As the Agile environment has efficient principles that allow quick responses to changes and the ability to deal with uncertainty, exploratory testing may seem like a perfect match for such projects. However, this is only partially true. In reality, diverse reasons impede its usage in Agile projects, and companies should take them into account before designing QA strategies.
Protractor has been a popular choice for writing end-to-end (E2E) browser tests over the past decade. However, Protractor is being removed from the Angular project as of Angular 15 due to a loss of dedicated developers and the rise of better testing frameworks. Based on this state of affairs, what should developers working with Protractor do, and what tool choices do developers have going forward?
All around us, we are seeing a growing trend of artificial intelligence (AI) being implemented in every aspect of our lives—from self-driving cars to intelligent chatbots. But what about the world of DevOps? Has AI come to play a role here as well? The growing role of AI in DevOps has unearthed some key benefits it can bring to many DevOps workflows.
The approach to test via comparison of multiple API responses between production and test code versions is very effective and produces the required results, release over release. Improvements and changes, however, are needed to address changing needs. This is true for most if not all tech solutions; the economics principle ‘Law of Diminishing Marginal Utility’ also applies to software. A tech solution that excited stakeholders when first introduced could become stale very soon. A revamp or a new solution is needed to match evolving expectations.
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.
In the software community, the emergence of AI has stoked thoughts of both possibility and concern about its impact. For software testers, the critical questions swirling around AI are: “What is the future of testing in a world of AI? Will testers become obsolete?” Coveros CEO Jeff Payne talked with testing and AI expert and CEO of TestersAI, Jason Arbon, to find out what the emergence of AI means for the testing and software community.
Greg Paskal, evangelist in testing sciences and lead author for RealWorldTestAutomation.com, chats with TechWell community manager Owen Gotimer about testing as a craft, choosing the right test automation tools, and current testing trends around the world.
Talia Nassi, developer advocate at Split Software, chats with TechWell community manager Owen Gotimer about the fears, myths, and benefits of testing in production and how to get your stakeholders on board. Continue the conversation with Talia (@Talia Nassi) and Owen (@owen) on the TechWell Hub (hub.techwell.com)!
Melissa Benua, director of engineering at mParticle, chats with TechWell community manager Owen Gotimer about the importance of whole team quality, how to get started using the test pyramid, and how developers can start writing testable code.
Most modern testing, especially in a DevOps model, uses a lot of telemetry to evaluate and monitor quality of experience for apps and services. In this interconnected world, there is power and risk in data. Ken Johnston will share his personal experiences dealing with US and European Union privacy regulations and the methods he and his team have implemented to mitigate the potential of significant penalties for the misuse of data. He will cover privacy-preserving techniques such as differential privacy and private enclave, what constitutes primary versus secondary uses of data, and how you should handle personally identifiable information (PII). You'll leave with a better understanding of how to keep data private and secured, as well as how to keep your team adhering to privacy best practices and regulations.
Serverless cloud applications are rapidly moving into the mainstream. In this model, teams focus on developing and deploying code on a known technology stack and runtime, with fixed interfaces for application, database, and network.