How Property-Based Testing Finds Bugs Example-Based Tests Miss
from Software Testing with Fexingo: QA, Automation, and Reliable Software Engineering Hosted by Fexingo
In this episode of Software Testing with Fexingo, Lucas and Luna dive into property-based testing — a technique that generates hundreds of random inputs to find edge cases you never considered. They contrast it with traditional example-based testing using a real-world case: a simple e-commerce discount function that seemed correct but failed on a rare combination of price and quantity. Lucas explains how tools like Hypothesis for Python and QuickCheck for Haskell work, why property-based testing catches off-by-one errors and boundary bugs that example tests miss, and how teams can start small by replacing just one test per sprint. Luna shares a story from a fintech team that found a currency-rounding bug after running property tests on transaction fees — a bug that had been in production for six months. They also discuss the learning curve: writing good properties requires thinking about invariants rather than specific inputs. By the end, you'll understand why adding property-based tests to your suite can double your confidence without doubling your test count. #PropertyBasedTesting #SoftwareTesting #QA #Automation #HypothesisPython #QuickCheck #Haskell #TestGeneration #EdgeCases #Invariants #Ecommerce #Fintech #CurrencyRounding #BoundaryTesting #Fuzzing #Technology #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo
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