Confluent Online Assessment Questions

Confluent Software Engineer Coding Round Experience

During the post-qualifier coding round for an SSE2 position at Confluent, I was tasked with solving a search-related problem. I successfully implemented the code for the first half of the requirements

Confluent | Senior Software Engineer | Offer

My experience regarding recent SSE interview rounds with Confluent - I took a referral. After 20 days, recruiter called me and asked to schedule a Qualifer round. Qualifier Round: I was asked a DSA+LLD...

#37 Sudoku Solver

LeetCode #37: Sudoku Solver. Difficulty: Hard. Topics: Array, Hash Table, Backtracking, Matrix. Asked at Confluent in the last 6 months.

#36 Valid Sudoku

LeetCode #36: Valid Sudoku. Difficulty: Medium. Topics: Array, Hash Table, Matrix. Asked at Confluent in the last 6 months.

#1797 Design Authentication Manager

LeetCode #1797: Design Authentication Manager. Difficulty: Medium. Topics: Hash Table, Linked List, Design, Doubly-Linked List. Asked at Confluent in the last 6 months.

Buying Chairs: Minimum Cost to Seat All Guests Given Chair Capacities

## Problem You are furnishing a venue. There are `n` types of chairs available; chair type `i` holds `capacity[i]` people and costs `price[i]` dollars. You need to seat exactly `guests` people. You can buy multiple chairs of the same type. You must seat every guest (no guest left standing). Return the minimum total cost to buy a set of chairs that seats at least `guests` people. ```python def min_cost_to_seat(capacity: list[int], price: list[int], guests: int) -> int: ... ``` ``` Input: capacity = [4, 6, 2], price = [10, 15, 5], guests = 10 Output: 25 Explanation: Buy 1 chair of type 1 (4 seats, $10) + 1 chair of type 2 (6 seats, $15) = 10 seats, $25. Alternatively: 5 x type 3 (10 seats, $25) = same cost. Input: capacity = [3], price = [7], guests = 10 Output: 28 Explanation: Need 4 chairs (ceil(10/3)=4), 4*7=28. ``` ## Follow-ups 1. What if you can only buy each chair type once (0/1 knapsack variant)? 2. How does your solution change if you want to minimize chairs purchased (not cost), breaking ties by cost? 3. What if `guests` can be up to 10^9 — how do you handle the scale? 4. Suppose some chairs require a delivery fee that applies once per type purchased. How do you model that?

Minimum Health Required for Gaming: Survive a Sequence of Attacks with Minimum Starting HP

## Problem You are playing a game. You face `n` rounds in order. In each round, you either lose `damage[i]` HP or gain `heal[i]` HP (represented as negative damage). You die if your HP reaches 0 or below at any point. What is the minimum integer starting HP so you survive all rounds? ```python def min_starting_health(rounds: list[int]) -> int: """ rounds[i] > 0: take that much damage rounds[i] < 0: heal that much HP Return minimum starting HP (>= 1) to survive all rounds. """ ... ``` ``` Input: rounds = [2, 7, -4, 3] Output: 8 Explanation: Start = 8 -> after 2 dmg: 6 -> after 7 dmg: -1 (dead) Start = 9 -> 9->7->0 (dead) Start = 10-> 10->8->1->5->2 (alive). Minimum is 10. Input: rounds = [-5, 3, 1] Output: 5 ``` ## Follow-ups 1. What if you can choose the order of rounds — what ordering minimizes starting HP? 2. How would you solve this if HP also has a maximum cap (e.g., cannot exceed 100)? 3. Binary search is one approach. What is the invariant you'd binary search on, and what are the bounds? 4. Extend to 2D: you navigate a grid of cells, each with a damage/heal value. Find min starting HP to reach bottom-right from top-left.