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DSA Goprogramming

Fibonacci Using DP in DSA Go

Choose your learning style10 modes available
Mental Model
Remember past Fibonacci numbers so you don't calculate them again.
Analogy: Like writing down each step of a recipe so you don't have to guess or redo steps later.
fib[0] = 0
fib[1] = 1
fib[2] = ?
fib[3] = ?
fib[4] = ?
...
Dry Run Walkthrough
Input: Calculate Fibonacci number for n=5 using DP
Goal: Find the 5th Fibonacci number efficiently by storing previous results
Step 1: Initialize fib array with fib[0]=0 and fib[1]=1
fib: [0, 1, ?, ?, ?, ?]
Why: Base cases are known and needed to build next numbers
Step 2: Calculate fib[2] = fib[1] + fib[0] = 1 + 0
fib: [0, 1, 1, ?, ?, ?]
Why: Use stored values to find next Fibonacci number
Step 3: Calculate fib[3] = fib[2] + fib[1] = 1 + 1
fib: [0, 1, 1, 2, ?, ?]
Why: Build next number from previous two
Step 4: Calculate fib[4] = fib[3] + fib[2] = 2 + 1
fib: [0, 1, 1, 2, 3, ?]
Why: Continue building sequence using stored results
Step 5: Calculate fib[5] = fib[4] + fib[3] = 3 + 2
fib: [0, 1, 1, 2, 3, 5]
Why: Final Fibonacci number for n=5 found efficiently
Result:
fib: [0, 1, 1, 2, 3, 5]
Answer: 5
Annotated Code
DSA Go
package main

import "fmt"

func fibonacciDP(n int) int {
	if n <= 1 {
		return n
	}
	fib := make([]int, n+1)
	fib[0], fib[1] = 0, 1
	for i := 2; i <= n; i++ {
		fib[i] = fib[i-1] + fib[i-2]
	}
	return fib[n]
}

func main() {
	result := fibonacciDP(5)
	fmt.Println(result)
}
if n <= 1 { return n }
Handle base cases directly to avoid unnecessary computation
fib := make([]int, n+1) fib[0], fib[1] = 0, 1
Initialize array to store Fibonacci numbers with base values
for i := 2; i <= n; i++ { fib[i] = fib[i-1] + fib[i-2] }
Fill array by summing previous two Fibonacci numbers
return fib[n]
Return the nth Fibonacci number from stored results
OutputSuccess
5
Complexity Analysis
Time: O(n) because we calculate each Fibonacci number once from 2 to n
Space: O(n) because we store all Fibonacci numbers up to n in an array
vs Alternative: Compared to naive recursion which is O(2^n), DP is much faster by avoiding repeated calculations
Edge Cases
n = 0
Returns 0 immediately as base case
DSA Go
if n <= 1 {
	return n
}
n = 1
Returns 1 immediately as base case
DSA Go
if n <= 1 {
	return n
}
n is large (e.g., 50)
Calculates efficiently without stack overflow or repeated work
DSA Go
fib := make([]int, n+1)
When to Use This Pattern
When you see a problem asking for Fibonacci or similar sequences, use DP to store past results and avoid repeated work.
Common Mistakes
Mistake: Using naive recursion without memoization causing exponential time
Fix: Use an array to store results and build up from base cases
Mistake: Not handling base cases n=0 or n=1 correctly
Fix: Add explicit checks to return n when n <= 1
Summary
Calculates Fibonacci numbers efficiently by storing previous results.
Use when you need Fibonacci numbers or similar sequences without repeated calculations.
Remember to build from base cases and store each result to avoid repeated work.

Practice

(1/5)
1. What is the main advantage of using Dynamic Programming (DP) to calculate Fibonacci numbers compared to a simple recursive approach?
easy
A. It avoids repeated calculations by storing intermediate results.
B. It uses less memory by not storing any results.
C. It calculates Fibonacci numbers randomly.
D. It uses recursion without any optimization.

Solution

  1. Step 1: Understand recursion inefficiency

    Simple recursion recalculates the same Fibonacci values multiple times, causing exponential time complexity.
  2. Step 2: Role of DP in optimization

    DP stores previously computed Fibonacci numbers in a table (memoization or tabulation), avoiding repeated work and improving efficiency.
  3. Final Answer:

    It avoids repeated calculations by storing intermediate results. -> Option A
  4. Quick Check:

    DP stores results = avoids repeats [OK]
Hint: DP saves past results to speed up Fibonacci calculation [OK]
Common Mistakes:
  • Thinking DP uses less memory than recursion
  • Believing DP calculates values randomly
  • Confusing DP with plain recursion
2. Which of the following Go code snippets correctly initializes a slice to store Fibonacci numbers for DP with size n?
easy
A. fib := new(int)
B. fib := make([]int, n+1)
C. fib := []int{n}
D. fib := [n]int{}

