Project Management

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Person parasailing 5 Steps to Getting Started with Risk-Based Testing

Risk-based testing is an approach to testing that helps us handle our limited resources. It’s also a valid model for years to come because it focuses testing resources where they can have the most impact—regardless of whether limitations are due to budget, tight schedules, or even the uncertainty of an unexpected situation like COVID-19. Here are some practical tips, examples, and steps you can use to adopt risk-based testing.

Shawn Jaques's picture Shawn Jaques
Agile developers and testers collaborating Testing in Agile: How to Get Started

There is a lot of interest in organizations around a transformation to agility. However, the focus is usually on agile development, so it may not be clear how software testing is done in agile. If you're responsible for leading your testing teams, don't let them be left behind. Here’s how you can make testers part of the transformation, too—step by step, because this is agile, after all.

Balazs Schaffhauser's picture Balazs Schaffhauser
Tester and developer shaking hands across a table How to Collaborate on a Brand-New QA Team

As a quality analyst, when you raise a bug, developers sometimes react as if you were personally attacking their job. The situation can be even more difficult if you are starting a new QA team, where you will work with people who have never had the quality assurance component. Here is some advice for ways you can be effective when you’re starting on a team that has never worked with quality analysts before.

Juan Pablo Aguirre's picture Juan Pablo Aguirre
Woman wearing a hard hat and working with a machine Blending Machine Learning and Hands-on Testing

As your QA team grows, manual testing can lose the ability to focus on likely problem areas and instead turn into an inefficient checkbox process. Using machine learning can bring back the insights of a small team of experienced testers. By defining certain scenarios, machine learning can determine the probability that a change has a serious defect, so you can evaluate risk and know where to focus your efforts.

James Farrier's picture James Farrier
Car dashboard with various meters and dials 5 Key Elements for Designing a Successful Dashboard

When you’re designing a dashboard to track and display metrics, it is important to consider the needs and expectations of the users of the dashboard and the information that is available. There are several aspects to consider when creating a new dashboard in order to make it a useful tool. For a mnemonic device to help you easily remember the qualities that make a good dashboard, just remember the acronym “VITAL.”

Nels Hoenig's picture Nels Hoenig
Cards and chips at a casino Risk Coverage: A New Currency for Testing

In the era of agile and DevOps, release decisions need to be made rapidly—preferably, even automatically and instantaneously. Test results that focus solely on the number of test cases leave you with a huge blind spot. If you want fast, accurate assessments of the risks associated with promoting the latest release candidate to production, you need a new currency in testing: Risk coverage needs to replace test coverage.

Wolfgang Platz's picture Wolfgang Platz
Pawn chess piece with a king's crown on top Zero to SME: Quickly Becoming Your Own Subject Matter Expert

On a new project, we often lack the luxury of having a subject matter expert available to answer our questions. When that’s the case, we have to become our own SME. Here are a few key methods from the writings and presentations of experts in various fields that deal with information gathering and rapid learning. You can easily use these methods, right now, to quickly gain the knowledge you need in order to move forward.

Thomas Sullivan's picture Thomas Sullivan
Laptop screen showing test data analytics Applying Data Analytics to Test Automation

Testers gather lots of metrics about defect count, test case execution classification, and test velocity—but this information doesn't necessarily answer questions around product quality or how much money test efforts have saved. Testers can better deliver business value by combining test automation with regression analysis, and using visual analytics tools to process the data and see what patterns emerge.

Harsh Vardhan's picture Harsh Vardhan
Computer showing data analysis Rookie Mistakes in Data Analytics

It's easy to make simple mistakes in data analysis. But these little mistakes can result in rework, errors, and—in the worst case—incorrect conclusions that lead you down the wrong path. Making small process changes can help you steer clear of these mistakes and end up having a real impact, both in the amount of time you spend and in your results. Here are some tips for avoiding rookie mistakes in data analytics.

Nels Hoenig's picture Nels Hoenig
Developers and testers giving each other useful feedback Improve Tester-Developer Relationships with Helpful Feedback

Testers and developers often have a strained relationship. Each side has a certain level of expectations as to what the other side should know and do, while there is little understanding of the constraints, conditions, and requirements that the other team has to work within. But it does not have to be this way. A little effort in giving more specific and helpful feedback can go a long way toward improving attitudes.

Michael Stahl's picture Michael Stahl

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