WEBINAR
Practical Applications of AI and Machine Learning for Smarter Test Automation
Watch Forrester's VP and Principal Analyst, Diego Lo Guidice, and Parasoft's VP of Products, Mark Lambert, discuss how leading organizations are leveraging these technologies to achieve higher levels of automation and augmentation.
AI and machine learning are the latest buzzwords to hit the software industry, but it seems like everyone has a different interpretation about what they mean, and how they can help organizations be successful. How do we make any sense of it all, and how does it apply to software test automation in a practical way?
In this webinar, Forrester’s VP and Principal Analyst, Diego Lo Guidice, and Parasoft’s VP of Products, Mark Lambert, discuss the state of AI in software testing and how leading organizations are leveraging these technologies for smarter test automation.
Topics covered include:
- How to leverage AI and machine learning in the context of software testing
- How to use machine learning to build a scalable testing practice that is efficient, consistent and change resistant
- Use cases of artificial intelligence and machine learning to help organizations achieve higher levels of automation and augmentation
- How these technologies ultimately unblock the DevOps pipeline to deliver at the speed of agile
About Parasoft
Parasoft’s software testing solutions support the entire software development process, from when the developer writes the first line of code all the way through unit and functional testing, to performance and security testing, leveraging simulated test environments along the way. Parasoft's unique analytics platform aggregates data from across all testing practices, providing insights up and down the testing pyramid to enable organizations to succeed in today's most strategic development initiatives, including Agile/DevOps, Continuous Testing, and the complexities of IoT. Parasoft’s automated software testing innovations fuel software development organizations, helping teams reduce the time, cost, and effort of delivering high-quality software to the market.