## Round 1 - Coding ## Problem You are given a list of events. Each event is either `"START"` or `"END"`. A trip begins on a `START` event and ends on the next `END` event. Implement a `TripCounter` class that processes events one at a time and returns the number of completed trips at any point. ```python class TripCounter: def __init__(self): pass def process(self, event: str) -> int: # Returns total completed trips after processing this event pass def active_trips(self) -> int: # Returns number of currently open (unfinished) trips pass ``` ## Example ``` events = ["START", "START", "END", "END", "START", "END"] After "START" -> completed=0, active=1 After "START" -> completed=0, active=2 After "END" -> completed=1, active=1 After "END" -> completed=2, active=0 After "START" -> completed=2, active=1 After "END" -> completed=3, active=0 ``` ## Follow-ups 1. What if events include a trip ID and you need to match START/END by ID? How does your data structure change? 2. How would you handle an `END` event with no matching `START`? Should it throw, return -1, or be silently ignored? 3. If trips have timestamps, how do you compute average trip duration? 4. At scale (millions of events/sec), how would you process this in a distributed stream?

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Trip Counter - Tracking Active Journeys with Start/End Events

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Round 1 - Coding Problem You are given a list of events. Each event is either "START" or "END". A trip begins on a START event and ends on the next END event. Implement a TripCounter class that processes events one at a time and returns the number of completed trips at any point. Example Follow-ups What if events include a trip ID and you need to match START/END by ID? How does your data structure change? How would you handle an END event with no matching START? Should it throw, return -1, or be…

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This question was reported by a candidate who interviewed at Axon. LeakCode aggregates interview reports from 10+ sources, including 1Point3Acres, Glassdoor, LeetCode Discuss, Blind, Reddit, Indeed, and Nowcoder. Each report is translated where necessary, deduplicated against existing entries, and tagged by company, role, round type, and reporting date.

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How To Practice This Type of Question

Solve similar problems on LeetCode under timed conditions (25-35 minutes per medium difficulty). The goal is pattern recognition: recognize the underlying technique (sliding window, two-pointer, BFS, memoized recursion, etc.) within 60-90 seconds of reading. Strong candidates verbalize their hypothesis out loud before coding, then iterate based on feedback. Weak candidates dive into implementation immediately, lose time on the wrong approach, and run out of time for follow-ups.

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Apply the standard interview round template: clarify requirements (2-3 minutes), state your approach out loud and confirm direction with the interviewer (3-5 minutes), code with narration (15-25 minutes), test with concrete examples including edge cases (5 minutes), discuss optimization or trade-offs if time permits (5 minutes). This template is universally accepted across FAANG and adjacent companies; deviating from it produces weaker interviewer feedback signal.

The single most predictive failure mode in Axon reports tagged "no hire": not asking clarifying questions. Interviewers are explicitly trained to weight this. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into code immediately. The clarifying-question check is often the first signal recorded in the interviewer's written notes.