits of Robotic Process Automation (RPA)
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Implementing RPA for mobile testing
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Conclusion
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References
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30. Key Considerations in Testing Internet of Things (IoT) Applications
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30. Key Considerations in Testing Internet of Things (IoT) Applications
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Need for a robust IoT test strategy
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IoT Revolution – key findings from the World Quality Report 2016
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IoT Testing Considerations
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IoT testing types
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Conclusion
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References
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31. Algorithmic Business – In Need of Model-Based Testing
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31. Algorithmic Business – In Need of Model-Based Testing
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Introduction and journey of analytics
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Algorithmic business – an illustration
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Implications of testing – the need for model-based testing
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Conclusion
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32. Making Testing Adaptive, Interactive, Iterative, and Contextual with Cognitive Intelligence
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32. Making Testing Adaptive, Interactive, Iterative, and Contextual with Cognitive Intelligence
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Background – cognitive intelligence
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What is cognitive testing all about?
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Evolution of cognitive technology and available platforms
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Methodologies involved in cognitive testing
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Advantages of cognitive testing compared to the current methods
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Sector specific use cases
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Technologies supported
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Costs involved
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Challenges associated in implementing cognitive technologies
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Conclusion
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33. FinTech – A New Disruptor in Industry and Implications for Testing and QA
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33. FinTech – A New Disruptor in Industry and Implications for Testing and QA
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FinTech ecosystem
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FinTech services and their impact on various sectors
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Testing for FinTech applications or solutions
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Conclusion
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34. Blockchain Technology – Assuring Secure Business
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34. Blockchain Technology – Assuring Secure Business
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Introduction to blockchain
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The blockchain process
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Popular blockchains
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Implication for testing
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Conclusion
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35. Technologies for Digital Supply Chains and QA Considerations
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35. Technologies for Digital Supply Chains and QA Considerations
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Understanding the customer buying process
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Industry trends in supply chain management
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New technologies in supply chain management
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An illustration – new technologies in retail
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Focus of QA in supply chain
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Conclusion
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36. Potential Innovations in eHealth-Care – Implications for Testing and QA
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36. Potential Innovations in eHealth-Care – Implications for Testing and QA
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Digital transformation trends in the healthcare sector
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Applications of digital eHealth-Care care
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Digital eHealth-Care care ecosystem
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Typical challenges in digital eHealth-Care care
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Need for robust digital QA
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An illustrative customer journey validation of patient using wearables
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Conclusion
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37. Trends in the Global Automotive Sector – Implications for Testing and QA
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37. Trends in the Global Automotive Sector – Implications for Testing and QA
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Business drivers for global automotive evolution
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Key highlights from the growing Chinese automotive market
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Influence of global automotive trends on the Chinese market
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How are trends in automotive segments shaping software testing?
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Conclusion
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38. Digital Transformation in Consumer Products and Retail Sector – QA Considerations
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38. Digital Transformation in Consumer Products and Retail Sector – QA Considerations
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Current challenges in the consumer products and retail sector
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Physical versus online stores – key trends
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Digital transformation in CPR industry
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Customer journey of a digital shopper in an omni-channel environment – an illustration
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Being digital – what value levers can it offer to CPR industry
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Factors considered by digital shoppers
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Multi/omni-channel CPR – quality considerations
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Digital transformation in CPR - tests required
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Conclusion
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39. Digital Transformation Trends in Energy and Utilities – QA Considerations
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39. Digital Transformation Trends in Energy and Utilities – QA Considerations
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Technology trends in utilities industry
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Key technology blocks of digital transformation in the EUC sector
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Challenge of multichannel and the need for a unified customer journey
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Testing considerations in an EUC customer journey – an illustration
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Testing considerations in smart metering infrastructure – an illustration
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Digital transformation QA trends in EUC
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Conclusion
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References
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40. Smart Energy and Smart Grids – in Need of Effective Testing
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40. Smart Energy and Smart Grids – in Need of Effective Testing
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Background
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Trends in Energy and Utilities (E&U)
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Typical challenges in the E&U segment
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Smart Meters and Smart Grids
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Testing process for Smart Metering Infrastructure (SMI)
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Conclusion
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41. Testing Airline Digital Applications – Case for Responsive Design
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41. Testing Airline Digital Applications – Case for Responsive Design
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Background – the state of the airline business
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Role of digitization
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QA and testing in the airline industry
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Testing responsive web designs
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Conclusion
42
42. Orthogonal Array Testing (OAT) – an Application in Healthcare Industry
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42. Orthogonal Array Testing (OAT) – an Application in Healthcare Industry
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Background
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Challenges in H&LS applications testing
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How can Orthogonal Array Testing Strategy (OATS) help?
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Conclusion
43
43. Future of Consulting in the Era of Digital Disruption
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43. Future of Consulting in the Era of Digital Disruption
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Digital driving a shift in the way consulting worked
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The digital age consultant
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Future of consulting
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What would I do differently as a consultant now?
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Conclusion
44
44. Future of Testing in the Digital World
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44. Future of Testing in the Digital World
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Key technology trends that would shape the future of Information Technology
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Testing considerations for new technologies
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Conclusion
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45. Future of Testing – Career Opportunities
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45. Future of Testing – Career Opportunities
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Career options in testing services
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Typical roles in testing services
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The importance of industry and domain, technology and tools, and process skills in testing careers
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Required skills for agile and DevOps testing
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New breed of testers in DevOps
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Conclusion
46
46. Robotics and Machine Learning Combined with Internet of Things – What Could This Mean for Indian Services Industries
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46. Robotics and Machine Learning Combined with Internet of Things – What Could This Mean for Indian Services Industries
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Understanding the context – robotics, machine learning, and IoT
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What does advancement of technology mean for the Indian economy?
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Outlook for the the services sector in India – a point of view
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Conclusion
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A. References
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Across Chapters – World Quality Report 2016 (Capgemini, Sogeti, HPE):
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Chapter 2 – Future of Testing Engagement Models – Are Predictions of increased QA Spends Justified?
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Chapter 3 – The Benefits of Replacing Testing Subcontractors with Managed Testing Services
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Chapter 18 – Service Virtualization as an Enabler of DevOps
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Chapter 30 – Key Considerations in Testing Internet of Things (IOT) Applications
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Chapter 31 – Algorithmic Business – In Need of Model-Based Testing
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Chapter 46 – Robotics and Machine Learning Combined with Internet of Things – What could this mean for Indian Services Industries
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Index
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Index

Chapter 19. Best Practices in Identifying Regression Test Cases

Regression testing is carried out to ensure that changes carried out in an application do not impact the working of the earlier working parts of the application. As the software ages, the size of the test suite keeps increasing.

Regression testing needs to be carried out as many times as a new build is released, even if the changes made are small. In DevOps engagements, where continuous integration is carried out, carrying out manual regression will be time consuming as well as expensive; hence, regression tests are often automated.

It is important to carefully choose test cases that need to be used for regression tests to ensure that a test suite is optimal.

In this chapter, we will discuss the given topics:

  • Need for regression testing
  • Software regression process
  • Process for choosing test cases to be included for regression
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