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Machine Learning Heralds the End of Selenium
Slideshow
Selenium has been the cure for free and low-cost browser testing for years, and—in the world of agile, mobile, DevOps, and browserless interfaces—it is showing its age. Comparing Selenium to what’s coming, Jason Arbon says that machine learning and data analytics will become the new standard for test automation. With Selenium, test engineers suffer from the pains of broken element identification; broken, buggy, and partially implemented mobiletest capabilities; exploding costs of building abstraction layers on their apps; brittle test code when the application under test changes; and absence of any context or test logic in the framework. Jason unwraps the work that several startups and projects initiated in the past twenty-four months are actively doing to fix these issues with new general-purpose, test frameworks that combine machine learning and data analytics.
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Jason Arbon
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Continuous Testing vs. Test Automation: Three Key Differences
Slideshow
The past few years have brought a sea change in the way applications are architected, developed, and consumed—increasing both the complexity of testing and the risk of software failures. Given the trends that impact both architectures (cloud, microservices, and APIs) and processes (DevOps, agile, and continuous delivery), how can software testing keep pace with modern application delivery? Enter continuous testing. Wayne Ariola explores the three main differences between continuous testing and test automation.
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Wayne Ariola
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Mindmapping: A General Purpose (Test) Planning Tool
Slideshow
MindMapping is a general technique of organizing your thoughts, aligning your ideas, and breaking things down. It’s uses are, in fact, mind blowing. But in this session, join Bob Galen, as he takes you on a visual tour of mindmapping as applied in the software testing space. We’ll be using a free tool and be creating maps to illustrate test case design, test idea generation, sprint-level test planning, and release-level test planning using mindmaps. Along the way, you’ll also gain some new insights into risk-based testing with an agile twist, as we explore the 3-Amigos metaphor. You’ll leave this session with a rudimentary library of maps and another, quite powerful tool, to add to your toolbox. Bring your laptop or other device, as we’ll be using MindMup to create a few simple mindmaps.
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Bob Galen
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Make Your Team Awesome—Yes, You Can!
Slideshow
The key to creating high-performing teams is psychological safety—the ability to be vulnerable in front of others even when they hold diverse viewpoints, and the opportunity to take risks and trust that everything will be OK. However, creating this safety is easier said than done. Maaret Pyhäjärvi shares her story of working with software development and test teams to enable them to be awesome. She explains how to reinforce the positive while enabling great software product development by empowering others in your team. Maaret explores how to be brave when others are not, and how to care for and build safety for others. She describes being a catalyst for your team, emphasizing learning—always with safety as a prerequisite. Today, Maaret uses her position as a tester not only to test every part of the software but also to build the collaboration habits of the team, delivering actionable information to improve product quality.
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Maaret Pyhäjärvi
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Automated Security Scanning for Your Delivery Pipeline
Slideshow
[video:https://youtu.be/CwZ-F4TUsig width:300 height:200 align:right]
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Matthew Grasberger
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Thirteen Patterns of Testers Thriving in Agile Teams
Slideshow
[video:https://youtu.be/MJEXQY-E304 width:300 height:200 align:right]
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Shaun Bradshaw
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AI-Driven Testing as a Service: Fad, Fiction, or Future?
Slideshow
Advances in artificial intelligence (AI) and machine learning (ML) are leading to a new generation of software, which is becoming self-adaptive, autonomous, and smart. Academic researchers and industry practitioners are investigating how these new AI and ML technologies can be leveraged to improve software testing and testing services. A handful of testing-as-a-service (TaaS) vendors already offer services that use AI bots to perform some functional and performance testing. How well do they live up to their claims? Can they be used as an effective substitute or supplement for human testers? Or is AI-driven testing just another passing trend? Join Tariq King as he discusses the current state-of-the-art in AI-based testing services and explores what this new generation of testing services has to offer. Come see demonstrations of AI-driven testing tools and understand their benefits and limitations.
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Tariq King
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Automated Testing: Beyond the Basics
Slideshow
[video:https://youtu.be/XubfvhFNs0s width:300 height:200 align:right]
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Jim Holmes
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Migrating from Test Cases to Real-World Telemetry Measures
Slideshow
Ken Johnston sees today’s software ecosystem in the light of Everything as a Service (EaaS). Operating systems like Windows, Android, and Chrome OS all ship regularly like a service. Browsers automatically update every few weeks, and apps are constantly updating through all the app stores. Although getting a test to pass once and signing off has gone by the wayside for software testing, still we run test cases over and over again. Ken shares how Microsoft took millions of test cases—yes, actually millions—and turned the important ones into measures based on real world telemetry. Massive amounts of data coming in from real devices and real users measure product quality and tie it to key customer satisfaction metrics.
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Ken Johnston
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Transformation from QA to Engineering: Testing in the Fast Lane
Slideshow
[video:https://youtu.be/IavieFiAUYI width:300 height:200 align:right]
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Jennifer Scandariato
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