Packet Latency Tracker

What this sliding-window data-structure problem tests

This is an easy Python coding problem that appears in networking and systems interviews at quant firms. It asks you to implement a real-time monitoring class that maintains summary statistics (average, min, max) over a fixed-size window of the most recent observations.

The core challenge is choosing the right data structure and maintaining efficiency as the window slides: new packets arrive and old ones drop out. You need to handle the window boundary correctly, ensure all three statistics stay accurate, and avoid unnecessary recomputation. Interviewers care about clean, correct logic and whether you handle edge cases like an empty window.

• Circular/sliding-window data structures (deque, circular buffer)
• Tracking aggregate statistics incrementally
• Time and space trade-offs for min/max queries
• Boundary conditions and off-by-one errors