demonstrate power of dynamic programmic using fibonacci calculation

Author: NirmalSilwal

CodingBlocks Training/Day27/fibonacciDynamicProg.java

@@ -0,0 +1,84 @@
+package Lecture27;
+
+
+public class fibonacciDynamicProg {
+
+	// to demonstrate time taken by DP approach and without DP approach
+
+	public static long STARTTIME;
+	public static long ENDTIME;
+
+	public static void startAlgo() {
+		STARTTIME = System.currentTimeMillis();
+	}
+
+	public static long endAlgo() {
+		ENDTIME = System.currentTimeMillis();
+		return ENDTIME - STARTTIME;
+	}
+
+	public static void main(String[] args) {
+
+		int nthItem = 45;
+
+		startAlgo();
+		System.out.println(fibonacciRecursiveOptimal(nthItem));
+		System.out.println("time taken using DP approach in ms:" + endAlgo());
+
+		System.out.println();
+		
+		startAlgo();
+		System.out.println(fibonacciNonOptimal(nthItem)); 
+		System.out.println("time taken without using DP approach in ms: " + endAlgo());
+	}
+
+	// time complexity: O(n)
+	public static int fibonacciRecursiveOptimal(int n) {
+		int[] memStorage = new int[n + 1];
+		return fibonacciRecursiveOptimal(n, memStorage);
+	}
+
+	private static int fibonacciRecursiveOptimal(int n, int[] storage) {
+		if (n == 0 || n == 1) {
+			return n;
+		}
+
+		// accessing previously calculated factorial value of n
+		if (storage[n] != 0) {
+			return storage[n];
+		}
+		int fnm1 = fibonacciRecursiveOptimal(n - 1, storage);
+		int fnm2 = fibonacciRecursiveOptimal(n - 2, storage);
+
+		int fibbN = fnm1 + fnm2;
+
+		storage[n] = fibbN;
+
+		return fibbN;
+	}
+
+	// without using DP approach
+	// time complexity: Exponential
+	public static int fibonacciNonOptimal(int n) {
+		if (n == 0 || n == 1) {
+			return n;
+		}
+
+		int fnm1 = fibonacciNonOptimal(n - 1);
+		int fnm2 = fibonacciNonOptimal(n - 2);
+
+		int fibbN = fnm1 + fnm2;
+
+		return fibbN;
+	}
+
+}
+
+
+/* output:
+1134903170
+time taken using DP approach in ms:0
+
+1134903170
+time taken without using DP approach in ms: 7393
+*/