How One Engineer Debugged a Floating Point Bug That Cost a Drone Company $2 Million

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How One Engineer Debugged a Floating Point Bug That Cost a Drone Company $2 Million

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In this episode of The Software Engineering Podcast with Fexingo, Lucas and Luna dive into a real-world debugging nightmare: a floating-point precision bug in a drone navigation system that caused erratic flight patterns and led to $2 million in lost contracts. They break down the core issue — why 0.1 + 0.2 does not equal 0.3 in IEEE 754 binary floating-point representation — and walk through the specific scenario where accumulated rounding errors in a Kalman filter threw off position estimates by over a meter. The conversation covers how the engineer traced the bug using delta debugging, why a switch to fixed-point arithmetic fixed it, and what lessons every developer should take away about numerical computing in safety-critical systems. If you've ever wondered why your calculations seem off or why NASA lost a Mars orbiter, this episode will give you a concrete, actionable understanding of floating-point gotchas. No abstract theory — just the actual numbers and code-level decisions that made the difference between a working drone and a $2 million mistake. #FloatingPoint #DroneEngineering #Debugging #NumericalPrecision #IEEE754 #KalmanFilter #FixedPointArithmetic #SafetyCriticalSystems #DeltaDebugging #SoftwareEngineering #Technology #Programming #EmbeddedSystems #RealWorldBug #FexingoBusiness #BusinessPodcast #CodeQuality #TechPodcast Keep every episode free: buymeacoffee.com/fexingo

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