Conference Presentations

STAREAST Testing in Production
Slideshow

How do you know your feature is working perfectly in production? And if something breaks in production, how will you know?

Talia Nassi
STAREAST The Reality Distortion Field of Testing
Slideshow

The reality distortion field (RDF) is a term coined by Bud Tribble at Apple Computers in 1981 to describe Steve Job's charisma and its effect on the developers working on the Macintosh project.

Lloyd Roden
STAREAST API Testing: Going from Manual to Automated
Slideshow

API testing can be challenging—especially for the uninitiated. Ever wonder what makes an API test great? Patrick Poulin will arm you with an understanding of the benefits of automating API testing over doing it manually.

Patrick Poulin
STAREAST The Who, What, Where, When, and How of Test Strategies
Slideshow

What is a test strategy, and how do you develop one? Join Adam Satterfield and Janna Loeffler as they talk through developing a test strategy.

Janna Loeffler
Agile DevOps East Continuous Testing Is Not Test Automation
Slideshow

The DevOps movement is front and center across enterprises. Companies with mature systems are breaking down siloed IT departments and federating them into product development teams and departments. Testing and its practices are at the heart of these changes, so companies are turning to continuous testing with the hopes that they can automate their way through the testing bottleneck by focusing on automating regression tests. But this strategy is failing. Adam Auerbach will explain why he thinks that is, what true continuous testing looks like, and how continuous testing should be implemented. Adam will demonstrate that to keep pace with development in the new “you build it, you own it” environment, testing teams and individuals must develop new technical skills and even embrace coding to stay relevant and add more value to the business.

Adam Auerbach
STARCANADA Mobbing for Test Design: Connecting with Your Colleagues’ Test Ideas
Slideshow

Do you have trouble generating test case ideas? Are there seemingly obvious bugs getting through your test plan? Are you considering revamping your current test analysis and design? If you answered yes to any of these questions, then this session is for you. You may have heard of mob...

Jeff MacBane
STARCANADA Testing at 43,000 Feet: Reporting Risk That Matters
Slideshow

Testing dashboards can give stakeholders the false impression that projects are under control. But are they really? As a tester, you can see a counter indicating a high percentage of passing tests but know that you may still have critical failures in the product. Alexandre Bauduin will...

Alexandre Bauduin
STARCANADA Ditch Your Bug-Tracking Tool: 3 Solid Tactics to Minimize Bug Counts
Slideshow

A bug-free product release is an ideal that testers, developers, and project managers strive for, but when it comes to the go/no-go decision, the balance is often struck between "good" and "good enough," leaving behind a rotting to-do pile in the bug-tracking tool that is rarely acted upon...

Jerry Penner
STARCANADA Gaining Consciousness
Slideshow

Testers make difficult decisions with minimal information in turbulent times on critical projects.  Independent consultant, Fiona Charles, suggests that testers must learn to draw a line in the decision-making process between trained intuition and careless assumption.  In this...

Fiona Charles
Fighting Test Flakiness: A Disease that Artificial Intelligence Will Cure
Slideshow

Artificial Intelligence (AI) is making it possible for computers to diagnose some medical diseases more accurately than doctors. Such systems analyze millions of patient records, recognize underlying data patterns, and generalize them for diagnosing previously unseen patients. A key challenge is determining whether a patient's symptoms and history are attributed to a known disease or other factors. Software testers face a similar problem when triaging automation failures. They investigate questions like, Is the failure due to a defect, environmental issue, or nondeterministic test script? Is there current or historical evidence to support one belief over another? Join Tariq King as he describes how test failures and flakiness can be modeled for machine learning (ML) as causal disease-symptom relations.

Tariq King

Pages

AgileConnection is a TechWell community.

Through conferences, training, consulting, and online resources, TechWell helps you develop and deliver great software every day.