Rod Cutting Problem in DSA Go - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main goal of the Rod Cutting Problem?

To cut a rod into pieces to maximize the total selling price based on given prices for different lengths.

beginner

What technique is commonly used to solve the Rod Cutting Problem efficiently?

Dynamic Programming is used to avoid repeated calculations by storing results of subproblems.

beginner

In the Rod Cutting Problem, what does the 'price array' represent?

It represents the selling price for rods of different lengths, where the index corresponds to the length.

intermediate

Why is a bottom-up approach preferred over a naive recursive approach in the Rod Cutting Problem?

Because bottom-up avoids repeated calculations and runs faster by building solutions from smaller lengths up to the full length.

intermediate

What is the time complexity of the dynamic programming solution for the Rod Cutting Problem?

O(n^2), where n is the length of the rod, due to nested loops over lengths and cuts.

What does the Rod Cutting Problem aim to maximize?

A Number of pieces cut

B Total selling price of cut pieces

C Length of the longest piece

D Minimum price of any piece

The goal is to maximize the total selling price obtained by cutting the rod into pieces.

Which programming technique helps avoid repeated calculations in the Rod Cutting Problem?

A Dynamic Programming

B Greedy Algorithm

C Backtracking

D Brute Force

Dynamic Programming stores results of subproblems to avoid repeated work.

What is the input that defines the prices for different rod lengths?

A Cut array

B Length array

C Price array

D Weight array

The price array holds prices for rods of lengths from 1 to n.

What is the time complexity of the dynamic programming solution for rod cutting of length n?

A O(n)

B O(n!)

C O(log n)

D O(n^2)

The solution uses nested loops leading to O(n^2) time complexity.

Which approach builds the solution from smaller subproblems up to the full problem?

A Bottom-up dynamic programming

B Top-down recursion without memoization

C Greedy approach

D Divide and conquer

Bottom-up dynamic programming solves smaller problems first and uses their results.

Explain how dynamic programming solves the Rod Cutting Problem.

Think about how you can reuse answers for smaller rod lengths.

Describe the difference between naive recursion and dynamic programming in the Rod Cutting Problem.

Consider how many times the same subproblem is solved.

Practice

1. What is the main goal of the Rod Cutting Problem in algorithms?

easy

A. To count the total number of ways to cut the rod

B. To maximize the total profit by cutting the rod into pieces

C. To find the shortest rod length possible

D. To minimize the number of cuts made on the rod

Solution

1. Step 1: Understand the problem objective

   The rod cutting problem aims to cut a rod into pieces to get the maximum total price from selling those pieces.

2. Step 2: Identify the goal

   The goal is to maximize profit, not minimize cuts or count ways.

3. Final Answer:

   To maximize the total profit by cutting the rod into pieces -> Option B

4. Quick Check:

   Maximize profit = To maximize the total profit by cutting the rod into pieces [OK]

Hint: Focus on maximizing profit, not minimizing cuts or counting ways [OK]

Common Mistakes:

• Thinking the goal is to minimize cuts
• Confusing with counting number of ways
• Assuming shortest rod length is the goal

2. Which of the following Go function signatures correctly represents a rod cutting function that takes rod length and price slice as input and returns maximum profit as int?

easy

A. func rodCutting(prices int, length []int) int

B. func rodCutting(prices []int, length int) bool

C. func rodCutting(length int, prices []int) string

D. func rodCutting(length int, prices []int) int

Solution

1. Step 1: Analyze parameter types and order

   The rod length should be an int, prices should be a slice of ints ([]int), and return type should be int for max profit.

2. Step 2: Match correct signature

   func rodCutting(length int, prices []int) int matches: func rodCutting(length int, prices []int) int

3. Final Answer:

   func rodCutting(length int, prices []int) int -> Option D

4. Quick Check:

   Correct parameter types and return int = func rodCutting(length int, prices []int) int [OK]

Hint: Remember: length int, prices []int, return int for profit [OK]

Common Mistakes:

• Swapping parameter order
• Wrong return type like string or bool
• Using incorrect parameter types

