STARWEST 2021 Concurrent Session : Applying AI/ML Techniques to Analyze Historical Data For Testing

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Wednesday, October 6, 2021 - 1:30pm to 2:30pm

Applying AI/ML Techniques to Analyze Historical Data For Testing

With the growing importance of system performance rather than just the working function of it, we see an evergrowing need at bringing the bar low, with the client needing their application to perform extensively within speck of time. Comparing the timing for each page load takes substantial time/effort and sometimes tend to come with human error, which in turn can change the course of action. To overcome this, the presentation will provide different AI/Machine Learning techniques that can be applied to the automation and performance tests which will provide a summarized as well as detailed analysis of present as well as past test results with a single click. This solution provides the details regarding the monitoring stats, performance logs and test results. One click tool is developed which shares the consolidated report for Resource utilization graphs, slow pages, Stored Procedures and other metrics via an custom reports. Key takeaways include learning different AI/Machine Learning techniques that can be applied to analyze the historical as well as current data derived from the Performance + Automation Test Results, Zero Cost Automation + Performance Testing, Performance Monitoring and Analysis.

Deloitte Consulting India Pvt Ltd

Jigesh Shah is a Performance and Automation Test Architect with rich experience in in US Healthcare, Insurance, and eLearning. Jigesh an OCJP, Certified Scrum Master , AWS , Docker and Azure associate has worked on various testing tools like Load Runner, VSTS ,Selenium, JIRA ,SQL Server, DynaTrace, AppDynamics, Appium, Microsoft team system and various test management tools. He is currently assigned to a public sector client and has been responsible for the delivering large scale & hybrid performance and automation testing solutions.