Why Subarray Sum Equals K Using Hash Map in DSA C#?

The Big Idea

What if you could instantly find any continuous period that adds up to your target without checking every possibility?

The Scenario

Imagine you have a long list of daily expenses, and you want to find if there is a continuous period where the total spending equals exactly $k. Doing this by checking every possible period manually would take forever.

The Problem

Manually adding sums for every possible sub-list means repeating many calculations, which is slow and tiring. It's easy to make mistakes and miss some periods, especially when the list is long.

The Solution

Using a hash map, we can remember sums we have seen before. This helps us quickly find if a previous sum allows the current sum to form a subarray that equals k, making the search fast and reliable.

Before vs After

✗ Before

int count = 0;
for (int start = 0; start < nums.Length; start++) {
    int sum = 0;
    for (int end = start; end < nums.Length; end++) {
        sum += nums[end];
        if (sum == k) count++;
    }
}

✓ After

Dictionary<int, int> sumCounts = new Dictionary<int, int>();
sumCounts[0] = 1;
int sum = 0, count = 0;
for (int i = 0; i < nums.Length; i++) {
    sum += nums[i];
    if (sumCounts.ContainsKey(sum - k)) count += sumCounts[sum - k];
    if (sumCounts.ContainsKey(sum)) {
        sumCounts[sum] += 1;
    } else {
        sumCounts[sum] = 1;
    }
}

What It Enables

This method lets you find all continuous periods summing to k in a long list instantly, even if the list is huge.

Real Life Example

Tracking your calorie intake daily, you want to find if there was any continuous stretch of days where your total calories matched your target exactly.

Key Takeaways

Manual checking is slow and repeats work.

Hash map remembers sums to find matches quickly.

Efficiently counts all subarrays summing to k in one pass.

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}