Mohini Agarwal
Senior Software Test Engineer
About
Mohini Agarwal is a QA and Quality Engineering professional with over 12 years of experience in automation testing, CI/CD pipelines, and API-driven systems. She is passionate about building reliable testing strategies and exploring how AI can enhance modern software quality practices.
Rachana Menon
Senior Software Test Engineer
About
Rachana Menon is a Test Engineer passionate about building reliable and scalable automation systems. She has hands-on experience building scalable test frameworks, integrating schema validation, and running automated test pipelines. Her journey in testing has been driven by solving real-world challenges—especially around flaky tests, catching breaking changes early in distributed systems.She is particularly interested in practical applications of AI in testing and modern automation strategies. As a first-time conference speaker, Rachana brings a fresh, real-world perspective from the field, sharing lessons learned from implementing automation in fast-paced engineering environments.
From API Contracts to UI Confidence: AI-Driven Quality in CI/CD
Description
In modern distributed architectures, the most disruptive defects are often the ones that live in the gaps between services. Contract violations—schema drift, breaking API changes, and consumer-provider mismatches—frequently bypass traditional test suites, only to cause catastrophic failures in the UI or downstream services after deployment.
This session provides a technical blueprint for bridging the gap between API reliability and UI confidence. We will walk through a practical implementation of containerized CI/CD pipelines that utilize oasdiff and Docker to detect breaking changes before they hit production.
Key technical takeaways include:
Automating the "Contract-to-UI" Link: How to ensure UI automation remains stable by catching underlying API shifts early.
AI-Driven Testing with Schemathesis: Using AI to derive edge cases and boundary tests directly from OpenAPI specs to increase coverage without manual script bloating.
Intelligent Triage: Implementing AI-assisted failure analysis to interpret pipeline logs and provide plain-language explanations for complex integration failures.
Securing the Pipeline: A critical look at security-conscious AI adoption, focusing on data residency and sandboxed execution using enterprise-bounded platforms like Azure OpenAI or AWS Bedrock.