Refactored a few searching algorithms

Added documentation to these algorithms
This commit is contained in:
nik 2018-04-12 16:37:47 +03:00
parent cf778675df
commit 7d178c51b4
6 changed files with 193 additions and 156 deletions

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@ -1,71 +0,0 @@
import java.util.Scanner;
/**
*
* @author Varun Upadhyay (https://github.com/varunu28)
*
*/
class BinarySearch
{
/**
* This method implements the Generic Binary Search
*
* @param array The array to make the binary search
* @param key The number you are looking for
* @param lb The lower bound
* @param ub The upper bound
* @return the location of the key
**/
public static <T extends Comparable<T>> int BS(T array[], T key, int lb, int ub)
{
if ( lb > ub)
return -1;
int mid = (ub+lb) >>> 1;
int comp = key.compareTo(array[mid]);
if (comp < 0)
return (BS(array, key, lb, mid-1));
if (comp > 0)
return (BS(array, key, mid + 1, ub));
return mid;
}
// Driver Program
public static void main(String[] args)
{
Scanner input=new Scanner(System.in);
// For INTEGER Input
Integer[] array = new Integer[10];
int key = 5;
for (int i = 0; i < 10 ; i++ )
array[i] = i+1;
int index = BS(array, key, 0, 9);
if (index != -1)
System.out.println("Number " + key + " found at index number : " + index);
else
System.out.println("Not found");
// For STRING Input
String[] array1 = {"a", "b", "c", "d", "e"};
String key1 = "d";
int index1 = BS(array1, key1, 0, array1.length-1);
if (index1 != -1)
System.out.println("String " + key1 + " found at index number : " + index1);
else
System.out.println("Not found");
input.close();
}
}

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@ -1,77 +0,0 @@
import java.io.BufferedReader;
import java.io.InputStreamReader;
/**
*
* @author Varun Upadhyay (https://github.com/varunu28)
*
*/
public class LinearSearch{
/**
* The main method
* @param args Command line arguments
*/
public static void main(String[] args) throws Exception {
BufferedReader br = new BufferedReader(new InputStreamReader(System.in));
// Test for Integer inputs
Integer[] myArray;
int size = 0;
//Prompt user to create array and its elements
System.out.print("Enter the array size: ");
size = Integer.parseInt(br.readLine());
myArray = new Integer[size];
for (int i = 0; i < size; i++){
System.out.print("For index " + i + ", enter an integer: ");
myArray[i] = Integer.parseInt(br.readLine());
}
//Prompt user to search for particular element
System.out.print("Enter integer to search for: ");
Integer key = Integer.parseInt(br.readLine());
//Output array and index of target element, if found
System.out.printf("The integer %d is found in index %d\n", key, linearSearch(myArray, key));
// Test for String inputs
String[] myArray1;
int size1 = 0;
//Prompt user to create array and its elements
System.out.print("Enter the array size: ");
size1 = Integer.parseInt(br.readLine());
myArray1 = new String[size];
for (int i = 0; i < size1; i++){
System.out.print("For index " + i + ", enter a String: ");
myArray1[i] = br.readLine();
}
//Prompt user to search for particular element
System.out.print("Enter String to search for: ");
String key1 = br.readLine();
//Output array and index of target element, if found
System.out.printf("The string %s is found in index %d\n", key1, linearSearch(myArray1, key1));
}
/**
* Generic Linear search method
*
* @param array List to be searched
* @param value Key being searched for
* @return Location of the key
*/
public static <T extends Comparable<T>> int linearSearch(T[] array, T value) {
int lo = 0;
int hi = array.length - 1;
for (int i = lo; i <= hi; i++) {
if (array[i].compareTo(value) == 0) {
return i;
}
}
return -1;
}
}

