Teams everywhere are looking to speed up testing without sacrificing quality, so once again, some of the top articles last year were about continuous integration, machine learning, and—of course—how to best implement and use test automation. But readers were also interested in what they shouldn't be doing, with two high-ranking articles about test practices we should stop and a tool you may be misusing.
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.
There is much published about the data we generate to assess product quality. There is less discussion about the data testers generate for our own use that can help us improve our work—and even less is said about recommended practices for data collection. Test data collection, management, and use all call for upfront planning and ongoing maintenance. Here's how testers can improve these practices.
Stacy Kirk, CEO at QualityWorks Consulting Group, discusses how testers can go from champions of quality to true QA heroes. She says people in testing are the unspoken heroes of software, and details what needs to change so they can find their voices to step up and lead. Stacy also talks about how far women in tech have come and how much value they bring, as well as discusses the challenges she has faced as a female CEO and how much it has taught her, both in and out of the tech world.
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.
Janna Loeffler, manager of quality engineering at Ultimate Software, discusses the importance of detailing a test strategy, along with the most crucial aspect: communication. She talks about how testers are often not comfortable saying “I don’t know,” and about how they should get out of their comfort zone to ask for help. She also gives insight into strategies people can take to admit they don’t know without fear, and seeking answers and conversations from others in the testing community.
When people do not have good luck with automation, it is hardly ever because of the tool being used, but almost always because of the wrong automation strategy, wrong expectations, and wrong adoption of automation. Automation tools only answer the “how” of automation, while having an automation strategy gives answers to who, where, when, what, and why. Here's why it's so important to have a test automation strategy.
Selenium has widespread adoption as a test automation tool, but it comes with some challenges. We talked to some experts in the test automation industry about Selenium’s reign as the tool of choice for UI testing, whether that crown is warranted, and what they think is important for teams to focus on when it comes to their test automation efforts. Then, Parasoft talks about how teams can solve UI testing challenges and make Selenium more maintainable with its new product, Parasoft Selenic.
When you are running against time but still cannot afford to cut corners while testing, automation is a good solution. You can release high-quality software within a short span of time, detect more errors and bugs, and align your testing with agile development. Here’s how you can set up an automated testing initiative to overcome delivery challenges and improve your testing outcomes.