The widespread adoption of test automation has created many challenges — for everything from development lifecycle integration to scripting strategy.
One pitfall of automation is that teams often rush to automate everything they can. This is the automation firehose.
However, just because a scenario CAN be automated does not mean it SHOULD be automated. For scenarios that should be automated, teams must adopt implementation plans to ensure tests are reliable and deriving value.
Join this webinar led by Perfecto’s Chief Evangelist, Eran Kinsbruner, along with Thomas Haver, Manager of Automation & Delivery. In this session, the audience will:
- Understand which test scenarios to automate.
- Learn how to maximize the benefits of automation.
- Receive a checklist to determine automation feasibility and ROI.
Chief Evangelist, Perfecto
Eran Kinsbruner is the chief evangelist and author at Perfecto, a Perforce company. He authored two books, The Digital Quality Handbook and Continuous Testing for DevOps Professionals. Eran is also a monthly columnist at InfoWorld.com and The Enterprisers Project. Eran is a software engineering professional with nearly twenty years of experience at companies such as Matrix, Sun Microsystems, General Electric, Texas Instruments, and NeuStar. He holds various industry certifications from ISTQB, CMMI, and others. Eran is a recognized mobile testing influencer and thought leader, as well as an experienced speaker in the major software engineering conferences.
Founder and CEO, Selftest IO
Tariq King is the founder and CEO of Selftest IO, a company on a mission to develop the next-generation of systems and services with intrinsic self-testing properties. Tariq has over fifteen years' experience in software testing research and practice, and has formerly held positions a test architect, engineering manager, director, and head of quality. Tariq holds Ph.D. and M.S. degrees in Computer Science from Florida International University (FIU). His areas of research are software testing, artificial intelligence, autonomic and cloud computing, model-driven engineering, and computer science education.