š Scenario: Imagine you want to find the nth number in the Fibonacci sequence. This sequence starts with 0 and 1, and each next number is the sum of the two before it. Calculating this directly can be slow for big numbers. We will use a method called Tabulation Bottom Up Dynamic Programming to solve it efficiently.
šÆ Goal: You will build a Java program that uses a table (array) to store Fibonacci numbers from the bottom up. This way, you avoid repeating calculations and get the answer quickly.
š What You'll Learn
Create an integer variable n with the value 10
Create an integer array fibTable of size n + 1
Fill the base cases for Fibonacci in fibTable
Use a for loop with variable i from 2 to n to fill the table
Print the Fibonacci number at position n from fibTable
š” Why This Matters
š Real World
Calculating Fibonacci numbers efficiently is useful in computer science problems like algorithm design, financial modeling, and biological computations.
š¼ Career
Understanding dynamic programming and tabulation is important for software engineering interviews and solving optimization problems in real projects.
Progress0 / 4 steps
1
Create the input variable n
Create an integer variable called n and set it to 10.
DSA Java
Hint
Use int n = 10; inside the main method.
2
Create the Fibonacci table array fibTable
Create an integer array called fibTable with size n + 1.
DSA Java
Hint
Use int[] fibTable = new int[n + 1]; to create the array.
3
Fill base cases and build the table using a for loop
Set fibTable[0] to 0 and fibTable[1] to 1. Then use a for loop with variable i from 2 to n to fill fibTable[i] as the sum of fibTable[i - 1] and fibTable[i - 2].
DSA Java
Hint
Remember to set the first two Fibonacci numbers before the loop.
4
Print the Fibonacci number at position n
Print the value of fibTable[n] using System.out.println.
DSA Java
Hint
Use System.out.println(fibTable[n]); to print the result.
Practice
(1/5)
1. What is the main idea behind Tabulation Bottom Up DP in dynamic programming?
easy
A. Solve the problem by recursion without storing results
B. Start solving from the biggest problem and break it down
C. Use random guesses to find the solution
D. Build a table from the smallest subproblems up to the main problem
Solution
Step 1: Understand Tabulation Approach
Tabulation means filling a table starting from the smallest subproblems to bigger ones.
Step 2: Compare with other methods
Unlike recursion, tabulation avoids repeated work by storing results in a table.
Final Answer:
Build a table from the smallest subproblems up to the main problem -> Option D
Quick Check:
Tabulation = Bottom Up DP [OK]
Hint: Think bottom-up: solve small parts first, then bigger [OK]
Common Mistakes:
Confusing tabulation with recursion
Thinking tabulation starts from the biggest problem
Ignoring the use of a table to store results
2. Which of the following is the correct way to initialize a DP array for bottom-up Fibonacci in Java?
easy
A. int[] dp = new int[n+1]; dp[0] = 0; dp[1] = 1;
B. int[] dp = new int[n]; dp[1] = 0; dp[2] = 1;
C. int[] dp = new int[n+1]; dp[0] = 1; dp[1] = 1;
D. int[] dp = new int[n]; dp[0] = 0; dp[1] = 1;
Solution
Step 1: Check array size for Fibonacci
We need size n+1 to store from 0 to n indices.
Step 2: Set base cases correctly
Fibonacci starts with dp[0]=0 and dp[1]=1.
Final Answer:
int[] dp = new int[n+1]; dp[0] = 0; dp[1] = 1; -> Option A
Quick Check:
Base cases dp[0]=0, dp[1]=1 [OK]
Hint: Array size n+1 and dp[0]=0, dp[1]=1 for Fibonacci [OK]
Common Mistakes:
Using wrong array size causing IndexOutOfBounds
Swapping base case values
Starting indices from 1 instead of 0
3. What will be the output of the following Java code using bottom-up DP to find Fibonacci of 5?
int n = 5;
int[] dp = new int[n+1];
dp[0] = 0; dp[1] = 1;
for (int i = 2; i <= n; i++) {
dp[i] = dp[i-1] + dp[i-2];
}
System.out.println(dp[n]);
medium
A. 13
B. 5
C. 3
D. 8
Solution
Step 1: Trace DP array filling
dp[2]=1, dp[3]=2, dp[4]=3, dp[5]=5 by adding previous two values.
4. Identify the error in this bottom-up DP code for Fibonacci:
int n = 5;
int[] dp = new int[n];
dp[0] = 0; dp[1] = 1;
for (int i = 2; i <= n; i++) {
dp[i] = dp[i-1] + dp[i-2];
}
System.out.println(dp[n]);
medium
A. Array size is too small, causing IndexOutOfBoundsException
B. Base cases dp[0] and dp[1] are incorrect
C. Loop condition should be i < n instead of i <= n
D. No error, code runs fine
Solution
Step 1: Check array size
Array dp has size n=5, valid indices 0 to 4 only.
Step 2: Loop accesses dp[5]
Loop runs i=2 to 5 inclusive, dp[5] access causes error.
Final Answer:
Array size is too small, causing IndexOutOfBoundsException -> Option A
Quick Check:
Array size must be n+1 for dp[n] access [OK]
Hint: Array size must cover all indices used in loop [OK]
Common Mistakes:
Using array size n instead of n+1
Ignoring loop boundary causing runtime error
Assuming code runs without error
5. You want to find the number of ways to climb n stairs if you can take 1 or 2 steps at a time using bottom-up DP. Which code snippet correctly implements this?
hard
A. int[] dp = new int[n+1]; dp[0]=0; dp[1]=1; for(int i=2;i<=n;i++){ dp[i]=dp[i-1]+dp[i-2]; } return dp[n];
B. int[] dp = new int[n]; dp[0]=1; dp[1]=2; for(int i=2;i
C. int[] dp = new int[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];
D. int[] dp = new int[n+1]; dp[0]=1; dp[1]=1; for(int i=1;i<=n;i++){ dp[i]=dp[i-1]+dp[i-2]; } return dp[n];
Solution
Step 1: Initialize base cases for climbing stairs
dp[0]=1 means 1 way to stand still; dp[1]=1 means 1 way to climb 1 step.
Step 2: Fill dp using sum of previous two steps
For iā„2, dp[i] = dp[i-1] + dp[i-2] counts ways taking 1 or 2 steps.
Step 3: Check loop and return
Loop runs i=2 to n inclusive; return dp[n] is correct.
Final Answer:
int[] dp = new int[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]; -> Option C