What if you could answer any sum question instantly without adding numbers again and again?
Why Prefix Sum Array in DSA Go?
Imagine you have a long list of daily sales numbers and you want to quickly find the total sales between any two days. Doing this by adding numbers one by one every time can be tiring and slow.
Manually adding numbers for each query means repeating the same additions many times. This wastes time and can cause mistakes, especially if the list is very long or if you have many queries.
A prefix sum array keeps track of running totals so you can find the sum between any two points instantly by subtracting two values. This saves time and reduces errors.
func sumRange(arr []int, start int, end int) int {
total := 0
for i := start; i <= end; i++ {
total += arr[i]
}
return total
}func buildPrefixSum(arr []int) []int {
prefix := make([]int, len(arr)+1)
for i := 1; i <= len(arr); i++ {
prefix[i] = prefix[i-1] + arr[i-1]
}
return prefix
}
func sumRange(prefix []int, start int, end int) int {
return prefix[end+1] - prefix[start]
}It enables lightning-fast queries for sums over any range, making your programs much faster and more efficient.
Online shopping sites use prefix sums to quickly calculate total sales or discounts over different periods without recalculating everything each time.
Manual summing is slow and error-prone for repeated queries.
Prefix sum arrays store running totals to answer sum queries instantly.
This technique speeds up programs and reduces mistakes.
Practice
prefix sum array in algorithms?Solution
Step 1: Understand prefix sum array concept
A prefix sum array stores cumulative sums of elements from the start to each position.Step 2: Use prefix sums for subarray sums
Using prefix sums, sum of any subarray can be found quickly by subtracting two prefix sums.Final Answer:
To quickly find the sum of elements in any subarray -> Option DQuick Check:
Prefix sum array helps fast subarray sums [OK]
- Confusing prefix sum with sorting
- Thinking prefix sum reverses array
- Assuming prefix sum finds max element
prefix from an integer slice arr?Solution
Step 1: Check prefix array size and indexing
Prefix sum array usually has length one more than original to handle zero prefix sum at start.Step 2: Verify loop and indexing logic
Loop from 1 to len(arr), prefix[i] = prefix[i-1] + arr[i-1] correctly accumulates sums.Final Answer:
prefix := make([]int, len(arr)+1) for i := 1; i <= len(arr); i++ { prefix[i] = prefix[i-1] + arr[i-1] } -> Option BQuick Check:
Correct prefix sum initialization uses offset indexing [OK]
- Using prefix array same length as original
- Starting loop at 0 and accessing prefix[-1]
- Incorrect indexing of arr inside loop
arr := []int{2, 4, 6, 8}
prefix := make([]int, len(arr)+1)
for i := 1; i <= len(arr); i++ {
prefix[i] = prefix[i-1] + arr[i-1]
}
fmt.Println(prefix)Solution
Step 1: Calculate prefix sums step-by-step
prefix[0]=0
prefix[1]=0+2=2
prefix[2]=2+4=6
prefix[3]=6+6=12
prefix[4]=12+8=20Step 2: Write final prefix array
The prefix array is [0, 2, 6, 12, 20]Final Answer:
[0 2 6 12 20] -> Option AQuick Check:
Sum accumulates correctly in prefix array [OK]
- Forgetting initial zero in prefix array
- Adding wrong elements at each step
- Confusing prefix array length
arr := []int{1, 3, 5}
prefix := make([]int, len(arr))
for i := 1; i < len(arr); i++ {
prefix[i] = prefix[i-1] + arr[i]
}
fmt.Println(prefix)Solution
Step 1: Check prefix array initialization
Prefix array is size len(arr), which can work but prefix[0] must be set before use.Step 2: Analyze loop and prefix[0]
Loop starts at i=1, prefix[1] = prefix[0] + arr[1]. prefix[0] is zero by default in Go, but it should be explicitly set to arr[0] before the loop.Step 3: Check correctness of prefix sums
prefix[0] is zero, but arr[0] is never added, so prefix sums are incomplete.Final Answer:
prefix[0] is not initialized before use -> Option CQuick Check:
Missing prefix[0] initialization causes wrong sums [OK]
- Not initializing prefix[0]
- Wrong prefix array size
- Incorrect loop start index
arr, how can you use a prefix sum array to find the sum of elements between indices l and r (inclusive) efficiently?Solution
Step 1: Understand prefix sum indexing
Prefix sum array usually has length len(arr)+1 with prefix[0]=0, prefix[i] = sum of arr[0..i-1].Step 2: Calculate subarray sum using prefix sums
Sum from l to r = prefix[r+1] - prefix[l] because prefix[r+1] sums up to arr[r].Final Answer:
sum = prefix[r+1] - prefix[l] -> Option AQuick Check:
Subarray sum = prefix[r+1] - prefix[l] [OK]
- Using prefix[r] - prefix[l-1] without offset
- Adding prefix sums instead of subtracting
- Confusing indices by 1
Ready to prove it?
Pass the test and this pattern moves unknown
