As our regression pack is growing large day by day and there always been a case to shorten the QA cycle everytime, we need something which ensures effective testing of the code.

To do this we need to be smart and identify the tests that only affects the system due to selective code changes. Doing this manually can become a nightmare.

Hence a test recommendation system is now a days a need of an hour. With changes in the code it can effectively pinpoint the tests that are affected and could be considered for a targetted regression.

In this workshop you will see / learn how to design this recommendation system which would predict the cases that you should run. You would see how can we come up with a model which can do so.

Outline: 

• What are recommendation systems ?
• What are the usecases where a recommendation system can be effective in a software development lifecycle ?
• Our usecase
• High level Architecure of the system
• Tools required to build the system
• Discuss some common ML Algorithm in a layman language
• Code the system
• Run the system
• Understand how this can be deployed