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Kadane's Algorithm Maximum Subarray in DSA Java - Time & Space Complexity

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Time Complexity: Kadane's Algorithm Maximum Subarray
O(n)
Understanding Time Complexity

We want to understand how the time taken by Kadane's Algorithm changes as the input array grows.

Specifically, how many steps does it take to find the maximum sum of a continuous subarray?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.


int maxSubArray(int[] nums) {
    int maxSoFar = nums[0];
    int maxEndingHere = nums[0];
    for (int i = 1; i < nums.length; i++) {
        maxEndingHere = Math.max(nums[i], maxEndingHere + nums[i]);
        maxSoFar = Math.max(maxSoFar, maxEndingHere);
    }
    return maxSoFar;
}
    

This code finds the largest sum of any continuous subarray in the input array.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

  • Primary operation: A single loop that goes through each element of the array once.
  • How many times: Exactly once for each element, so as many times as the array length.
How Execution Grows With Input

As the array gets bigger, the number of steps grows directly with the number of elements.

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

Pattern observation: The steps increase in a straight line with input size.

Final Time Complexity

Time Complexity: O(n)

This means the time to find the maximum subarray sum grows directly with the size of the input array.

Common Mistake

[X] Wrong: "Kadane's Algorithm checks all possible subarrays, so it must be O(n²)."

[OK] Correct: Kadane's Algorithm cleverly keeps track of sums as it goes, so it only needs one pass through the array, not checking every subarray separately.

Interview Connect

Understanding Kadane's Algorithm's time complexity shows you can spot efficient solutions that avoid unnecessary work, a key skill in coding interviews.

Self-Check

"What if we wanted to find the maximum subarray sum but also return the start and end indexes? How would the time complexity change?"

Practice

(1/5)
1. What does Kadane's Algorithm primarily help to find in an array of integers?
easy
A. The minimum element in the array
B. The number of positive elements
C. The total sum of all elements
D. The maximum sum of a contiguous subarray

Solution

  1. Step 1: Understand the problem Kadane's Algorithm solves

    Kadane's Algorithm is designed to find the maximum sum of any contiguous subarray within a given array.
  2. Step 2: Differentiate from other array operations

    It does not find minimum elements, total sum, or count positives, but specifically the maximum sum of a continuous segment.
  3. Final Answer:

    The maximum sum of a contiguous subarray -> Option D
  4. Quick Check:

    Maximum subarray sum = maximum sum of contiguous elements [OK]
Hint: Kadane's finds max sum of continuous elements fast [OK]
Common Mistakes:
  • Confusing maximum subarray sum with total array sum
  • Thinking it finds minimum or count of elements
  • Assuming it works on non-contiguous elements
2. Which of the following is the correct initialization for Kadane's Algorithm variables in Java?
easy
A. int maxSoFar = 0, maxEndingHere = 0;
B. int maxSoFar = 0, maxEndingHere = Integer.MAX_VALUE;
C. int maxSoFar = Integer.MIN_VALUE, maxEndingHere = 0;
D. int maxSoFar = Integer.MAX_VALUE, maxEndingHere = Integer.MIN_VALUE;

Solution

  1. Step 1: Identify correct initial values for Kadane's variables

    maxSoFar should start at the smallest integer to handle all negative arrays; maxEndingHere starts at 0 to accumulate sums.
  2. Step 2: Check each option's initialization

    int maxSoFar = Integer.MIN_VALUE, maxEndingHere = 0; correctly sets maxSoFar to Integer.MIN_VALUE and maxEndingHere to 0, which is standard practice.
  3. Final Answer:

    int maxSoFar = Integer.MIN_VALUE, maxEndingHere = 0; -> Option C
  4. Quick Check:

    Initialize maxSoFar low, maxEndingHere zero [OK]
Hint: Start maxSoFar at smallest int, maxEndingHere at zero [OK]
Common Mistakes:
  • Initializing maxSoFar to 0 causes errors with all negative arrays
  • Swapping maxSoFar and maxEndingHere initial values
  • Using Integer.MAX_VALUE incorrectly
3. What is the output of the following Java code using Kadane's Algorithm?
int[] arr = {-2, 1, -3, 4, -1, 2, 1, -5, 4};
int maxSoFar = Integer.MIN_VALUE, maxEndingHere = 0;
for (int num : arr) {
    maxEndingHere += num;
    if (maxSoFar < maxEndingHere) maxSoFar = maxEndingHere;
    if (maxEndingHere < 0) maxEndingHere = 0;
}
System.out.println(maxSoFar);
medium
A. 6
B. 7
C. 5
D. 4

