Pursuit of Artificial Intelligence in Test Automation (ONLINEGUWAHATI – 3.0 Mobile & DT Automation Framework)

At OnlineGuwahati.com, we have always been on the eye out to pick the best happenings in the industry and leverage it to make our tools and frameworks more efficient, smart and tech up to date. As we continued to explore Data Analytics and Artificial Intelligence, we made it our pursuit to change the way our test automation framework really works. Hence we decided to collect our test run outcomes like logs, results, screenshots, pathways, exceptions etc. To analyze it and help our algorithms take smart decisions and drive it with lesser manual intervention !!

Key Features of In-The-Dockyard framework OnlineGuwahati – 3.0 Mobile and DT Automation Framework
1. Test predicto-R
2. Suite optimize-R
3. Coverage analyse-R
4. Regression prioritize-R
Also, we are building the next generation risk-based test prioritizing intelligence which would continuously sample out defect density area wise, understand and analyze the type of failures, capture and understand user usage behavior to build a prioritizing matrix which would be the guiding scale for prioritizing the test in turn.
This helps reduce the delay, overall time and cost of the test automation effort with a much better risk management.
This would also definitely help us eliminate duplicate and redundant tests. Lessing the overall count of test cases to achieve the optimal QUALITY vs QUANTITY formula.

Written by
Gautam Goswami

Can be reached for real-time POC development and hands-on technical training at gautambangalore@gmail.com. Besides, to design, develop just as help in any Hadoop/Big Data handling related task. Gautam is a advisor and furthermore an Educator as well. Before that, he filled in as Sr. Technical Architect in different technologies and business space across numerous nations.
He is energetic about sharing information through blogs, preparing workshops on different Big Data related innovations, systems and related technologies.