Subarray Sum Equals K Using Hash Map in DSA C++ - Time & Space Complexity

Time Complexity: Subarray Sum Equals K Using Hash Map

O(n)

Understanding Time Complexity

We want to know how fast the algorithm finds subarrays that add up to a target sum.

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

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

int subarraySum(vector<int>& nums, int k) {
    unordered_map<int, int> prefixCount;
    prefixCount[0] = 1;
    int count = 0, sum = 0;
    for (int num : nums) {
        sum += num;
        if (prefixCount.find(sum - k) != prefixCount.end()) {
            count += prefixCount[sum - k];
        }
        prefixCount[sum]++;
    }
    return count;
}
    

This code counts how many continuous parts of the array add up exactly to k using a map to track sums.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: One loop through the array elements.
• How many times: Exactly once for each element in the array.

How Execution Grows With Input

Each new element adds a fixed amount of work: updating sum, checking the map, and updating the map.

Input Size (n)	Approx. Operations
10	About 10 steps
100	About 100 steps
1000	About 1000 steps

Pattern observation: The work grows directly in proportion to the input size.

Final Time Complexity

Time Complexity: O(n)

This means the time needed grows linearly with the number of elements in the array.

Common Mistake

[X] Wrong: "Because we use a map inside the loop, the time is O(n²)."

[OK] Correct: The map operations (find and update) are on average constant time, so they do not multiply the loop time.

Interview Connect

Understanding how to use a map to track sums efficiently is a valuable skill that shows you can optimize beyond simple nested loops.

Self-Check

"What if we replaced the unordered_map with a balanced tree map? How would the time complexity change?"

Practice

1. What is the main purpose of using a hash map in the Subarray Sum Equals K problem?

easy

A. To keep track of the maximum subarray length

B. To sort the array elements before processing

C. To store the original array elements as keys

D. To store cumulative sums and their frequencies for quick lookup

Solution

1. Step 1: Understand the problem goal

   The problem requires finding subarrays whose sums equal a target value k.

2. Step 2: Role of hash map in solution

   The hash map stores cumulative sums and their counts to quickly check if a previous sum exists that forms a subarray summing to k.

3. Final Answer:

   To store cumulative sums and their frequencies for quick lookup -> Option D

4. Quick Check:

   Hash map stores sums = D [OK]

Hint: Hash map tracks sums to find subarrays fast [OK]

Common Mistakes:

• Using hash map to sort elements
• Storing array elements as keys instead of sums
• Trying to track max length instead of counts

2. Which of the following is the correct C++ syntax to declare a hash map for storing int keys and values?

easy

A. std::unordered_map map;

B. std::map<int> map;

C. unordered_map map;

D. std::hash_map map;

Solution

1. Step 1: Identify correct hash map declaration

   In C++, std::unordered_map<Key, Value> is used for hash maps.

2. Step 2: Check syntax correctness

   std::unordered_map map; uses correct template syntax and namespace. Others have syntax errors or wrong types.

3. Final Answer:

   std::unordered_map map; -> Option A

4. Quick Check:

   Correct unordered_map syntax = A [OK]

Hint: Use std::unordered_map for hash maps [OK]

Common Mistakes:

• Missing template brackets <>
• Using std::map instead of unordered_map for hash map
• Wrong order of template parameters

3. What will be the output of the following C++ code snippet?

std::vector<int> nums = {1, 2, 3};
int k = 3;
int count = 0;
std::unordered_map prefixSumCount;
prefixSumCount[0] = 1;
int sum = 0;
for (int num : nums) {
    sum += num;
    if (prefixSumCount.find(sum - k) != prefixSumCount.end()) {
        count += prefixSumCount[sum - k];
    }
    prefixSumCount[sum]++;
}
std::cout << count << std::endl;

medium

A. 2

B. 1

C. 3

D. 0

Solution

1. Step 1: Calculate prefix sums and counts

   Prefix sums: 1, 3, 6. Check if (sum - k) exists in map: - sum=1: 1-3=-2 not found - sum=3: 3-3=0 found, count=1 - sum=6: 6-3=3 found, count=1+1=2

2. Step 2: Final count of subarrays with sum k

   Count is 2 because subarrays [1,2] and [3] sum to 3.

3. Final Answer:

   2 -> Option A

4. Quick Check:

   Subarrays summing to 3 = 2 [OK]

Hint: Track prefix sums and check sum-k in map [OK]

Common Mistakes:

• Not initializing prefixSumCount[0] = 1
• Incorrectly updating count
• Confusing sum and sum-k keys

4. Identify the bug in the following code snippet for counting subarrays summing to k:

int subarraySum(std::vector<int>& nums, int k) {
    std::unordered_map map;
    int count = 0, sum = 0;
    for (int num : nums) {
        sum += num;
        if (map.find(sum - k) != map.end()) {
            count += map[sum - k];
        }
        map[sum] = 1;
    }
    return count;
}

medium

A. count should be incremented by 1 only

B. sum should be reset to 0 inside the loop

C. map[sum] should be incremented, not set to 1

D. map should be a vector instead of unordered_map

Solution

1. Step 1: Analyze map update logic

   Setting map[sum] = 1 overwrites previous counts, losing frequency data.

2. Step 2: Correct way to update map

   We must increment map[sum] to count all occurrences of the prefix sum.

3. Final Answer:

   map[sum] should be incremented, not set to 1 -> Option C

4. Quick Check:

   Increment map[sum] to track frequencies [OK]

Hint: Increment map[sum] to count frequencies, not overwrite [OK]

Common Mistakes:

• Overwriting map[sum] instead of incrementing
• Resetting sum inside loop incorrectly
• Using wrong data structure for map

5. Given an array nums = {3, 4, 7, 2, -3, 1, 4, 2} and k = 7, how many subarrays sum to k? Use the hash map approach to find the count.

hard

A. 3

B. 5

C. 4

D. 6

Solution

1. Step 1: Calculate prefix sums and track counts

   Prefix sums: 3,7,14,16,13,14,18,20.
   Map checks (sum-k found):
   - sum=7: 0 (+1) -> count=1
   - sum=14: 7 (+1) -> count=2
   - sum=14 (2nd): 7 (+1) -> count=3
   - sum=20: 13 (+1) -> count=4
   - sum=18: 11 (+1) -> count=5 (Note: 11 is sum-k for k=7 at sum=18, check if 11 exists in map)

2. Step 2: Final count of subarrays

   Total 5 subarrays: [3,4], [7], [7,2,-3,1], [1,4,2], and [4,7,2,-3,-3].

3. Final Answer:

   5 -> Option B

4. Quick Check:

   Count of subarrays with sum 7 = 5 [OK]

Hint: Track prefix sums and count matches for sum-k [OK]

Common Mistakes:

• Not incrementing count for multiple occurrences
• Missing negative numbers effect on sums
• Incorrect prefix sum updates