Intelligent Test Automation for Agile Teams
Traditionally, test automation was implemented with frameworks that require a specialized workforce (SDETs), need a significant amount of maintenance and infrastructure for the executions, notifications, and reporting. Today, the QA Automation Tools industry is ripe for the adoption of newer technologies and had been somewhat late to shift to SaaS, ML, and AI. Here at Fox, we have teams using various tools to augment our testing needs, and it's been very challenging, inefficient, and somewhat unreliable. Looking for a unified solution, we've conducted several POCs and have adopted the SaaS-based tools. The adoption had resulted in tremendous improvements in the quality of the releases across all teams and had allowed us to shift left, where testing is performed earlier in the cycle. The low-code approach allows for in-sprint, rapid test case development, improved reporting, and overall visibility. Takeaways: When we look back, we see how computing had changed over the few decades by widely adopted and well-known services such as AWS, Google Cloud, Microsoft Azure, and others. Today, the new breed of SaaS-based test automation tools is maturing and will follow the same trajectory, adding more capabilities under the belt, allowing for self-healing, AI, ML, and analytics, eventually becoming a de-facto standard, and changing the way we approach test automation, transforming the industry.