Merge pull request #137 from daniel-mueller/coding-style-fixes

turned some public methods private

Dynamic Programming/Edit_Distance.java

@@ -0,0 +1,69 @@
+    /**
+    Author : SUBHAM SANGHAI
+    A Dynamic Programming based solution for Edit Distance problem In Java
+    Edit distance is a way of quantifying how dissimilar two strings (e.g., words) are to one another, 
+    by counting the minimum number of operations required to transform one string into the other
+    **/
+    import java.util.HashMap;
+    import java.util.Map;
+    import java.util.Scanner;
+    public class Edit_Distance
+    {
+      public static int minDistance(String word1, String word2) 
+      {
+    	int len1 = word1.length();
+    	int len2 = word2.length();
+     	// len1+1, len2+1, because finally return dp[len1][len2]
+    	int[][] dp = new int[len1 + 1][len2 + 1];
+     
+    	for (int i = 0; i <= len1; i++) 
+    	{
+    		dp[i][0] = i;
+    	}
+     
+    	for (int j = 0; j <= len2; j++) 
+    	{
+    		dp[0][j] = j;
+    	}
+     	//iterate though, and check last char
+    	for (int i = 0; i < len1; i++) 
+    	{
+    		char c1 = word1.charAt(i);
+    		for (int j = 0; j < len2; j++) 
+    		{
+    			char c2 = word2.charAt(j);
+     			//if last two chars equal
+    			if (c1 == c2)
+    			{
+    				//update dp value for +1 length
+    				dp[i + 1][j + 1] = dp[i][j];
+    			} 
+    			else 
+    			{
+    				int replace = dp[i][j] + 1;
+    				int insert = dp[i][j + 1] + 1;
+    				int delete = dp[i + 1][j] + 1;
+     
+    				int min = replace > insert ? insert : replace;
+    				min = delete > min ? min : delete;
+    				dp[i + 1][j + 1] = min;
+    			}
+    		}
+    	}
+    	return dp[len1][len2];
+      }
+    	// Driver program to test above function
+    	public static void main(String args[])
+    	{
+    		Scanner input = new Scanner(System.in);
+    		String s1,s2;
+    		System.out.println("Enter the First String");
+    		s1 = input.nextLine();
+    		System.out.println("Enter the Second String");
+    		s2 = input.nextLine();
+    		//ans stores the final Edit Distance between the two strings
+    		int ans=0;
+    		ans=minDistance(s1,s2);
+    		System.out.println("The minimum Edit Distance between \"" + s1 + "\" and \"" + s2 +"\" is "+ans);
+    	}
+    }

Dynamic Programming/Fibonacci.java

@@ -11,7 +11,7 @@ import java.util.Map;
 
 public class Fibonacci {
 
-    public static Map<Integer,Integer> map = new HashMap<Integer,Integer>();
+    private static Map<Integer,Integer> map = new HashMap<Integer,Integer>();
 
     public static void main(String[] args) throws Exception {
 
@@ -29,7 +29,7 @@ public class Fibonacci {
      * Outputs the nth fibonacci number
      **/
 
-    public static int fibMemo(int n) {
+    private static int fibMemo(int n) {
         if (map.containsKey(n)) {
             return map.get(n);
         }
@@ -54,7 +54,7 @@ public class Fibonacci {
      * Outputs the nth fibonacci number
      **/
 
-    public static int fibBotUp(int n) {
+    private static int fibBotUp(int n) {
 
         Map<Integer,Integer> fib = new HashMap<Integer,Integer>();
 

Dynamic Programming/Levenshtein_distance.java

@@ -7,7 +7,7 @@
  */
 
 public class Levenshtein_distance{
-	private int minimum(int a, int b, int c){
+	private static int minimum(int a, int b, int c){
 		if(a < b && a < c){
 			return a;
 		}else if(b < a && b < c){
@@ -16,7 +16,7 @@ public class Levenshtein_distance{
 			return c;
 		}
 	}
-	public int calculate_distance(String a, String b){
+	private static int calculate_distance(String a, String b){
 		len_a = a.length() + 1;
 		len_b = b.length() + 1;
 		int [][] distance_mat = new int[len_a][len_b];

Dynamic Programming/LongestIncreasingSubsequence.java

@@ -31,7 +31,7 @@ public class LongestIncreasingSubsequence {
         return r;
     }
 
-    public static int LIS(int[] array) {
+    private static int LIS(int[] array) {
         int N = array.length;
         if (N == 0)
             return 0;