Robinhood Interview Questions

Background: Robinhood deals with transactions and payments where users may need to convert currencies or make payments using the smallest number of coins possible. This problem is central to creating efficient financial applications that handle payments.Problem statement: Given an integer amount representing the total amount of money and an integer array coins representing the denominations of coins, write a function to determine the minimum number of coins that you need to make up that amount. If that amount cannot be made up by any combination of the coins, return -1.Function/class signature:

• def min_coins(coins: List[int], amount: int) -> int:

Example 1:

• Input: coins = [1, 2, 5], amount = 11


• Output: 3


• Explanation: The optimal combination is 5 + 5 + 1.

Example 2:

• Input: coins = [2], amount = 3


• Output: -1


• Explanation: It is not possible to make the amount 3 with denomination 2.

Constraints:

• 1 <= coins.length <= 12


• 1 <= coins[i] <= 2^31 - 1


• 0 <= amount <= 10^4

Background: Robinhood needs to implement a feature that helps users find the minimum number of coins needed to make a specific amount in currency transactions. This relates to the financial transactions that occur on their platform, ensuring efficient solutions for such operations.Problem statement: Given an integer array coins representing different denominations of coins and an integer amount representing a total amount of money, calculate the minimum number of coins that you need to make up that amount. If that amount cannot be made up by any combination of the coins, return -1.Function/class signature:

• def min_coins(coins: List[int], amount: int) -> int:

Example 1:

• Input: coins = [1, 2, 5], amount = 11


• Output: 3


• Explanation: 11 = 5 + 5 + 1, hence 3 coins are needed.

Example 2:

• Input: coins = [2], amount = 3


• Output: -1


• Explanation: It's not possible to form amount 3 with just coin 2.

Constraints:

• 1 <= coins.length <= 12


• 1 <= coins[i] <= 2^31 - 1


• 0 <= amount <= 10^4

1. Background: At Robinhood, users often need to make transactions with various coin denominations. An efficient way to determine the least number of coins to make a specific amount can enhance user experience and operational efficiency.
2. Problem statement: Given an array of coin denominations and a target amount, design a function to find the minimum number of coins needed to make that amount. If it's not possible to make that amount, return -1. The function should optimize for the number of coins used.
3. Function/class signature:
- def min_coins(coins: List[int], amount: int) -> int:
4. Example 1:
- Input: coins = [1, 2, 5], amount = 11
- Output: 3
- Explanation: 11 can be made with 1 coin of 5 and 3 coins of 2 (5 + 2 + 2 + 2 = 11).
5. Example 2:
- Input: coins = [2], amount = 3
- Output: -1
- Explanation: It's impossible to make up the amount 3 with coins of denomination 2.
6. Constraints:
- 1 <= len(coins) <= 100
- 1 <= coins[i] <= 1000
- 0 <= amount <= 10^4

Background: Robinhood provides a platform for trading and investing; thus, it needs efficient algorithms for currency conversion and transaction handling, where determining the minimum number of coins could optimize trading algorithms.
Problem statement: Given an integer amount and an array of integers coins, each representing the value of coins available, write a function to determine the minimum number of coins that make up the given amount. If it is not possible to make up the amount using the given coins, return -1.
Function/class signature:

• def min_coins(coins: List[int], amount: int) -> int:

Example 1:
Input: coins = [1, 2, 5], amount = 11
Output: 3
Explanation: 11 = 5 + 5 + 1, minimum coins needed are 3.
Example 2:
Input: coins = [2], amount = 3
Output: -1
Explanation: It is not possible to make amount 3 with coin 2.
Constraints:

• 1 <= coins.length <= 12


• 1 <= coins[i] <= 2 * 10^4


• 0 <= amount <= 10^7

Background: Robinhood often deals with transactions that involve different currencies and fee structures. A feature that helps users quickly compute the most efficient way to combine different coin denominations to meet a desired amount can enhance user experience.Problem statement: Given a set of coin denominations and a target amount, calculate the minimum number of coins required to make that amount. If it's not possible to make that amount using the provided coins, return -1.Function/class signature:

• def min_coins(coins: List[int], amount: int) -> int:

Example 1:

• Input: coins = [1, 2, 5], amount = 11


• Output: 3


• Explanation: We can use two coins of 5 and one coin of 1 to make 11.

Example 2:

• Input: coins = [2], amount = 3


• Output: -1


• Explanation: We cannot make 3 with coin of 2 only.

Constraints:

• 1 <= len(coins) <= 100


• 1 <= coins[i] <= 1000


• 0 <= amount <= 10000

Background: Robinhood requires efficient task management to handle multiple user requests and processes simultaneously. Developing a job scheduling system will streamline this and improve user experience.
Problem statement: Create a class JobScheduler that can schedule tasks for execution at specific times. The class should support adding jobs and retrieving the next job to execute based on scheduled times. The class should also allow for cancellation of scheduled jobs.
Function/class signature:

• def add_job(job_id: int, run_time: int) -> None: # Add a job with a specified run time


• def get_next_job() -> Union[int, None]: # Get the next job to execute


• def cancel_job(job_id: int) -> None: # Cancel a job by its ID

Example 1: Input: add_job(1, 5) then get_next_job() → Output: 1, Explanation: Job 1 is scheduled to run at time 5.
Example 2: Input: add_job(2, 3), add_job(3, 4), then get_next_job() → Output: 2, Explanation: Job 2 is scheduled to run at time 3 and is the next to execute.
Constraints:

• Job IDs are unique integers.


• Run times are positive integers not exceeding 10000.


• There can be at most 1000 jobs scheduled at a time.