As The World Turns
Speaker: Adonis Celestine
Time: 10:00, Thursday
While in the last few years IT world has rushed to adopt Agile and DevOps, Software Testing has been merely playing a catch-up game. What were once the best practices of software testing like Risk based testing, Root cause analysis, etc. are now struggling to be relevant in modern development teams. Many organizations, in the zest of embracing speed at the cost of quality, have restricted the originally intuitive role of testers to be merely automation zombies!
With intelligent bots, we can bring back the essence of what made us testers so special – Gaining cognitive insights on the quality gaps, risks, causes and how to prevent it. Advancements in Natural Language Processing (NLP), Machine Learning & Data Science have made this dream a reality in a fast-paced development environment like our team.
In this presentation, we will discuss my recent assignment where we used open source big data engine and Machine Learning algorithms to process historical data that are readily available in IT development process like defect logs, incident logs, user stories, application logs etc. By analysing the data, we could predict what defect could occur whenever new code is committed, prioritise the high-risk test cases and categorise the defect on root causes. This brought in the necessary quality to our team and also enabled our quality process to make a real shift to the left.
I would like to share how we “Learned from yesterday, lived our life today and our hope for tomorrow”