In this episode we’ll be test talking with Eran Sher, CEO and co-founder of SeaLights.io, about software quality analytics and why analytics are so important in today’s fast-paced software developing and testing world. Discover actionable tips on how to track and optimize your testing efforts to increase your team’s velocity without sacrificing quality.
About Eran Sher
Eran has over 20 years experience as an entrepreneur, building emerging and high growth enterprise software companies. He is currently the Co-Founder and CEO of Sealights, the first cloud-based, continuous testing platform. Prior to founding SeaLights, Eran co-founded Nolio (One of the first Application Release Automation platform) which was acquired by CA Technologies. Following which, Eran lead the DevOps Business Unit as VP Strategy.
Prior to Nolio, Eran held senior management positions at PortAuthority Technologies ( acquired by Websense), Mercury Interactive ( acquired by HP) and Conduct ( acquired by Mercury Interactive).
SeaLights is the #1 software Quality Intelligence Platform. With SeaLights you can increase velocity and eliminate the risk of technical debt with software quality analytics by improving the visibility of code activity, tests, and releases.
To do this they built the next generation Test, Code & Quality management platform that makes quality measurable across all tests, tools, technologies, and environments!
Quotes & Insights from this Test Talk
- We managed to speak with hundreds of engineering software engineering leaders, Quality Assurance leaders, DevOps leaders and I think the main message that what we are hearing from the market is the need for velocity. We are saying that software development is changing and most of the changes are the changes are around the velocity of development. And then of course velocity of testing as well. That imposes a lot of new challenges on software development teams and on quality assurance teams.
- Software quality intelligence is a term that we can come up with. The idea is that software development is becoming so fast and so distributed that it’s becoming very hard to determine what’s your quality. There are three main challenges with quality. One it’s very hard to determine what’s your quality. Second It’s very hard to determine which test you need to execute. This is why everyone executes all their tests all the time. And we know that it’s going to be a bottleneck because you keep adding test all the time especially in a continuous integration continuous delivery environment. And the third one is that it’s very hard to determine which test you need to develop and which just you don’t need to develop. So quality intelligence, the concept, is the ability to use data analytics that can provide you with real-time data and offline data to answer those questions.
- I think everyone would agree that Sprint planning is mainly focused on defining the user stories for the coming sprint. And then the planning of the quality activities or the test development activities are pretty straightforward. An automation engineer or a developer will need to develop the functional, integration test, not just the units they are being tasked by — guys developed tests to those user stories and the definition of done would be that these new tests for those users stories will pass will pass successfully. But we also found that there is no way today to actually verify that those tests were developed properly. That there were no code changes that were done as part of this sprint that those tests were not actually testing it at all. You don’t have this visibility.
- With our test gap analytics now the scrum master, the product owner the dev team leader the QA architect is the Test architect. Now as part of the Sprint planning they’re able to pull the test gap analytics report, understand where are the high-risk gaps and then decide if they’re going to develop specific tests in that specific sprint to start closing the gap.
- One of the main things that will happen in 2019 where we’ll see this transition to not just AI and machine learning in test automation but in managing quality thru data analytics and not just opinions and feelings and experience.
- My best advice, not just for software quality, is use data. It’s much much easier to make decisions or you have data to make better decisions. And if it’s in software engineering and quality now you have the data. So use it.
Connect with Eran Sher
- Blog: https://www.sealights.io/blog/
- Company: www.sealights.io
- LinkedIn: Eran Sher
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