DRMacIver/hypothesis

Features

• Test Case Generators - Automatically generates diverse randomized input data and test scenarios to identify bugs and edge cases.
• Test Data Generators - Creates diverse sets of synthetic data based on defined strategies to stress test application logic.
• Edge Case Analysis - Automatically identifies unexpected inputs and boundary conditions that cause software to crash or behave incorrectly.
• Bug Reproduction Scripting - Reduces complex failing test inputs to the smallest possible examples to make bug reproduction faster.
• Constraint-Based Data Generation - Implements rule-based generation of diverse randomized inputs to thoroughly stress test application logic.
• Failing Case Shrinkers - Provides a mechanism to simplify complex failing test inputs into the smallest possible examples.
• Example Shrinking - Simplifies complex failing inputs into the smallest possible examples that still trigger the original failure.
• Generative Testing - Implements property-based testing by generating numerous random test cases to validate code invariants.
• Python Libraries - Provides a comprehensive property-based testing framework specifically designed for the Python ecosystem.
• Automated Test Generators - Automatically generates randomized datasets to stress test code logic and improve software robustness.
• Test Case Shrinking - Includes a shrinking algorithm that reduces complex failing examples to their minimal form to accelerate debugging.
• Deterministic - Provides deterministic seeding to ensure failing random input sequences can be exactly reproduced for debugging.
• State Transition Testing - Simulates random sequences of actions to verify that state transitions in a system remain valid.
• Input Space Partitioning - Systematically divides the range of possible input values into subsets to discover boundary conditions.
• Testing Frameworks - Property-based testing library.

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