Companies that want to reduce testing costs usually try working with fewer people, or even cutting back on the amount of testing done. But with those approaches, quality usually suffers. Releasing a critical bug and suffering the subsequent pain usually costs multiple times what testing would. There are better ways to save money, and it can be done just by being smarter about our test cases and their structure.
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.
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.
Best practices for test automation emphasize reliability, portability, reusability, readability, maintainability, and more. But how can your existing automated test suite adopt these qualities? Should you address these issues with your current tests, or create an entirely new set of tests? Here are some questions that will help you determine if your test automation maintenance program is operating as it should be.
QA testers often take on more of a role than just testing software code. When the team needs help, QA should lend a hand in assisting with business analysis, customer communication, user experience, and user advocacy.
The internet of things (IoT) continues to proliferate as connected smart devices become critical for individuals and businesses. Even with test automation, performing comprehensive testing can be quite a challenge.
Because enterprise applications are highly interconnected, development in stages puts a strain on the implementation and execution of automated testing. Service virtualization can be introduced to validate work in progress while reducing the dependencies on components and third-party technologies still under development.
Shachar Schiff, founder and principal consultant at BadTesting, chats with TechWell community manager Owen Gotimer about the recent rebrand of BadTesting, the four archetypes he uses to help customers, and the universal importance of communication.
In this interview, Melissa Tondi, senior QA strategist at Rainforest, discusses the foundation you need in order to have a positive introduction for new tools and technologies. She explains why the team leader has to understand what motivates each individual and how to get them excited about their job. Melissa says team members also have to realize that if they are in any way involved in testing software, they are a technologist, so they have to embrace the tools and technology that will continuously improve and streamline repetitive tasks.
Technologist and evangelist Peter Varhol and Gerie Owens, a test architect and certified ScrumMaster, discuss their STARWEST presentation, “What Aircrews Can Teach Testers about Testing.” They talk about how testers can apply airline safety practices to their teams’ delivery of high-quality applications through complementary expertise, collaboration, and decision-making. They also explain how blind deference to authority and automation can be detrimental to a testing team, and how to use everyone’s skills to achieve success.
Rob Sabourin, the program chair for STARWEST 2018, discusses the selection process for conference speakers, his favorite aspect of the conference, and the interactive Test Lab. He also details his “Testing in the Dark” talk, which gives strategies to use when you’re required to test software without any requirements, design, or product knowledge.
Are you a leader with a quality problem? Every organization struggles with quality at some point in their product lifecycle. Knowing what to measure and how to build a culture of quality with specific and actionable methods is key.
We are often reminded by those experienced in writing test automation that code is code. The sentiment being conveyed is that test code should be written with the same care and rigor that production code is written with.