Perforce Software announced the release of the book, “Accelerating Software Quality: Machine Learning and Artificial Intelligence in the Age of DevOps.” This announcement was a part of Perforce’s virtual meeting on ML and AI in DevOps.
About Perforce
Perforce powers are at an unrivalled level. With the assistance of scalable DevOps solutions, they assist enterprises to overcome complicated product development challenges by enhancing security, visibility, and productivity throughout the products lifecycle. Their portfolio includes Repository Management, Embeddable Analytics, Solutions for Agile Planning and ALM, Dynamic Code Analysis, Automated Mobile and Web Testing, API Management, Version Control, Open Source Support, and more. With around 15,000 clients, Perforce is trusted by some of the world’s dominating brands to operate their business-critical technology development.
“My latest book provides a complete overview of the use cases for AI and ML in software development and testing, along with practical tools and examples for managers and practitioners looking to enhance their overall productivity, automation, and efficiency. My hope is that readers will be better positioned to make decisions as they adopt AI/ML technologies on their DevOps journey,” says Kinsbruner.
“Accelerating Software Quality” is a book written by best-selling author Eran Kinsbruner, and spearheaded by Perforce. The book covers the basics of ML and AI in testing and software development and also gives practical tips in applying commercial and open source ML/AI tools. Along with Kinsbruner’s insights around 20 DevOps leaders have also provided their views on how ML and AI will influence existing tools, apps, and processes.
Additional topics expressed in the book comprise automated security scanning for vulnerabilities, API testing and management using ML/AI, chatbot testing, reducing effort and time through test impact analysis (TIA), visual-based testing using AI, automated code reviews, robotic process automation (RPA), the prevention of production defects, and AIOps for smarter code deployments and more.
