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Testing Practitioner Handbook

By : Renu Rajani

4.5 (19)

Testing Practitioner Handbook

4.5 (19)

By: Renu Rajani

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.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

1. State of Digital Transformation – What Has Changed in the Last Four Years (2013-16)?

1. State of Digital Transformation – What Has Changed in the Last Four Years (2013-16)?

Renewed focus on efficiency and effectiveness

QA and testing transformation focus

QA and testing transformation drivers

State of digital maturity

Spends for digital QA

Predictions on the level of cloud-based applications

Increased challenges in mobile and IoT multichannel testing

Reduction in customer experience testing challenges

Conclusion

2. Future of Testing Engagement Models – Are Predictions of Increased QA Spends Justified?

2. Future of Testing Engagement Models – Are Predictions of Increased QA Spends Justified?

How is QA effort spread

QA organizations would follow hybrid QA teams (centralized and decentralized)

What will be the future of testing engagement models?

Conclusion

References

3. The Benefits of Replacing Testing Subcontractors with Managed Testing Services

3. The Benefits of Replacing Testing Subcontractors with Managed Testing Services

Findings from the World Quality Report 2016 on industrialization and testing centers of excellence

Use of direct subcontractors remains prevalent

Key challenges associated while working with subcontractors

How replacing testing subcontractors with managed testing services helps

Conclusion

4. Digital Quality Assurance in a Factory Model

4. Digital Quality Assurance in a Factory Model

Services factories

A digital factory model for industrializing digital QA delivery

Key Elements for Onboarding in DQAF

Benefits delivered through DQAF model

Conclusion

5. Crowdsourcing – Enabling Flexible, On-Demand Testing COEs

5. Crowdsourcing – Enabling Flexible, On-Demand Testing COEs

Trends - crowdsourced testing

What is crowdtesting and how does it work?

Crowdtesting operating models

Crowdtesting as part of Testing Center of Excellence (TCOE)

The benefits of crowdtesting

Conclusion

References

6. Testing Goes an Extra Mile over Weekends

6. Testing Goes an Extra Mile over Weekends

Weekend testing – modus operandi

Advantages

Disadvantages

Trends in the use of crowdsourced testing

How can large IT organizations ride the weekend testing bandwagon?

Conclusion

References

7. Testing in Agile Development and the State of Agile Adoption

7. Testing in Agile Development and the State of Agile Adoption

What do agile projects promise compared to traditional waterfall?

Flavors of agile

How is testing done in agile sprints?

Agile in distributed environments

State of agile adoption – findings from the World Quality Report 2016-2017

Conclusion

8. Agile and DevOps Adoption are Gaining Momentum

8. Agile and DevOps Adoption are Gaining Momentum

Increased use of agile/DevOps principles

Increased complexity of testing in the agile landscape

Challenges cited in setting up agile test COEs

How is QA transforming to meet the demands of agile/DevOps life cycles

What is the difference between testing in DevOps and traditional life cycle?

Conclusion

9. Does the Rise of DevOps Undermine Agile?

9. Does the Rise of DevOps Undermine Agile?

Agile is about speed

DevOps removes the boundaries between dev, QA, and operations

Agile versus DevOps

Conclusion

10. Role of Automation in DevOps Life Cycle

10. Role of Automation in DevOps Life Cycle

The importance of automation in DevOps

Early integration automation

Automation – the default practice

Deployment automation

Automation – metrics and measurements

Best practices to adopt early and continuously automate

Conclusion

11. Assessing the State of Your DevOps Adoption with DevOps Benchmarking Approach

11. Assessing the State of Your DevOps Adoption with DevOps Benchmarking Approach

Why DevOps – the drivers

Challenges organizations face in implementing DevOps

DevOps QA benchmarking — why and what?

DevOps QA benchmarking assessment areas

Conclusion

12. Accelerating DevOps – ChatOps is the New Cool

12. Accelerating DevOps – ChatOps is the New Cool

DevOps trends from World Quality Report

ChatOps – How does it work?

Application of ChatOps as a collaboration platform

Benefits of ChatOps

Conclusion

13. Behavior-Driven Development (BDD) Using Gherkin in Agile/DevOps Environment

13. Behavior-Driven Development (BDD) Using Gherkin in Agile/DevOps Environment

Background – Behavior-Driven Development (BDD)

Gherkin – basic syntax and illustration

Roles of members involved

Benefits of using Gherkin

Conclusion

14. Automating Configuration Management for DevOps Test Environments

14. Automating Configuration Management for DevOps Test Environments

Background

Types of test environments

Potential solutions for automated configuration management

The benefits of automating configuration management

Conclusion

15. Automated Test Data Management in the DevOps Environment

15. Automated Test Data Management in the DevOps Environment

Background

TDM in DevOps environment – key challenges

Automated TDM solution for DevOps environment

Typical TDM services and TDM architecture

Benefits of automated TDM

Best practices in TDM

Conclusion

16. Testing in DevOps Life Cycle Using Microservices Architecture

16. Testing in DevOps Life Cycle Using Microservices Architecture

What is microservices architecture?