Solution

  1. Step 1: Understand slice initialization

    To store Fibonacci numbers up to n, we need a slice of length n+1 to hold indices 0 through n.
  2. Step 2: Check each option

    fib := make([]int, n+1) uses make with length n+1, correctly creating a slice. fib := []int{n} creates a slice with one element n, not size n+1. fib := new(int) creates a pointer to int, not a slice. fib := [n]int{} is invalid syntax for slice.
  3. Final Answer:

    fib := make([]int, n+1) -> Option B
  4. Quick Check:

    make slice with n+1 length = correct [OK]
Hint: Use make([]int, n+1) to create DP slice for Fibonacci [OK]
Common Mistakes:
  • Using array syntax instead of slice
  • Creating pointer instead of slice
  • Initializing slice with wrong length
3. What is the output of the following Go code snippet?
func fibDP(n int) int {
    fib := make([]int, n+1)
    fib[0], fib[1] = 0, 1
    for i := 2; i <= n; i++ {
        fib[i] = fib[i-1] + fib[i-2]
    }
    return fib[n]
}

fmt.Println(fibDP(5))
medium
A. 13
B. 8
C. 3
D. 5

Solution

  1. Step 1: Trace Fibonacci values in slice

    fib[0]=0, fib[1]=1; then fib[2]=1, fib[3]=2, fib[4]=3, fib[5]=5.
  2. Step 2: Return fib[5]

    The function returns fib[5], which is 5.
  3. Final Answer:

    5 -> Option D
  4. Quick Check:

    Fibonacci(5) = 5 [OK]
Hint: Trace fib array from 0 to n to find fib[n] [OK]
Common Mistakes:
  • Confusing index with Fibonacci value
  • Returning fib[n-1] instead of fib[n]
  • Off-by-one errors in loop
4. Identify the error in this Go function for Fibonacci using DP and select the fix:
func fibDP(n int) int {
    fib := make([]int, n)
    fib[0], fib[1] = 0, 1
    for i := 2; i <= n; i++ {
        fib[i] = fib[i-1] + fib[i-2]
    }
    return fib[n]
}
medium
A. Return fib[n-1] instead of fib[n].
B. Initialize fib[0] and fib[1] to 1 and 1.
C. Change slice size to n+1 to avoid index out of range.
D. Change loop to for i := 1; i < n; i++.

Solution

  1. Step 1: Check slice size and indexing

    Slice fib is created with length n, but loop and return access fib[n], which is out of range.
  2. Step 2: Fix slice size

    Increase slice size to n+1 so fib[n] is valid and no runtime error occurs.
  3. Final Answer:

    Change slice size to n+1 to avoid index out of range. -> Option C
  4. Quick Check:

    Slice size must cover all indices accessed [OK]
Hint: Slice length must be at least n+1 for fib[n] access [OK]
Common Mistakes:
  • Not increasing slice size causes runtime panic
  • Changing initial values incorrectly
  • Modifying loop incorrectly causing wrong results
5. You want to compute the 10th Fibonacci number using DP but with constant space (only two variables). Which Go code snippet correctly implements this optimization?
hard
A. func fib(n int) int { a, b := 0, 1 for i := 2; i <= n; i++ { a, b = b, a+b } return b }
B. func fib(n int) int { fib := make([]int, n+1) fib[0], fib[1] = 0, 1 for i := 2; i <= n; i++ { fib[i] = fib[i-1] + fib[i-2] } return fib[n] }
C. func fib(n int) int { if n <= 1 { return n } return fib(n-1) + fib(n-2) }
D. func fib(n int) int { a, b := 0, 1 for i := 1; i < n; i++ { a = b b = a + b } return a }

Solution

  1. Step 1: Understand constant space DP

    We only keep last two Fibonacci numbers and update them iteratively to save space.
  2. Step 2: Analyze options

    func fib(n int) int { a, b := 0, 1 for i := 2; i <= n; i++ { a, b = b, a+b } return b } correctly updates a and b simultaneously and returns b as fib(n). func fib(n int) int { fib := make([]int, n+1) fib[0], fib[1] = 0, 1 for i := 2; i <= n; i++ { fib[i] = fib[i-1] + fib[i-2] } return fib[n] } uses slice (not constant space). func fib(n int) int { if n <= 1 { return n } return fib(n-1) + fib(n-2) } is simple recursion (inefficient). func fib(n int) int { a, b := 0, 1 for i := 1; i < n; i++ { a = b b = a + b } return a } updates variables incorrectly causing wrong result.
  3. Final Answer:

    func fib(n int) int { a, b := 0, 1 for i := 2; i <= n; i++ { a, b = b, a+b } return b } -> Option A
  4. Quick Check:

    Update two vars simultaneously for constant space [OK]
Hint: Update two vars together to save space in Fibonacci DP [OK]
Common Mistakes:
  • Using slice instead of variables for DP
  • Incorrect variable update order causing wrong sums
  • Using recursion without memoization
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