Book Image

Testing Practitioner Handbook

By : Renu Rajani
Book Image

Testing Practitioner Handbook

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.
Table of Contents (56 chapters)
Testing Practitioner Handbook
Credits
About the Author
Acknowledgement
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Index

Methodologies involved in cognitive testing


Cognitive testing leverages machine learning, artificial intelligence, natural language processing, speech-to-text, image recognition, and similar cognitive computing techniques. Cognitive testing uses heuristics to predict defects and to measure system performance and optimize the test coverage based on assessed risk.

Products such as IBM Watson, Google Deepmind, and Microsoft Oxford provide platform for cognitive computing. The same can be leveraged for solving test optimization problems. Some examples of how cognitive intelligence can be leveraged in testing are as follows:

  • Test prioritization

  • Automated regression test bed selection and prioritization

  • Failure prediction using log analyzers

  • Test coverage optimization

  • Comparing product module patterns in production vis-à-vis test coverage

  • Bridging the gap in test coverage

  • Determining how much testing is enough

  • Assessing release readiness and provide a decision on halting regression

  • Providing a risk index...