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How (Not) to Measure Quality
Measuring quality requires many questions to be answered. The most obvious ones may be: “What is quality?”, but also “How can we measure it?”, “Which metrics are most accurate?”, “Which are most practical?”.
In this talk, I share some general motivations for measuring quality. I review commonly used metrics that claim to measure quality, I rate them with regards to how they may be helpful or harmful to achieve actual goals. I give some examples how the weaknesses of one metric might be countered by another one to create a beneficial system.
Target Audience: Developers, Project Leader, Manager, Decision Makers, Quality Engineers, Testers, Product Owners
Prerequisites: Basic Software Project Experience, Rough Understanding of Software Development
Level: Advanced
Extended Abstract:
Measuring quality requires many questions to be answered. The most obvious ones may be: “What is quality?”, but also “How can we measure it?”, “Which metrics are most accurate?”, “Which are most practical?”.
In my experience, one question is often not answered or postponed until it is too late: “Why do we want to measure quality?” Is it because we want to control how well our developers are performing? Is it to detect problems early? Is it to measure the impact of changes? Is it the product or the process we care about? Is it to improve locally in a single team or globally across the company? Is there a specific problem that we are trying to solve, and if so, which one?
Instead of trying to define what software quality is – which is hard and depends on a lot of factors – we should first focus on the impact of our measuring. Some metrics may work great for one team, but not for the company as a whole. Some will help to reach your team or organizational goal, some will not help at all, and some will even have terrible side effects by setting unintended incentives. Some can be gamed, others might be harmful to motivation. Consider an overemphasis on lead time, which can lead to cutting corners. Or measuring the number of bugs found, which can cause a testers versus developers situation.
In this talk, I share some general motivations for measuring quality. I review various commonly used metrics that claim to measure quality. Based on my experience, I rate them with regards to how they may be helpful or harmful to achieve actual goals and which side effects are to be expected. I give some examples how the weaknesses of one metric might be countered by another one to create a beneficial system.
Michael Kutz has been working in professional software development for more than 10 years now. He loves to write working software, and he hates fixing bugs. Hence, he developed a strong focus on test automation, continuous delivery/deployment and agile principles.
Since 2014 he works at REWE digital as a software engineer and internal coach for QA and testing. As such his main objective is to support the development teams in QA and test automation to empower them to write awesome bug-free software fast.
The State and Future of UI Testing
UI testing is an essential part of software development. But the automation of UI tests is still considered too complex and flaky.
This talk will cover the "state of the art" of UI testing with an overview of tools and techniques. It will be shown which kind of representations are used by today's test tools and how the addressing of elements in the UI is done.
In addition, the role of artificial intelligence in the different approaches is shown and a prediction of testing tools of the future is presented.
Target Audience: Developers, Testers
Prerequisites: Basic Knowledge of UI-Testing
Level: Advanced
Extended Abstract:
UI testing is an essential part of software development. Despite technological progress, the automation of UI tests is still considered too complex to function completely without manual intervention.
In addition to classical selector-based approaches, more and more image-based methods are being pursued.
This talk will cover the "state of the art" of UI testing with an overview of tools and techniques. In particular, current problems and future developments will be discussed. Furthermore, it will be shown which kind of UI representations are used by today's test tools and how the addressing of elements in the user interface is done.
In addition, the role of artificial intelligence in the different approaches is shown and a prediction of testing tools of the future is presented on the basis of current research.
Johannes Dienst is Developer Advocate at askui. His focus is on automation, documentation, and software quality.
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