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Explore advanced testing techniques in this conference talk from EuroPython 2015. Dive into two powerful approaches for generating random input that targets failing test cases: property-based testing with Hypothesis and fuzzing with American Fuzzy Lop (AFL). Learn how Hypothesis, inspired by Haskell's QuickCheck, allows you to specify properties your code must maintain and automatically searches for counterexamples. Discover how AFL uses instrumentation and genetic algorithms to explore code paths, uncovering crashes and hangs other methods miss. See practical demonstrations of applying these techniques to Python code using Python-AFL, and gain insights into improving your testing strategy for more robust software.
