Why Tabulation Bottom Up DP in DSA C?

The Big Idea

What if you could solve big problems by solving small ones first, without repeating yourself?

The Scenario

Imagine you want to find the number of ways to climb stairs, but you try to count every possible step combination by hand.

For example, climbing 10 stairs by taking 1 or 2 steps at a time.

The Problem

Counting all combinations manually is slow and confusing.

You might repeat counting the same steps again and again, making mistakes and wasting time.

The Solution

Tabulation Bottom Up DP helps by solving small parts first and storing their answers.

Then it builds up to the final answer without repeating work.

Before vs After

✗ Before

int countWays(int n) {
    if (n <= 1) return 1;
    return countWays(n-1) + countWays(n-2);
}

✓ After

int countWays(int n) {
    int dp[n+1];
    dp[0] = 1; dp[1] = 1;
    for (int i = 2; i <= n; i++) {
        dp[i] = dp[i-1] + dp[i-2];
    }
    return dp[n];
}

What It Enables

This method makes solving complex problems fast and reliable by avoiding repeated work.

Real Life Example

Calculating the number of ways to pay a bill using different coin denominations efficiently.

Key Takeaways

Manual counting repeats work and is slow.

Tabulation stores answers from small problems up to big ones.

It saves time and avoids mistakes.

Practice

1. What is the main idea behind Tabulation Bottom Up DP in dynamic programming?

easy

A. Build a table from the smallest subproblems up to the main problem

B. Solve the problem by recursion without storing results

C. Use random guesses to find the solution

D. Start solving from the biggest problem and break it down

Solution

1. Step 1: Understand the DP approach

   Tabulation means filling a table starting from the smallest subproblems.

2. Step 2: Compare with other methods

   Unlike recursion without storage, tabulation avoids repeated work by building up solutions.

3. Final Answer:

   Build a table from the smallest subproblems up to the main problem -> Option A

4. Quick Check:

   Bottom Up DP = Build table from small to big [OK]

Hint: Think: solve small parts first, then bigger ones [OK]

Common Mistakes:

• Confusing tabulation with recursion without memoization
• Thinking tabulation starts from the biggest problem
• Assuming tabulation guesses solutions randomly

2. Which of the following is the correct way to declare a DP table for Fibonacci numbers using tabulation in C?

easy

A. int dp[] = {0};

B. int dp[100] = {0};

C. int dp = 100;

D. int dp(100);

Solution

1. Step 1: Check C array declaration syntax

   In C, arrays are declared with size and type, e.g., int dp[100];

2. Step 2: Identify correct initialization

   int dp[100] = {0}; declares an int array of size 100 initialized to zero, suitable for DP table.

3. Final Answer:

   int dp[100] = {0}; -> Option B

4. Quick Check:

   C arrays need size and type [OK]

Hint: Use int dp[size] = {0} for zero-initialized arrays [OK]

Common Mistakes:

• Using parentheses instead of brackets for arrays
• Not specifying array size
• Assigning integer to array variable

3. What will be the output of the following C code using bottom-up DP to find Fibonacci number for n=5?

#include 
int main() {
    int n = 5;
    int dp[6] = {0};
    dp[0] = 0;
    dp[1] = 1;
    for(int i = 2; i <= n; i++) {
        dp[i] = dp[i-1] + dp[i-2];
    }
    printf("%d", dp[n]);
    return 0;
}

medium

A. 13

B. 8

C. 3

D. 5

Solution

1. Step 1: Trace DP table filling

   dp[0]=0, dp[1]=1; then dp[2]=1, dp[3]=2, dp[4]=3, dp[5]=5.

2. Step 2: Identify dp[n] value

   dp[5] = 5, so output is 5.

3. Final Answer:

   5 -> Option D

4. Quick Check:

   Fibonacci(5) = 5 [OK]

Hint: Remember Fibonacci sequence: 0,1,1,2,3,5... [OK]

Common Mistakes:

• Off-by-one errors in loop range
• Confusing dp indices with Fibonacci numbers
• Printing dp[n-1] instead of dp[n]

4. Find the error in this bottom-up DP code snippet for Fibonacci numbers:

int fib(int n) {
    int dp[n+1];
    dp[0] = 0;
    dp[1] = 1;
    for(int i = 1; i <= n; i++) {
        dp[i] = dp[i-1] + dp[i-2];
    }
    return dp[n];
}

medium

A. Array dp is not initialized to zero

B. Return statement should be dp[n-1]

C. Loop starts at 1 instead of 2 causing invalid access

D. Function should return void

Solution

1. Step 1: Check loop start index

   Loop starts at i=1, but dp[i-2] for i=1 is dp[-1], invalid index.

2. Step 2: Correct loop start

   Loop should start at i=2 to avoid negative index access.

3. Final Answer:

   Loop starts at 1 instead of 2 causing invalid access -> Option C

4. Quick Check:

   Loop must start at 2 to access dp[i-2] safely [OK]

Hint: Start loop at 2 for Fibonacci tabulation [OK]

Common Mistakes:

• Starting loop at 1 causing negative index
• Ignoring array bounds in DP
• Returning wrong dp index

5. Given the problem to find the minimum number of coins to make amount 7 using coins {1, 3, 4} with bottom-up DP, what is the minimum number of coins needed? Use this approach:

int coins[] = {1, 3, 4};
int amount = 7;
int dp[8];
dp[0] = 0;
for (int i = 1; i <= amount; i++) {
    dp[i] = INT_MAX;
    for (int j = 0; j < 3; j++) {
        if (coins[j] <= i && dp[i - coins[j]] != INT_MAX) {
            dp[i] = dp[i] < dp[i - coins[j]] + 1 ? dp[i] : dp[i - coins[j]] + 1;
        }
    }
}
printf("%d", dp[amount]);

hard

A. 2

B. 4

C. 3

D. 5

Solution

1. Step 1: Calculate dp values step-by-step

   dp[0]=0 For i=1: dp[1]=1 (coin 1) For i=2: dp[2]=2 (1+1) For i=3: dp[3]=1 (coin 3) For i=4: dp[4]=1 (coin 4) For i=5: dp[5]=2 (4+1) For i=6: dp[6]=2 (3+3) For i=7: dp[7]=2 (3+4)

2. Step 2: Identify minimum coins for amount 7

   Minimum coins needed for 7 is 2.

3. Final Answer:

   2 -> Option A

4. Quick Check:

   Minimum coins for 7 = 2 [OK]

Hint: Build dp from 0 to amount, pick min coins each step [OK]

Common Mistakes:

• Not updating dp[i] with minimum value
• Ignoring INT_MAX checks causing wrong results
• Confusing coin values and indices