Maximum Product Subarray in DSA Rust - 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.

use std::cmp::{max, min};

fn max_product(nums: &[i32]) -> i32 {
    let mut max_prod = nums[0];
    let mut min_prod = nums[0];
    let mut result = nums[0];
    for &num in nums[1..].iter() {
        let temp_max = max_prod;
        max_prod = max(num, max(max_prod * num, min_prod * num));
        min_prod = min(num, min(temp_max * num, min_prod * num));
        result = max(result, max_prod);
    }
    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 (n - 1) times, where n is the number of elements in the array.

How Execution Grows With Input

As the array size grows, the number of steps grows roughly the same way, one step per element after the first.

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

Pattern observation: The number of operations grows linearly with the input size.

Final Time Complexity

Time Complexity: O(n)

This means the time to find the maximum product subarray grows in direct proportion to 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, like O(n²)."

[OK] Correct: The multiple checks inside the loop are constant-time operations done once per element, so they do not multiply the loop count. The loop still runs only once per element, keeping the complexity linear.

Interview Connect

Understanding this linear time solution shows you can handle problems that need careful tracking of multiple values while scanning an array once, a common skill in coding interviews.

Self-Check

"What if we used recursion instead of a loop to find the maximum product subarray? 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 smallest product of its elements

B. The subarray with the largest sum of its elements

C. The longest subarray with all positive numbers

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

Solution

1. Step 1: Understand the problem goal

   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 sum problems or longest subarray problems; it focuses on product, not sum or length.

3. Final Answer:

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

4. Quick Check:

   Maximum product subarray = largest product contiguous segment [OK]

Hint: Look for the subarray with the highest multiplication result [OK]

Common Mistakes:

• Confusing product with sum
• Ignoring negative numbers impact
• Thinking about longest subarray instead

2. Which Rust code snippet correctly initializes variables to track the maximum and minimum products for the Maximum Product Subarray problem?

easy

A. let (mut max_prod, mut min_prod, mut result) = (nums[0], nums[0], nums[0]);

B. let max_prod = 0; let min_prod = 0; let result = 0;

C. let max_prod = None; let min_prod = None; let result = None;

D. let (max_prod, min_prod, result) = (0, 0, 0);

Solution

1. Step 1: Identify correct initialization

   We must start with the first element of the array for max, min, and result to handle negative and positive values properly.

2. Step 2: Check Rust syntax for mutable variables

   Variables must be mutable (mut) to update during iteration, and tuple assignment is correct.

3. Final Answer:

   let (mut max_prod, mut min_prod, mut result) = (nums[0], nums[0], nums[0]); -> Option A

4. Quick Check:

   Initialize with first element and mut keyword [OK]

Hint: Initialize with first element and use mut for updates [OK]

Common Mistakes:

• Using zero instead of first element
• Not making variables mutable
• Using Option types unnecessarily

3. What is the output of the following Rust code for the Maximum Product Subarray problem?

let nums = vec![2, 3, -2, 4];
let (mut max_prod, mut min_prod, mut result) = (nums[0], nums[0], nums[0]);
for &num in &nums[1..] {
    if num < 0 {
        let temp = max_prod;
        max_prod = min_prod;
        min_prod = temp;
    }
    max_prod = max_prod.max(num).max(max_prod * num);
    min_prod = min_prod.min(num).min(min_prod * num);
    result = result.max(max_prod);
}
println!("{}", result);

medium

A. 6

B. 8

C. 4

D. -2

Solution

1. Step 1: Trace iteration and variable updates

   Start: max_prod=2, min_prod=2, result=2 - num=3: num>0, max_prod=max(2,3,2*3)=6, min_prod=min(2,3,2*3)=2, result=max(2,6)=6 - num=-2: num<0, swap max_prod and min_prod (max_prod=2, min_prod=6), max_prod=max(2,-2,2*-2)=2, min_prod=min(6,-2,6*-2)=-12, result=max(6,2)=6 - num=4: num>0, max_prod=max(2,4,2*4)=8, min_prod=min(-12,4,-12*4)=-48, result=max(6,8)=8

2. Step 2: Check final result printed

   The code prints the final result variable which is 8 after the last iteration.

3. Final Answer:

   8 -> Option B

4. Quick Check:

   Final max product = 8 [OK]

Hint: Swap max and min on negative, track max product [OK]

Common Mistakes:

• Not swapping max and min on negative number
• Confusing max and min updates
• Forgetting to update result

4. Identify the bug in this Rust code snippet for Maximum Product Subarray:

let nums = vec![2, -5, -2, -4, 3];
let (mut max_prod, mut min_prod, mut result) = (nums[0], nums[0], nums[0]);
for &num in &nums[1..] {
    if num > 0 {
        let temp = max_prod;
        max_prod = min_prod;
        min_prod = temp;
    }
    max_prod = max_prod.max(num).max(max_prod * num);
    min_prod = min_prod.min(num).min(min_prod * num);
    result = result.max(max_prod);
}
println!("{}", result);

medium

A. The loop should start from index 0, not 1

B. Variables max_prod and min_prod are not mutable

C. The swap condition should be for negative numbers, not positive

D. The max and min updates use wrong methods max() and min()

Solution

1. Step 1: Analyze the swap condition

   The code swaps max_prod and min_prod only if num > 0, but it should swap when num is negative to handle sign changes correctly.

2. Step 2: Confirm other parts are correct

   Variables are mutable, loop starts from index 1 correctly, and max/min methods are used properly.

3. Final Answer:

   The swap condition should be for negative numbers, not positive -> Option C

4. Quick Check:

   Swap on negative numbers only [OK]

Hint: Swap max and min only when current number is negative [OK]

Common Mistakes:

• Swapping on positive numbers
• Not swapping at all
• Incorrect loop start index

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

hard

A. Subarray: [60], Product: 60

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

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

D. Subarray: [-1, -3, -10, 0, 60], Product: 0

Solution

1. Step 1: Evaluate products of subarrays

   Check subarrays: - [-1, -3, -10]: product = -1 * -3 * -10 = -30 - [60]: product = 60 - [-3, -10, 0]: product = 0 - Entire array: product = 0 The highest product is 60 from subarray [60].

2. Step 2: Confirm no larger product exists

   Other subarrays with zeros or negatives produce smaller or zero products.

3. Final Answer:

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

4. Quick Check:

   Max product is 60 from single element [OK]

Hint: Check single elements when zeros reset product [OK]

Common Mistakes:

• Ignoring single positive elements after zero
• Multiplying negatives without sign check
• Assuming longer subarray always better