The interview lasted around 60 minutes in total.

It started with a 5-minute introduction and background discussion, followed by approximately 20 minutes of debugging exercises where I was asked to identify and fix issues in the code.

The remaining 35-40 minutes focused on a long, scenario-based coding problem that required implementing a solution while discussing the approach and trade-offs.

The session was highly interactive, with continuous questions, hints, and discussions throughout the coding process.

• This event disconnects the same users: ["DISCONNECT", "Bob", "Alice"] (order of users does not matter)

We want to separate users based on their popularity (number of connections). To do this, write a function that takes in the event log and a number N and returns two collections:

• [Users with fewer than N connections]
• [Users with N or more connections]

Example: events = [ ["CONNECT","Alice","Bob"], ["DISCONNECT","Bob","Alice"], ["CONNECT","Alice","Charlie"], ["CONNECT","Dennis","Bob"], ["CONNECT","Pam","Dennis"], ["DISCONNECT","Pam","Dennis"], ["CONNECT","Pam","Dennis"], ["CONNECT","Edward","Bob"], ["CONNECT","Dennis","Charlie"], ["CONNECT","Alice","Nicole"], ["CONNECT","Pam","Edward"], ["DISCONNECT","Dennis","Charlie"], ["CONNECT","Dennis","Edward"], ["CONNECT","Charlie","Bob"] ]

Using a target of 3 connections, the expected results are:

• Users with less than 3 connections: ["Alice", "Charlie", "Pam", "Nicole"]
• Users with 3 or more connections: ["Dennis", "Bob", "Edward"]

All test cases:

• grouping(events, 3) => [["Alice", "Charlie", "Pam", "Nicole"], ["Dennis", "Bob", "Edward"]]
• grouping(events, 1) => [[], ["Alice", "Charlie", "Dennis", "Bob", "Pam", "Edward", "Nicole"]]
• grouping(events, 10) => [["Alice", "Charlie", "Dennis", "Bob", "Pam", "Edward", "Nicole"], []]

Complexity Variable: E = number of events