Deepika Kaushik
About Speaker
Deepika Kaushik
Associate Principle Engineer
Nagarro
With over 12 years of experience in software testing, I have worked extensively with Selenium, Appium, Playwright, API Testing, and Performance Testing, continuously adapting to new advancements. Passionate about automation and innovation, I am now shifting my focus towards AI-driven testing to enhance efficiency and accuracy in QA.
Currently at Nagarro, I have played a key role in designing automation frameworks, optimizing test strategies, and mentoring teams. My expertise spans web, mobile, API, and performance automation, ensuring robust and scalable solutions. My focus is on driving innovation in QA by leveraging cutting-edge tools and methodologies.
On a mission to revolutionize software testing with AI, automation, and performance-driven insights!
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Topic – AI‑Driven Test Retry Optimizer: Explainable, Data‑Driven Retries for Faster, More Reliable CI Pipelines
Flaky tests and transient infrastructure issues force QA teams to spend significant time on manual re-runs, hide real regressions, and delay releases. Traditional pass/fail heuristics do not differentiate between genuinely broken tests and transient failures, increasing noise in CI pipelines and weakening developer confidence.
This session presents a practical, production-ready AI-driven Test Retry Optimizer that uses historical execution behavior to make explainable, risk-aware retry decisions. The solution is lightweight, uses SQLite for data storage, and integrates seamlessly with existing pytest-based automation frameworks.