Explore dynamic unit testing and fuzzing techniques for robust software development in this EuroPython Conference talk. Learn how to overcome limitations of static unit tests by implementing randomized data generation using the Hypothesis library in Python. Discover strategies for specifying data generation templates, testing function invariants, and improving test suite coverage. Gain insights into applying fuzzing techniques to machine learning algorithms, as demonstrated by Blue Yonder. Delve into topics such as predictive analytics, big data, precision, and case coverage while examining practical examples and best practices for implementing dynamic tests in Python projects.
What's the Fuzz All About - Randomized Data Generation for Robust Unit Testing
EuroPython Conference via YouTube
Overview
Syllabus
Intro
Predictive analytics
Big data
Dynamic testing
Precision and case coverage
Dynamic tests
Dynamic tests in Python
First example
Summary
Toy example
URL lip example
Dynamic test
Conclusion
Questions
Taught by
EuroPython Conference