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Solve transaction aggregation and search tasks

Last updated: Mar 29, 2026

Quick Overview

This question evaluates array aggregation, prefix-sum and binary search techniques, divide-and-conquer recursion, segment-tree trade-offs, and algorithmic complexity analysis for scalable transaction and range-sum processing.

  • Medium
  • Current
  • Coding & Algorithms
  • Software Engineer

Solve transaction aggregation and search tasks

Company: Current

Role: Software Engineer

Category: Coding & Algorithms

Difficulty: Medium

Interview Round: Technical Screen

Complete the following coding tasks: (a) Given a list of transactions, each with userId and amount (credits positive, debits negative), compute the final balance for each userId. Return a map from userId to balance. Handle large inputs efficiently and specify time/space complexity. (b) Given an array of positive integers nums and a list of targets, for each target find the minimal prefix length k such that sum(nums[0..k-1]) >= target; return -1 if no such k exists. Implement using a prefix-sum array and binary search, and analyze complexity. (c) For an immutable integer array and a small number of range-sum queries [L, R] with no updates, write a simple recursive divide-and-conquer function to compute the sum for a given query. Then explain when you would instead build a segment tree (e.g., many queries and/or updates) and compare the trade-offs.

Quick Answer: This question evaluates array aggregation, prefix-sum and binary search techniques, divide-and-conquer recursion, segment-tree trade-offs, and algorithmic complexity analysis for scalable transaction and range-sum processing.

Related Interview Questions

  • Compute balances and array queries - Current (Medium)
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Current
Jul 31, 2025, 12:00 AM
Software Engineer
Technical Screen
Coding & Algorithms
4
0

Complete the following coding tasks: (a) Given a list of transactions, each with userId and amount (credits positive, debits negative), compute the final balance for each userId. Return a map from userId to balance. Handle large inputs efficiently and specify time/space complexity. (b) Given an array of positive integers nums and a list of targets, for each target find the minimal prefix length k such that sum(nums[0..k-1]) >= target; return -1 if no such k exists. Implement using a prefix-sum array and binary search, and analyze complexity. (c) For an immutable integer array and a small number of range-sum queries [L, R] with no updates, write a simple recursive divide-and-conquer function to compute the sum for a given query. Then explain when you would instead build a segment tree (e.g., many queries and/or updates) and compare the trade-offs.

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