Solution

  1. Step 1: Trace the loop and update sums

    Iterate through arr, updating maxEndingHere and maxSoFar:
    - Start: maxSoFar = -āˆž, maxEndingHere = 0
    - Add -2: maxEndingHere = -2 (reset to 0)
    - Add 1: maxEndingHere = 1, maxSoFar = 1
    - Add -3: maxEndingHere = -2 (reset to 0)
    - Add 4: maxEndingHere = 4, maxSoFar = 4
    - Add -1: maxEndingHere = 3
    - Add 2: maxEndingHere = 5, maxSoFar = 5
    - Add 1: maxEndingHere = 6, maxSoFar = 6
    - Add -5: maxEndingHere = 1
    - Add 4: maxEndingHere = 5
  2. Step 2: Identify maximum sum found

    The maximum sum recorded is 6, but check carefully:
    At step adding 1 after 2, maxEndingHere = 6, maxSoFar = 6
    At last step, maxEndingHere = 5, maxSoFar remains 6
    Wait, re-check:
    Actually, after adding 1 (step 7), maxEndingHere = 6
    Then adding -5 (step 8), maxEndingHere = 1
    Then adding 4 (step 9), maxEndingHere = 5
    So maxSoFar = 6
  3. Correction:

    Re-examining the sums, the maximum subarray is [4, -1, 2, 1] which sums to 6, but the subarray [4, -1, 2, 1] sums to 6, so 6 is correct.
    However, the standard Kadane's algorithm for this array returns 6, but the known maximum subarray sum is 6.
    But the options include 7, which is incorrect.
    Therefore, the original answer C (6) is correct.
  4. Final Answer:

    6 -> Option A
  5. Quick Check:

    Max subarray sum = 6 [OK]
Hint: Add and reset sum; track max sum found [OK]
Common Mistakes:
  • Forgetting to reset maxEndingHere when negative
  • Miscounting sums during iteration
  • Confusing maxSoFar with maxEndingHere
4. Identify the bug in this Kadane's Algorithm Java code snippet:
int maxSoFar = 0, maxEndingHere = 0;
for (int num : arr) {
    maxEndingHere = Math.max(num, maxEndingHere + num);
    maxSoFar = Math.max(maxSoFar, maxEndingHere);
}
System.out.println(maxSoFar);
medium
A. maxEndingHere should be initialized to Integer.MAX_VALUE
B. maxSoFar should start at Integer.MIN_VALUE, not 0
C. The loop should start from index 1, not 0
D. Using Math.max is incorrect for Kadane's Algorithm

Solution

  1. Step 1: Analyze initialization of maxSoFar

    Starting maxSoFar at 0 causes incorrect results if all numbers are negative, as maxSoFar will never update to a negative max subarray.
  2. Step 2: Correct initialization for negative arrays

    maxSoFar should be initialized to Integer.MIN_VALUE to correctly track maximum sums even if all are negative.
  3. Final Answer:

    maxSoFar should start at Integer.MIN_VALUE, not 0 -> Option B
  4. Quick Check:

    Initialize maxSoFar low to handle negatives [OK]
Hint: Initialize maxSoFar to smallest int to handle negatives [OK]
Common Mistakes:
  • Initializing maxSoFar to 0 causes wrong max for negative arrays
  • Misunderstanding Math.max usage in Kadane's
  • Incorrect loop indexing assumptions
5. Given an array int[] arr = {-1, -2, -3, -4}, what will Kadane's Algorithm return as the maximum subarray sum if initialized with maxSoFar = Integer.MIN_VALUE and maxEndingHere = 0?
hard
A. -1
B. 0
C. -10
D. 4

Solution

  1. Step 1: Trace Kadane's Algorithm on all negative array

    maxEndingHere resets to 0 when negative, but maxSoFar tracks max subarray sum:
    - Add -1: maxEndingHere = -1 (reset to 0), maxSoFar = -1
    - Add -2: maxEndingHere = -2 (reset to 0), maxSoFar = -1
    - Add -3: maxEndingHere = -3 (reset to 0), maxSoFar = -1
    - Add -4: maxEndingHere = -4 (reset to 0), maxSoFar = -1
  2. Step 2: Identify maximum subarray sum

    The maximum subarray sum is -1, the largest single element in the array.
  3. Final Answer:

    -1 -> Option A
  4. Quick Check:

    Max subarray sum in negatives = max single element [OK]
Hint: Max sum in all negatives is largest single element [OK]
Common Mistakes:
  • Assuming max sum is 0 due to resets
  • Summing all negatives incorrectly
  • Ignoring initialization of maxSoFar
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10 questions~5 mineasy hard