Testing in agile/DevOps life cycle using Microservices Architecture

Performance testing of Microservices

Monitoring Microservices

Conclusion

17. Automated Test Environments for DevOps

17. Automated Test Environments for DevOps

Test Environment Management – key challenges

Test environment automation approach for DevOps

Benefits of test environment automation

Test environment metrics to consider in release management

Test environment automation tools

Conclusion

18. Service Virtualization as an Enabler of DevOps

18. Service Virtualization as an Enabler of DevOps

Service virtualization and DevOps

Role of service virtualization in DevOps

Service virtualization – research input

Service virtualization automation tools used in DevOps

Conclusion

19. Best Practices in Identifying Regression Test Cases

19. Best Practices in Identifying Regression Test Cases

Background – software regression testing

Software regression process

How should one choose test cases for regression?

Conclusion

20. Accessibility Test Automation in DevOps Environment

20. Accessibility Test Automation in DevOps Environment

Background – Accessibility (AX)

AX and DevOps

AX test automation in DevOps

Standard AX tools

Conclusion

21. Performance Tuning of Java Applications

21. Performance Tuning of Java Applications

Performance bottlenecks – key challenges and solutions

Java performance tuning tools

Conclusion

22. Testing Mobile Applications – Key Challenges and Considerations

22. Testing Mobile Applications – Key Challenges and Considerations

User expectations

Key challenges encountered in testing mobile applications

Recommendations to enhance mobile applications usability

Conclusion

23. Testing Analytics Applications – What Has Changed in SMAC World

23. Testing Analytics Applications – What Has Changed in SMAC World

Understanding your customers, gathering data and analyzing it

Testing the data

Testing the BI/BA applications

How is testing done differently for big data/Hadoop applications?

Conclusion

24. Migrating Applications to Cloud Environments – Key Testing Considerations

24. Migrating Applications to Cloud Environments – Key Testing Considerations

Need for validating applications for cloud migration

Key testing focus areas in cloud migration of applications

Key challenges in validation during cloud migration of applications

Application migration validation – a holistic approach

Conclusion

25. How Should a Tester Adapt to Cloud – Call for Change of Mindset among Testers

25. How Should a Tester Adapt to Cloud – Call for Change of Mindset among Testers

What must testers prepare for when testing applications on cloud

Conclusion

26. On-Demand Performance Testing on Self-Service Environments

26. On-Demand Performance Testing on Self-Service Environments

On-demand performance testing environments — key challenges and solutions

Need for a cloud platform to build end-to-end performance testing

On-demand self-service environments for carrying out performance testing

Key scenarios for on-demand performance testing – proposed architecture

Conclusion

27. Quality Assurance for Digital Marketing Initiatives

27. Quality Assurance for Digital Marketing Initiatives

Evolution of digital marketing

Challenges of implementing digital marketing

Need for quality focus in digital marketing initiatives

QA of digital marketing applications – key validations

Conclusion

28. Security Dashboard for the Board

28. Security Dashboard for the Board

Why security threats need to be monitored and reported?

What should be monitored and reported?

Specific metrics to be reported in dashboard

Consequences of security lapses

Key challenges in implementing a dashboard

Conclusion

29. Applying Robotic Automation to Mobile Applications Testing

29. Applying Robotic Automation to Mobile Applications Testing

Software robot and their applicability

The benefits of Robotic Process Automation (RPA)

Implementing RPA for mobile testing

Conclusion

References

30. Key Considerations in Testing Internet of Things (IoT) Applications

30. Key Considerations in Testing Internet of Things (IoT) Applications

Need for a robust IoT test strategy

IoT Revolution – key findings from the World Quality Report 2016

IoT Testing Considerations

IoT testing types

Conclusion

References

31. Algorithmic Business – In Need of Model-Based Testing

31. Algorithmic Business – In Need of Model-Based Testing

Introduction and journey of analytics

Algorithmic business – an illustration

Implications of testing – the need for model-based testing

Conclusion

32. Making Testing Adaptive, Interactive, Iterative, and Contextual with Cognitive Intelligence

32. Making Testing Adaptive, Interactive, Iterative, and Contextual with Cognitive Intelligence

Background – cognitive intelligence

What is cognitive testing all about?

