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  5. Having Fun with Testing - Simplify and  Gamify AQA Tests using Machine Learning and Twitter

Having Fun with Testing - Simplify and  Gamify AQA Tests using Machine Learning and Twitter

Session details
Status: 
Accepted
Speaker(s): 
Shelley Lambert (Red Hat, Inc.)
Lan Xia (IBM)
Longyu Zhang (IBM)
Sophia Guo (Red Hat, Inc.)
Sayani Mallick (Student)
Asjad Khan
Avishree Khare (Student)
Experience level: 
Beginner
Session Track: 
Other Cool Stuff
Session Type: 
Standard

As much as we have embraced test automation, there are still too many manual processes required in daily test activities, such as analyzing test failures to match with known issues and maintaining third-party application test code. At the Eclipse AQAvit and Eclipse OpenJ9 projects, we target some of these manual processes as opportunities to apply various technologies and collaborate with Outreachy interns to see if we could improve our daily workflow.

 

This presentation covers our approaches to using machine learning to match test failures with possible related issues (our Deep AQAtik project) and the simplification and gamification of AQA external tests using the Twitter API (our Tweetest project).  For Deep AQAtik, we introduce our initial prototype development, data collection and pre-processing pipeline, machine learning model selection, model deployment, and user feedback collection for improvement.  For Tweetest, we present the idea of creating a generic external_custom test target and how we used Twitter to interact our testing framework to invoke third-party test material.

 

With the Deep AQAtik and Tweetest projects, we stretched our testing framework in new ways to be more intelligent, playful and simple.  Perhaps an even greater outcome of these projects was what we gained from our collaboration and incorporation of new and diverse viewpoints and skillful contributions of our interns.

 

Objective of the presentation: 
This presentation introduces two fun and creative explorations to improve the test process. The first approach uses machine learning to match test failures with existing open issues, while the second one aims to simplify and gamify AQA external tests with Twitter APIs. This objective of this talk is to share the outcome of these explorations as well as our experience of collaborating with Outreachy internship program on open source projects.
Attendee pre-requisites - If none, enter "N/A": 
N/A
Schedule info
Time: 
26 Oct 2021 - 16:50 to 26 Oct 2021 - 17:20
Room: 
Room 1
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