Maximum Product Subarray in DSA Typescript - Time & Space Complexity

Time Complexity: Maximum Product Subarray

O(n)

Understanding Time Complexity

We want to understand how the time needed to find the maximum product of a subarray changes as the input array grows.

How does the number of steps grow when the array gets bigger?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

function maxProduct(nums: number[]): number {
  let maxProd = nums[0], minProd = nums[0], result = nums[0];
  for (let i = 1; i < nums.length; i++) {
    const tempMax = maxProd;
    maxProd = Math.max(nums[i], maxProd * nums[i], minProd * nums[i]);
    minProd = Math.min(nums[i], tempMax * nums[i], minProd * nums[i]);
    result = Math.max(result, maxProd);
  }
  return result;
}
    

This code finds the maximum product of any contiguous 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: The loop runs exactly once for each element after the first, so (n - 1) times if n is the array length.

How Execution Grows With Input

As the array size grows, the number of steps grows roughly the same way.

Input Size (n)	Approx. Operations
10	About 9 loop steps
100	About 99 loop steps
1000	About 999 loop steps

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

Final Time Complexity

Time Complexity: O(n)

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

Common Mistake

[X] Wrong: "Because we check multiple products inside the loop, the time complexity is more than linear, maybe quadratic."

[OK] Correct: Inside the loop, the operations are constant time and do not depend on the input size, so the overall time still grows linearly.

Interview Connect

Understanding this linear time solution shows you can handle tricky problems efficiently, a skill that is valuable in many coding challenges and real projects.

Self-Check

"What if we used a nested loop to check every possible subarray product? How would the time complexity change?"

Practice

1. What does the "Maximum Product Subarray" problem ask you to find in an array of integers?

easy

A. The subarray with the largest sum of its elements

B. The contiguous subarray with the largest product of its elements

C. The longest subarray with all positive numbers

D. The subarray with the smallest product of its elements

Solution

1. Step 1: Understand the problem statement

   The problem asks for a contiguous part of the array where the product of all numbers is as large as possible.

2. Step 2: Differentiate from similar problems

   This is different from finding the largest sum or smallest product; it specifically focuses on the product of elements in a continuous segment.

3. Final Answer:

   The contiguous subarray with the largest product of its elements -> Option B

4. Quick Check:

   Maximum product subarray means largest product segment [OK]

Hint: Look for continuous elements with max product, not sum [OK]

Common Mistakes:

• Confusing product with sum
• Ignoring that subarray must be contiguous
• Thinking about longest subarray instead of max product

2. Which of the following TypeScript function signatures correctly represents a function to find the maximum product subarray?

easy

A. function maxProduct(nums: number[]): number

B. function maxProduct(nums: string): number

C. function maxProduct(nums: number): number[]

D. function maxProduct(nums: number[]): string

Solution

1. Step 1: Check input parameter type

   The input should be an array of numbers, so nums: number[] is correct.

2. Step 2: Check return type

   The function returns the maximum product value, which is a number, not an array or string.

3. Final Answer:

   function maxProduct(nums: number[]): number -> Option A

4. Quick Check:

   Input array, output number matches signature [OK]

Hint: Input is number array, output is single number [OK]

Common Mistakes:

• Using string type for input or output
• Returning array instead of number
• Incorrect parameter types

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

function maxProduct(nums: number[]): number {
  let maxProd = nums[0];
  let minProd = nums[0];
  let result = nums[0];
  for (let i = 1; i < nums.length; i++) {
    if (nums[i] < 0) {
      [maxProd, minProd] = [minProd, maxProd];
    }
    maxProd = Math.max(nums[i], maxProd * nums[i]);
    minProd = Math.min(nums[i], minProd * nums[i]);
    result = Math.max(result, maxProd);
  }
  return result;
}

console.log(maxProduct([2, 3, -2, 4]));

medium

A. 6

B. 4

C. -2

D. 24

Solution

1. Step 1: Initialize variables and start loop

   maxProd, minProd, and result start at 2. Loop from index 1 to 3.

2. Step 2: Iterate and update maxProd, minProd, and result

   At i=1 (3): maxProd = max(3, 2*3)=6, minProd = min(3, 2*3)=3, result=6.
   At i=2 (-2): nums[i]<0, swap maxProd and minProd: maxProd=3, minProd=6.
   maxProd = max(-2, 3*(-2)) = max(-2, -6) = -2.
   minProd = min(-2, 6*(-2)) = min(-2, -12) = -12.
   result = max(6, -2) = 6.
   At i=3 (4): maxProd = max(4, -2*4) = max(4, -8) = 4.
   minProd = min(4, -12*4) = min(4, -48) = -48.
   result = max(6, 4) = 6.

3. Final Answer:

   6 -> Option A

4. Quick Check:

   Max product subarray is [2,3] = 6 [OK]

Hint: Track max and min products, swap on negative [OK]

Common Mistakes:

• Not swapping max and min on negative number
• Only tracking max product, ignoring min product
• Confusing max product with sum

4. Identify the bug in this TypeScript function for maximum product subarray:

function maxProduct(nums: number[]): number {
  let maxProd = 1;
  let minProd = 1;
  let result = Number.MIN_VALUE;
  for (let num of nums) {
    if (num < 0) {
      let temp = maxProd;
      maxProd = minProd;
      minProd = temp;
    }
    maxProd = Math.max(num, maxProd * num);
    minProd = Math.min(num, minProd * num);
    result = Math.max(result, maxProd);
  }
  return result;
}

medium

A. Initializing maxProd and minProd to 0 instead of 1

B. Not swapping maxProd and minProd when num is positive

C. Using a for loop instead of forEach

D. Using Number.MIN_VALUE instead of Number.NEGATIVE_INFINITY for result

Solution

1. Step 1: Understand Number.MIN_VALUE usage

   Number.MIN_VALUE is the smallest positive number close to zero, not the most negative number.

2. Step 2: Correct initialization for result

   To track maximum product correctly, result should start at Number.NEGATIVE_INFINITY to handle negative products properly.

3. Final Answer:

   Using Number.MIN_VALUE instead of Number.NEGATIVE_INFINITY for result -> Option D

4. Quick Check:

   Use Number.NEGATIVE_INFINITY for max tracking [OK]

Hint: Use Number.NEGATIVE_INFINITY for max initial value [OK]

Common Mistakes:

• Confusing Number.MIN_VALUE with negative infinity
• Not swapping max and min on negative number
• Wrong initial values for maxProd and minProd

5. Given the array [-1, -3, -10, 0, 60], what is the maximum product subarray and its product?

hard

A. Subarray: [-1, -3, -10], Product: -30

B. Subarray: [-3, -10, 0], Product: 0

C. Subarray: [60], Product: 60

D. Subarray: [-10, 0, 60], Product: 0

Solution

1. Step 1: Analyze subarrays and their products

   Check products of contiguous subarrays:
   [-1] = -1
   [-1, -3] = 3
   [-1, -3, -10] = -30
   [-3] = -3
   [-3, -10] = 30
   [-10] = -10
   [0] = 0
   [60] = 60

2. Step 2: Identify maximum product

   The largest product found is 60 from subarray [60].

3. Final Answer:

   Subarray: [60], Product: 60 -> Option C

4. Quick Check:

   Max product is 60 from single element [60] [OK]

Hint: Check single elements and negative pairs carefully [OK]

Common Mistakes:

• Assuming negative product is maximum
• Ignoring single element subarrays
• Confusing zero product with max product