11 years in IT.
Java development background. Delivery Manager.
4 years of experience with test automation at scale.
Leading development of solutions and initiatives at Test Competency Center.
Mainly focused: Machine Learning and AI in Test Automation.
Report Portal Product Owner.
Topic: Neural networks and machine learning for the classification of automated test failures
The report will tell you about our experience of using machine learning to classify the automated test failures based on error logs and stack trace.
A little about what we use, how we use it, how we trained and optimized it. And what conclusions we have come to.
And neural networks as a next step in order to improve the processing and optimize the contents of logs. What we have done for this, and what conclusions we have come to.
On the various word forms of logs, their contents, and useless tails. And how their preprocessing shall improve the results of machine learning.