Largest Rectangle in Histogram Using Stack in DSA Go - Time & Space Complexity

Time Complexity: Largest Rectangle in Histogram Using Stack

O(n)

Understanding Time Complexity

We want to understand how the time needed to find the largest rectangle in a histogram changes as the number of bars grows.

How does the algorithm's work increase when the histogram gets bigger?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

func largestRectangleArea(heights []int) int {
    stack := []int{}
    maxArea := 0
    for i := 0; i <= len(heights); i++ {
        var h int
        if i == len(heights) {
            h = 0
        } else {
            h = heights[i]
        }
        for len(stack) > 0 && h < heights[stack[len(stack)-1]] {
            height := heights[stack[len(stack)-1]]
            stack = stack[:len(stack)-1]
            var width int
            if len(stack) == 0 {
                width = i
            } else {
                width = i - stack[len(stack)-1] - 1
            }
            area := height * width
            if area > maxArea {
                maxArea = area
            }
        }
        stack = append(stack, i)
    }
    return maxArea
}
    

This code finds the largest rectangle area in a histogram by using a stack to keep track of bars.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: A single loop over all bars with inner while-loop popping from the stack.
• How many times: Each bar is pushed and popped at most once, so total operations scale with number of bars.

How Execution Grows With Input

As the number of bars increases, the algorithm processes each bar a limited number of times.

Input Size (n)	Approx. Operations
10	About 20 (push and pop each bar once)
100	About 200
1000	About 2000

Pattern observation: The operations grow roughly in a straight line with input size.

Final Time Complexity

Time Complexity: O(n)

This means the time to find the largest rectangle grows directly in proportion to the number of bars.

Common Mistake

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

[OK] Correct: The inner loop does not run fully for each outer loop step; each bar is pushed and popped only once, so total work is linear.

Interview Connect

Understanding this algorithm shows you can use stacks smartly to solve problems efficiently, a skill valued in many coding challenges.

Self-Check

"What if we used a simple nested loop to check all rectangles instead of a stack? How would the time complexity change?"

Practice

1. What is the main purpose of using a stack in the Largest Rectangle in Histogram problem?

easy

A. To sort the histogram bars by height

B. To store the maximum area found so far

C. To keep track of bars' indices with increasing heights

D. To reverse the order of histogram bars

Solution

1. Step 1: Understand stack usage

   The stack stores indices of bars in increasing height order to find boundaries efficiently.

2. Step 2: Purpose in algorithm

   This helps quickly calculate the largest rectangle when a smaller height bar is found.

3. Final Answer:

   To keep track of bars' indices with increasing heights -> Option C

4. Quick Check:

   Stack tracks increasing bars = B [OK]

Hint: Stack stores indices of increasing heights [OK]

Common Mistakes:

• Thinking stack sorts bars by height
• Using stack to store areas instead of indices
• Ignoring the order of bars in stack

2. Which Go syntax correctly declares a stack to hold indices for the histogram bars?

easy

A. var stack []int

B. stack := make(map[int]int)

C. stack := []string{}

D. var stack int

Solution

1. Step 1: Identify stack type

   The stack holds indices, which are integers, so it should be a slice of int.

2. Step 2: Check syntax correctness

   "var stack []int" declares an empty slice of int, suitable for stack operations.

3. Final Answer:

   var stack []int -> Option A

4. Quick Check:

   Stack as []int slice = C [OK]

Hint: Use slice of int for stack indices [OK]

Common Mistakes:

• Using map instead of slice for stack
• Declaring stack as int instead of slice
• Using string slice for integer indices

3. What is the output of the following Go code snippet for histogram heights [2, 1, 5, 6, 2, 3]?

func largestRectangleArea(heights []int) int {
    stack := []int{}
    maxArea := 0
    for i := 0; i <= len(heights); i++ {
        var h int
        if i == len(heights) {
            h = 0
        } else {
            h = heights[i]
        }
        for len(stack) > 0 && h < heights[stack[len(stack)-1]] {
            height := heights[stack[len(stack)-1]]
            stack = stack[:len(stack)-1]
            var width int
            if len(stack) == 0 {
                width = i
            } else {
                width = i - stack[len(stack)-1] - 1
            }
            area := height * width
            if area > maxArea {
                maxArea = area
            }
        }
        stack = append(stack, i)
    }
    return maxArea
}

fmt.Println(largestRectangleArea([]int{2, 1, 5, 6, 2, 3}))

medium

A. 6

B. 12

C. 8

D. 10

Solution

1. Step 1: Trace stack and area calculation

   Process bars: max area found is 10 (from bars 5 and 6 with width 2).

2. Step 2: Confirm max area

   No larger rectangle found; 10 is the largest rectangle area.

3. Final Answer:

   10 -> Option D

4. Quick Check:

   Largest rectangle area = 10 [OK]

Hint: Largest area is max of all popped rectangles [OK]

Common Mistakes:

• Forgetting to add a zero height bar at end
• Incorrect width calculation after popping stack
• Not updating maxArea correctly

4. Identify the bug in this Go code snippet for Largest Rectangle in Histogram:

for i := 0; i < len(heights); i++ {
    for len(stack) > 0 && heights[i] < heights[stack[len(stack)-1]] {
        height := heights[stack[len(stack)-1]]
        stack = stack[:len(stack)-1]
        width := i
        if len(stack) > 0 {
            width = i - stack[len(stack)-1] - 1
        }
        area := height * width
        if area > maxArea {
            maxArea = area
        }
    }
    stack = append(stack, i)
}
return maxArea

medium

A. Loop should run until i <= len(heights) with a sentinel zero height

B. Width calculation is incorrect when stack is empty

C. Stack should store heights, not indices

D. maxArea should be reset inside the loop

Solution

1. Step 1: Check loop boundary

   The loop misses processing the last bars fully without a sentinel zero height at the end.

2. Step 2: Fix loop to include sentinel

   Loop should run until i <= len(heights) and treat i == len(heights) as height 0 to pop all remaining bars.

3. Final Answer:

   Loop should run until i <= len(heights) with a sentinel zero height -> Option A

4. Quick Check:

   Loop boundary with sentinel zero fixes bug [OK]

Hint: Add sentinel zero height to process all bars [OK]

Common Mistakes:

• Not adding sentinel zero height
• Incorrect width calculation when stack empty
• Resetting maxArea inside loop incorrectly

5. Given a histogram with heights [6, 2, 5, 4, 5, 1, 6], what is the largest rectangle area using the stack method?

hard

A. 12

B. 15

C. 8

D. 10

Solution

1. Step 1: Analyze bars and stack operations

   Largest rectangle is formed by bars with min height 5 spanning width 3 (indices 2 to 4: heights 5,4,5), area = 5*3 = 15.

2. Step 2: Confirm no larger area

   Other rectangles like 4*3=12 or 2*5=10 are smaller; 15 is maximum.

3. Final Answer:

   15 -> Option B

4. Quick Check:

   Max rectangle area = 15 [OK]

Hint: Check width between popped bars for max area [OK]

Common Mistakes:

• Calculating width incorrectly
• Missing wider rectangle spanning multiple bars
• Not popping all bars at the end