Over the past few years, software development has undergone a significant overhaul. Agile, DevOps, and continuous delivery are testimonies to organizations running things faster. When it comes to software testing, decreasing time-to-market without damaging the quality of the product is key. Users expect quick updates, fixes, and advanced features. Testers have to help their teams meet these needs while also bringing the costs down. Continuously reviewing testing trends and improving processes is central to testing optimally. With test analytics, testing organizations can identify areas of improvement, accelerate tests, and release better software faster.
Essentially, automated software testing is a quality control mechanism for vetting the operational aspects of the software. The goal is to develop a rigorous testing process that operates through test automation framework(s). Upon completion, the tools report results and compare them with previous testing cycles. In an age of analytics, it is no surprise that we have intelligent analytics solutions that present insights that translate test results into actionable information for process improvement.
In this whitepaper, we try to understand the need for test analytics for automated testing, the challenges in automation testing and analytics, and how to choose the right test tools.