1480. Running Sum of 1d Array
easyGiven an array nums, return the running sum where runningSum[i] = sum of nums[0..i]. A foundational prefix-sum warm-up that unlocks a whole family of range-query problems.
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Problem
Given an array nums. We define a running sum of an array as runningSum[i] = sum(nums[0]..nums[i]). Return the running sum of nums.
Constraints
1 <= nums.length <= 1000-10^6 <= nums[i] <= 10^6
Examples
Example 1
nums = [1,2,3,4][1,3,6,10]Explanation: Running sum is obtained as follows: [1, 1+2, 1+2+3, 1+2+3+4].
Example 2
nums = [1,1,1,1,1][1,2,3,4,5]Example 3
nums = [3,1,2,10,1][3,4,6,16,17]Solve it now
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Hints
Progressive — try the first before opening the next.
Hint 1
The naive approach recomputes a sum for every index. Can you reuse the work from the previous index?
Hint 2
Notice runningSum[i] = runningSum[i-1] + nums[i]. That is the entire algorithm.
Hint 3
You can do this in place by mutating nums itself to save the extra array allocation.
Solution approach
Reveal approach
Walk the array left to right while keeping a single accumulator. At index i, set nums[i] += nums[i-1] (or write to a fresh result array if mutation is forbidden). The trick is recognising that each running sum is one addition away from the previous one, which collapses what looks like an O(n^2) double-loop into a single linear pass. This same prefix-sum primitive powers range-sum queries, equilibrium-index problems, and 2D summed-area tables.
Complexity
- Time
- O(n)
- Space
- O(1)
Related patterns
- prefix-sum
Related problems
Asked at
Companies reported asking this problem (sourced from public Glassdoor, Blind, and Levels.fyi interview posts).
- Amazon
- Microsoft
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