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SUMMARY:Tech Talk: Identifying Potential Test Reductions Using Pytest and AST Analysis
DESCRIPTION:Speaker: Arun Vishwanathan ((https://www.linkedin.com/in/arun-vishwanathan-16b56917/))\nTitle: Identifying Potential Test Reductions Using Pytest and AST Analysis\nAbstract: Test matrix explosions are a growing challenge in modern software testing\, especially when using parameterized tests in machine learning pipelines. This talk presents a hybrid approach that combines Python's Abstract Syntax Tree (AST) analysis and Python's Test Framework parameterized testing to identify potential redundancies. By strategically trimming the test matrix\, we can achieve quicker testing and faster turnarounds.\nBio: Arun Vishwanathan is a Senior Software Development Test Engineer at Apple and specializes in Software Testing and Automation\, with over a decade of experience in the field. His work focuses on building tools and frameworks that enhance test automation\, boost productivity\, and enable cross-team collaboration. Currently\, he is developing a test frameworks for evaluating Machine Learning models. He holds a Master’s degree in Computer Science from the University of Southern California\, Los Angeles.\nSpeaker(s): Arun Vishwanathan\nVirtual: https://events.vtools.ieee.org/m/490367
URL:https://svec.org/event/tech-talk-identifying-potential-test-reductions-using-pytest-and-ast-analysis/
LOCATION:Virtual: https://events.vtools.ieee.org/m/490367
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