Prefix Sum Array in DSA Go - Time & Space Complexity

Time Complexity: Prefix Sum Array

O(n)

Understanding Time Complexity

We want to understand how fast we can build and use a prefix sum array.

How does the time needed grow as the input array gets bigger?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

package main

func prefixSum(arr []int) []int {
    n := len(arr)
    prefix := make([]int, n)
    prefix[0] = arr[0]
    for i := 1; i < n; i++ {
        prefix[i] = prefix[i-1] + arr[i]
    }
    return prefix
}

This code creates a prefix sum array where each element is the sum of all elements before it in the input array.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: A single for-loop that adds elements one by one.
• How many times: The loop runs once for each element after the first, so n-1 times.

How Execution Grows With Input

As the input array grows, the number of additions grows roughly the same way.

Input Size (n)	Approx. Operations
10	9 additions
100	99 additions
1000	999 additions

Pattern observation: The operations increase directly with input size, so doubling input roughly doubles work.

Final Time Complexity

Time Complexity: O(n)

This means the time to build the prefix sum grows in a straight line with the size of the input array.

Common Mistake

[X] Wrong: "Building a prefix sum array takes more time than just reading the array once because it does extra additions."

[OK] Correct: The prefix sum only adds one extra operation per element, so it still grows linearly and is very efficient.

Interview Connect

Knowing how prefix sums work and their time cost helps you solve many problems quickly, showing you understand efficient data processing.

Self-Check

"What if we wanted to build a 2D prefix sum array for a matrix? How would the time complexity change?"

Practice

1. What is the main purpose of a prefix sum array in algorithms?

easy

A. To find the maximum element in the array

B. To sort the array elements in ascending order

C. To reverse the array elements efficiently

D. To quickly find the sum of elements in any subarray

Solution

1. Step 1: Understand prefix sum array concept

   A prefix sum array stores cumulative sums of elements from the start to each position.

2. Step 2: Use prefix sums for subarray sums

   Using prefix sums, sum of any subarray can be found quickly by subtracting two prefix sums.

3. Final Answer:

   To quickly find the sum of elements in any subarray -> Option D

4. Quick Check:

   Prefix sum array helps fast subarray sums [OK]

Hint: Prefix sums store cumulative sums for fast subarray queries [OK]

Common Mistakes:

• Confusing prefix sum with sorting
• Thinking prefix sum reverses array
• Assuming prefix sum finds max element

2. Which of the following Go code snippets correctly initializes a prefix sum array prefix from an integer slice arr?

easy

A. prefix := make([]int, len(arr))
for i := 0; i < len(arr); i++ {
prefix[i] = prefix[i-1] + arr[i]
}

B. prefix := make([]int, len(arr)+1)
for i := 1; i <= len(arr); i++ {
prefix[i] = prefix[i-1] + arr[i-1]
}

C. prefix := make([]int, len(arr)+1)
for i := 0; i < len(arr); i++ {
prefix[i] = prefix[i-1] + arr[i]
}

D. prefix := make([]int, len(arr))
for i := 1; i < len(arr); i++ {
prefix[i] = prefix[i-1] + arr[i]
}

Solution

1. 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.

2. Step 2: Verify loop and indexing logic

   Loop from 1 to len(arr), prefix[i] = prefix[i-1] + arr[i-1] correctly accumulates sums.

3. Final Answer:

   prefix := make([]int, len(arr)+1) for i := 1; i <= len(arr); i++ { prefix[i] = prefix[i-1] + arr[i-1] } -> Option B

4. Quick Check:

   Correct prefix sum initialization uses offset indexing [OK]

Hint: Prefix array length = original length + 1, loop starts at 1 [OK]

Common Mistakes:

• Using prefix array same length as original
• Starting loop at 0 and accessing prefix[-1]
• Incorrect indexing of arr inside loop

3. What is the output of the following Go code?

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)

medium

A. [0 2 6 12 20]

B. [2 6 12 20 28]

C. [0 2 4 6 8]

D. [2 4 6 8 0]

Solution

1. 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=20

2. Step 2: Write final prefix array

   The prefix array is [0, 2, 6, 12, 20]

3. Final Answer:

   [0 2 6 12 20] -> Option A

4. Quick Check:

   Sum accumulates correctly in prefix array [OK]

Hint: Start prefix with 0, add elements cumulatively [OK]

Common Mistakes:

• Forgetting initial zero in prefix array
• Adding wrong elements at each step
• Confusing prefix array length

4. Identify the error in this Go code that tries to build a prefix sum array:

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)

medium

A. prefix array size should be len(arr)+1

B. Loop should start from i=0 instead of i=1

C. prefix[0] is not initialized before use

D. arr indexing is out of range

Solution

1. Step 1: Check prefix array initialization

   Prefix array is size len(arr), which can work but prefix[0] must be set before use.

2. 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.

3. Step 3: Check correctness of prefix sums

   prefix[0] is zero, but arr[0] is never added, so prefix sums are incomplete.

4. Final Answer:

   prefix[0] is not initialized before use -> Option C

5. Quick Check:

   Missing prefix[0] initialization causes wrong sums [OK]

Hint: Initialize prefix[0] before loop to avoid wrong sums [OK]

Common Mistakes:

• Not initializing prefix[0]
• Wrong prefix array size
• Incorrect loop start index

5. Given an integer slice arr, how can you use a prefix sum array to find the sum of elements between indices l and r (inclusive) efficiently?

hard

A. sum = prefix[r+1] - prefix[l]

B. sum = prefix[r] - prefix[l-1]

C. sum = prefix[r] + prefix[l]

D. sum = prefix[r+1] + prefix[l-1]

Solution

1. 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].

2. 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].

3. Final Answer:

   sum = prefix[r+1] - prefix[l] -> Option A

4. Quick Check:

   Subarray sum = prefix[r+1] - prefix[l] [OK]

Hint: Use prefix[r+1] - prefix[l] for sum between l and r [OK]

Common Mistakes:

• Using prefix[r] - prefix[l-1] without offset
• Adding prefix sums instead of subtracting
• Confusing indices by 1