Evolution of cognitive technology and available platforms

Methodologies involved in cognitive testing

Advantages of cognitive testing compared to the current methods

Sector specific use cases

Technologies supported

Costs involved

Challenges associated in implementing cognitive technologies

Conclusion

33. FinTech – A New Disruptor in Industry and Implications for Testing and QA

33. FinTech – A New Disruptor in Industry and Implications for Testing and QA

FinTech ecosystem

FinTech services and their impact on various sectors

Testing for FinTech applications or solutions

Conclusion

34. Blockchain Technology – Assuring Secure Business

34. Blockchain Technology – Assuring Secure Business

Introduction to blockchain

The blockchain process

Popular blockchains

Implication for testing

Conclusion

35. Technologies for Digital Supply Chains and QA Considerations

35. Technologies for Digital Supply Chains and QA Considerations

Understanding the customer buying process

Industry trends in supply chain management

New technologies in supply chain management

An illustration – new technologies in retail

Focus of QA in supply chain

Conclusion

36. Potential Innovations in eHealth-Care – Implications for Testing and QA

36. Potential Innovations in eHealth-Care – Implications for Testing and QA

Digital transformation trends in the healthcare sector

Applications of digital eHealth-Care care

Digital eHealth-Care care ecosystem

Typical challenges in digital eHealth-Care care

Need for robust digital QA

An illustrative customer journey validation of patient using wearables

Conclusion

37. Trends in the Global Automotive Sector – Implications for Testing and QA

37. Trends in the Global Automotive Sector – Implications for Testing and QA

Business drivers for global automotive evolution

Key highlights from the growing Chinese automotive market

Influence of global automotive trends on the Chinese market

How are trends in automotive segments shaping software testing?

Conclusion

38. Digital Transformation in Consumer Products and Retail Sector – QA Considerations

38. Digital Transformation in Consumer Products and Retail Sector – QA Considerations

Current challenges in the consumer products and retail sector

Physical versus online stores – key trends

Digital transformation in CPR industry

Customer journey of a digital shopper in an omni-channel environment – an illustration

Being digital – what value levers can it offer to CPR industry

Factors considered by digital shoppers

Multi/omni-channel CPR – quality considerations

Digital transformation in CPR - tests required

Conclusion

39. Digital Transformation Trends in Energy and Utilities – QA Considerations

39. Digital Transformation Trends in Energy and Utilities – QA Considerations

Technology trends in utilities industry

Key technology blocks of digital transformation in the EUC sector

Challenge of multichannel and the need for a unified customer journey

Testing considerations in an EUC customer journey – an illustration

Testing considerations in smart metering infrastructure – an illustration

Digital transformation QA trends in EUC

Conclusion

References

40. Smart Energy and Smart Grids – in Need of Effective Testing

40. Smart Energy and Smart Grids – in Need of Effective Testing

Background

Trends in Energy and Utilities (E&U)

Typical challenges in the E&U segment

Smart Meters and Smart Grids

Testing process for Smart Metering Infrastructure (SMI)

Conclusion

41. Testing Airline Digital Applications – Case for Responsive Design

41. Testing Airline Digital Applications – Case for Responsive Design

Background – the state of the airline business

Role of digitization

QA and testing in the airline industry

Testing responsive web designs

Conclusion

42. Orthogonal Array Testing (OAT) – an Application in Healthcare Industry

42. Orthogonal Array Testing (OAT) – an Application in Healthcare Industry

Background

Challenges in H&LS applications testing

How can Orthogonal Array Testing Strategy (OATS) help?

Conclusion

43. Future of Consulting in the Era of Digital Disruption

43. Future of Consulting in the Era of Digital Disruption

Digital driving a shift in the way consulting worked

The digital age consultant

Future of consulting

What would I do differently as a consultant now?

Conclusion

44. Future of Testing in the Digital World

44. Future of Testing in the Digital World

Key technology trends that would shape the future of Information Technology

Testing considerations for new technologies

Conclusion

45. Future of Testing – Career Opportunities

45. Future of Testing – Career Opportunities

Career options in testing services

Typical roles in testing services

The importance of industry and domain, technology and tools, and process skills in testing careers

Required skills for agile and DevOps testing

New breed of testers in DevOps

Conclusion

46. Robotics and Machine Learning Combined with Internet of Things – What Could This Mean for Indian Services Industries

46. Robotics and Machine Learning Combined with Internet of Things – What Could This Mean for Indian Services Industries

Understanding the context – robotics, machine learning, and IoT

What does advancement of technology mean for the Indian economy?

Outlook for the the services sector in India – a point of view

Conclusion

A. References

Across Chapters – World Quality Report 2016 (Capgemini, Sogeti, HPE):

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 18 – Service Virtualization as an Enabler of DevOps

Chapter 30 – Key Considerations in Testing Internet of Things (IOT) Applications

Chapter 31 – Algorithmic Business – In Need of Model-Based Testing

Chapter 46 – Robotics and Machine Learning Combined with Internet of Things – What could this mean for Indian Services Industries

Index

Index

Conclusion

In this chapter, we considered data points about an increased split of QA effort in development projects as against production support. This aligns with the need for more QA in new development projects associated with digital transformation. We also considered the trend of increased QA effort in the design phase, which aligns with the need for Shift-Left and Shift-Right principles in the DevOps life cycle.

We considered data points relating to the future of centralized with regard to the decentralized models of QA and concluded that the future will see the use of hybrid models. Organizations will continue to use MTS and Centralized COEs for business as usual functions to carry out QA efficiently. For the digital transformation initiatives and projects in the Agile/DevOps life cycle, the projects will carry out testing in the decentralized mode. Distributed Agile is an option that is also considered.

We then discussed future testing engagement models with a 3-plateau approach to...

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