3. What will be the output of the following Go code snippet for rod length 4 and prices [1, 5, 8, 9]?

package main

import "fmt"

func rodCutting(n int, prices []int) int {
    dp := make([]int, n+1)
    for i := 1; i <= n; i++ {
        maxVal := 0
        for j := 1; j <= i; j++ {
            val := prices[j-1] + dp[i-j]
            if val > maxVal {
                maxVal = val
            }
        }
        dp[i] = maxVal
    }
    return dp[n]
}

func main() {
    prices := []int{1, 5, 8, 9}
    result := rodCutting(4, prices)
    fmt.Println(result)
}

medium

A. 8

B. 9

C. 10

D. 11

Solution

1. Step 1: Understand the dp array calculation

   dp[i] stores max profit for rod length i. For length 4, check all cuts: - Cut 1: price 1 + dp[3] = 1 + 8 = 9 - Cut 2: price 5 + dp[2] = 5 + 5 = 10 - Cut 3: price 8 + dp[1] = 8 + 1 = 9 - Cut 4: price 9 + dp[0] = 9 + 0 = 9

2. Step 2: Calculate dp values stepwise

   dp[1]=1, dp[2]=5, dp[3]=8, dp[4]=max(9,10,9,9)=10 But re-check dp[3]: - Cut 1: 1 + dp[2]=1+5=6 - Cut 2: 5 + dp[1]=5+1=6 - Cut 3: 8 + dp[0]=8+0=8 So dp[3]=8 Now dp[4]: - Cut 1: 1 + dp[3]=1+8=9 - Cut 2: 5 + dp[2]=5+5=10 - Cut 3: 8 + dp[1]=8+1=9 - Cut 4: 9 + dp[0]=9+0=9 Max is 10

3. Final Answer:

   10 -> Option C

4. Quick Check:

   Max profit for length 4 = 10 [OK]

Hint: Calculate dp array stepwise checking all cuts [OK]

Common Mistakes:

• Ignoring dp values for smaller lengths
• Choosing wrong max profit among cuts
• Confusing indices in prices slice

4. Identify the bug in the following Go code for rod cutting and select the correct fix:

func rodCutting(n int, prices []int) int {
    dp := make([]int, n)
    for i := 1; i <= n; i++ {
        maxVal := 0
        for j := 1; j <= i; j++ {
            val := prices[j-1] + dp[i-j]
            if val > maxVal {
                maxVal = val
            }
        }
        dp[i] = maxVal
    }
    return dp[n]
}

medium

A. Change dp size to n+1 and access dp[i] safely

B. Change loop to start from i := 0 instead of 1

C. Remove inner loop and use only prices[i-1]

D. Change return to dp[n-1] instead of dp[n]

Solution

1. Step 1: Identify index out of range error

   dp slice is size n but code accesses dp[i] where i can be n, causing out of range error.

2. Step 2: Fix dp size to n+1

   Make dp size n+1 to safely store dp[n] and avoid index errors.

3. Final Answer:

   Change dp size to n+1 and access dp[i] safely -> Option A

4. Quick Check:

   dp size must be n+1 for dp[n] access [OK]

Hint: dp array size must be n+1 to avoid index errors [OK]

Common Mistakes:

• Using dp size n causes index out of range
• Changing loop start incorrectly
• Removing inner loop breaks logic

5. Given a rod of length 5 and prices [2, 5, 7, 8, 10], what is the maximum profit and the cuts to achieve it using the rod cutting problem approach?

hard

A. Max profit 12 by cuts [2,3]

B. Max profit 11 by cuts [1,4]

C. Max profit 13 by cuts [1,1,3]

D. Max profit 10 by cuts [5]

Solution

1. Step 1: Calculate max profit dp array

   dp[0] = 0
   dp[1] = max(prices[0] + dp[0]) = 2 + 0 = 2
   dp[2] = max(2 + dp[1] = 4, 5 + dp[0] = 5) = 5
   dp[3] = max(2 + dp[2] = 7, 5 + dp[1] = 7, 7 + dp[0] = 7) = 7
   dp[4] = max(2 + dp[3] = 9, 5 + dp[2] = 10, 7 + dp[1] = 9, 8 + dp[0] = 8) = 10
   dp[5] = max(2 + dp[4] = 12, 5 + dp[3] = 12, 7 + dp[2] = 12, 8 + dp[1] = 10, 10 + dp[0] = 10) = 12

2. Step 2: Identify cuts for max profit 12

   Max profit 12 achieved by cuts [2,3] or [3,2]. Prices 5 + 7 = 12.

3. Final Answer:

   Max profit 12 by cuts [2,3] -> Option A

4. Quick Check:

   Max profit 12 with cuts 2 and 3 [OK]

Hint: Calculate dp and track cuts for max profit [OK]

Common Mistakes:

• Not checking all cut combinations
• Assuming single cut is best
• Ignoring dp values for smaller lengths