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 understand 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.

public int SubarraySum(int[] nums, int k) {
    var count = 0;
    var sum = 0;
    var map = new Dictionary<int, int>();
    map[0] = 1;
    
    foreach (var num in nums) {
        sum += num;
        if (map.ContainsKey(sum - k)) {
            count += map[sum - k];
        }
        map[sum] = map.GetValueOrDefault(sum, 0) + 1;
    }
    return count;
}
    

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

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: One loop through the array, checking and updating the hash map.
• How many times: Exactly once for each element in the array (n times).

How Execution Grows With Input

Each new element adds a fixed amount of work: updating sums and hash map lookups.

Input Size (n)	Approx. Operations
10	About 10 checks and updates
100	About 100 checks and updates
1000	About 1000 checks and updates

Pattern observation: The work grows directly with the number of elements, so doubling the input doubles the work.

Final Time Complexity

Time Complexity: O(n)

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

Common Mistake

[X] Wrong: "Because there is a nested check inside the loop, the time is O(n²)."

[OK] Correct: The inner check is a quick hash map lookup, which is on average O(1), so it does not multiply the loop time.

Interview Connect

Understanding this pattern shows you can use extra memory smartly to speed up searching problems, a key skill in coding interviews.

Self-Check

"What if we replaced the hash map with a list and searched it each time? 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 store cumulative sums and their frequencies for quick lookup

B. To sort the array elements before processing

C. To store the original array elements as keys

D. To reverse the array for easier traversal

Solution

1. Step 1: Understand the problem goal

   The problem wants to find subarrays whose sums equal a target value k.

2. Step 2: Role of hash map in solution

   The hash map stores cumulative sums seen so far and how many times they occurred, enabling quick checks for needed sums.

3. Final Answer:

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

4. Quick Check:

   Hash map stores sums = A [OK]

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

Common Mistakes:

• Thinking hash map stores array elements directly
• Assuming sorting is needed
• Using hash map to reverse array

2. Which of the following is the correct way to declare a hash map (Dictionary) in C# to store cumulative sums and their counts?

easy

A. Dictionary sumCounts = new Dictionary();

B. HashMap sumCounts = new HashMap();

C. Map sumCounts = new Map();

D. Dictionary sumCounts = new Dictionary();

Solution

1. Step 1: Identify correct C# dictionary syntax

   C# uses Dictionary<TKey, TValue> with new Dictionary<TKey, TValue>() to declare hash maps.

2. Step 2: Check each option

   Dictionary sumCounts = new Dictionary(); uses correct generic syntax. Options B and C use Java-like syntax. Dictionary sumCounts = new Dictionary(); misses generic types.

3. Final Answer:

   Dictionary sumCounts = new Dictionary(); -> Option A

4. Quick Check:

   C# Dictionary syntax = A [OK]

Hint: Use Dictionary in C# for hash maps [OK]

Common Mistakes:

• Using Java HashMap syntax in C#
• Omitting generic type parameters
• Using non-existent Map type in C#

3. What is the output of the following C# code snippet?

int[] nums = {1, 2, 3};
int k = 3;
int count = 0;
Dictionary sumCounts = new Dictionary();
sumCounts[0] = 1;
int sum = 0;
foreach (int num in nums) {
    sum += num;
    if (sumCounts.ContainsKey(sum - k)) {
        count += sumCounts[sum - k];
    }
    if (sumCounts.ContainsKey(sum)) {
        sumCounts[sum]++;
    } else {
        sumCounts[sum] = 1;
    }
}
Console.WriteLine(count);

medium

A. 1

B. 0

C. 3

D. 2

Solution

1. Step 1: Calculate cumulative sums and check counts

   nums = [1,2,3], k=3. sumCounts starts with {0:1}. - sum=1: sum-k= -2 (not in sumCounts), count=0, sumCounts={0:1,1:1} - sum=3: sum-k=0 (in sumCounts=1), count=1, sumCounts={0:1,1:1,3:1} - sum=6: sum-k=3 (in sumCounts=1), count=2, sumCounts={0:1,1:1,3:1,6:1}

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 D

4. Quick Check:

   Subarrays count = 2 [OK]

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

Common Mistakes:

• Not initializing sumCounts with {0:1}
• Forgetting to update count correctly
• Misunderstanding sum-k lookup

4. Identify the bug in this C# code snippet for counting subarrays summing to k:

int[] nums = {1, 1, 1};
int k = 2;
int count = 0;
Dictionary sumCounts = new Dictionary();
int sum = 0;
foreach (int num in nums) {
    sum += num;
    if (sumCounts.ContainsKey(sum - k)) {
        count += sumCounts[sum - k];
    }
    sumCounts[sum] = 1;
}
Console.WriteLine(count);

medium

A. nums array is empty

B. sumCounts is not initialized with sum 0 count 1

C. count is not incremented correctly

D. sum variable is not updated inside the loop

Solution

1. Step 1: Check initialization of sumCounts

   sumCounts should start with {0:1} to count subarrays starting at index 0, but here it is empty.

2. Step 2: Check updating sumCounts inside loop

   sumCounts[sum] = 1 overwrites counts instead of incrementing, but main bug is missing initial {0:1}.

3. Final Answer:

   sumCounts is not initialized with sum 0 count 1 -> Option B

4. Quick Check:

   Initialize sumCounts[0] = 1 [OK]

Hint: Always initialize sumCounts with {0:1} before loop [OK]

Common Mistakes:

• Not initializing sumCounts with {0:1}
• Overwriting counts instead of incrementing
• Ignoring sum-k lookup logic

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

hard

A. 5

B. 3

C. 4

D. 6

Solution

1. Step 1: Calculate cumulative sums and track counts

   Initialize sumCounts = {0:1}, sum=0, count=0. - i=0: sum=3, sum-k=-4(not found), count=0, sumCounts={0:1,3:1} - i=1: sum=7, sum-k=0(found=1), count=1, sumCounts={0:1,3:1,7:1} - i=2: sum=14, sum-k=7(found=1), count=2, sumCounts={0:1,3:1,7:1,14:1} - i=3: sum=16, sum-k=9(not found), count=2, sumCounts={0:1,3:1,7:1,14:1,16:1} - i=4: sum=13, sum-k=6(not found), count=2, sumCounts={0:1,3:1,7:1,14:1,16:1,13:1} - i=5: sum=14, sum-k=7(found=1), count=3, sumCounts[14]=2 - i=6: sum=18, sum-k=11(not found), count=3, sumCounts={0:1,3:1,7:1,14:2,16:1,13:1,18:1} - i=7: sum=20, sum-k=13(found=1), count=4, sumCounts={0:1,3:1,7:1,14:2,16:1,13:1,18:1,20:1}

2. Step 2: Verify the counted subarrays

   Subarrays summing to 7 are: - [3,4] - [7] - [7,2,-3,1] - [1,4,2] Count is 4 total.

3. Final Answer:

   4 -> Option C

4. Quick Check:

   Count subarrays with sum k = 4 [OK]

Hint: Track sums and counts carefully to find all subarrays [OK]

Common Mistakes:

• Missing subarrays with negative numbers
• Not updating counts when sum repeats
• Forgetting to initialize sumCounts with {0:1}