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@ -0,0 +1,87 @@
package search;
import java.util.Random;
import java.util.stream.Stream;
/**
*
*
*
* Binary search is one of the most popular algorithms
* The algorithm finds the position of a target value within a sorted array
*
* Worst-case performance O(log n)
* Best-case performance O(1)
* Average performance O(log n)
* Worst-case space complexity O(1)
*
*
* @author Varun Upadhyay (https://github.com/varunu28)
* @author Podshivalov Nikita (https://github.com/nikitap492)
*
* @see SearchAlgorithm
* @see IterativeBinarySearch
*
*/
class BinarySearch implements SearchAlgorithm {
/**
*
* @param array is an array where the element should be found
* @param key is an element which should be found
* @param <T> is any comparable type
* @return index of the element
*/
@Override
public <T extends Comparable<T>> int find(T array[], T key) {
return search(array, key, 0, array.length);
}
/**
* This method implements the Generic Binary Search
*
* @param array The array to make the binary search
* @param key The number you are looking for
* @param left The lower bound
* @param right The upper bound
* @return the location of the key
**/
private <T extends Comparable<T>> int search(T array[], T key, int left, int right){
if (right < left) return -1; // this means that the key not found
// find median
int median = (left + right) >>> 1;
int comp = key.compareTo(array[median]);
if (comp < 0) {
return search(array, key, left, median - 1);
}
if (comp > 0) {
return search(array, key, median + 1, right);
}
return median;
}
// Driver Program
public static void main(String[] args) {
//just generate data
Random r = new Random();
int size = 200;
int maxElement = 100;
Integer[] integers = Stream.generate(() -> r.nextInt(maxElement)).limit(size).sorted().toArray(Integer[]::new);
//the element that should be found
Integer shouldBeFound = integers[r.nextInt(size - 1)];
BinarySearch search = new BinarySearch();
int atIndex = search.find(integers, shouldBeFound);
System.out.println(String.format("Should be found: %d. Found %d at index %d. An array length %d"
, shouldBeFound, integers[atIndex], atIndex, size));
}
}

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@ -1,14 +1,28 @@
package search;
import java.util.Arrays; import java.util.Arrays;
import java.util.Random; import java.util.Random;
/** /**
* Binary search is one of the most popular algorithms
* This class represents iterative version {@link BinarySearch}
* Iterative binary search is likely to have lower constant factors because it doesn't involve the overhead of manipulating the call stack.
* But in java the recursive version can be optimized by the compiler to this version.
*
* Worst-case performance O(log n)
* Best-case performance O(1)
* Average performance O(log n)
* Worst-case space complexity O(1)
* *
* @author Gabriele La Greca : https://github.com/thegabriele97 * @author Gabriele La Greca : https://github.com/thegabriele97
* @author Podshivalov Nikita (https://github.com/nikitap492)
*
* @see SearchAlgorithm
* @see BinarySearch
* *
*/ */
public final class IterativeBinarySearch { public final class IterativeBinarySearch implements SearchAlgorithm {
/** /**
* This method implements an iterative version of binary search algorithm * This method implements an iterative version of binary search algorithm
@ -18,13 +32,14 @@ public final class IterativeBinarySearch {
* *
* @return the index of key in the array or -1 if not found * @return the index of key in the array or -1 if not found
*/ */
public static <T extends Comparable<T>> int binarySearch(T[] array, T key) { @Override
public <T extends Comparable<T>> int find(T[] array, T key) {
int l, r, k, cmp; int l, r, k, cmp;
l = 0; l = 0;
r = array.length - 1; r = array.length;
while (l <= r) { while (l < r) {
k = (l + r) / 2; k = (l + r) / 2;
cmp = key.compareTo(array[k]); cmp = key.compareTo(array[k]);
@ -32,7 +47,7 @@ public final class IterativeBinarySearch {
return k; return k;
} else if (cmp < 0) { } else if (cmp < 0) {
r = --k; r = --k;
} else if (cmp > 0) { } else {
l = ++k; l = ++k;
} }
} }
@ -53,7 +68,7 @@ public final class IterativeBinarySearch {
//Arrays.sort(array); //if needed //Arrays.sort(array); //if needed
Integer key = base + rand.nextInt(array.length * 2); //can generate keys that aren't in array Integer key = base + rand.nextInt(array.length * 2); //can generate keys that aren't in array
System.out.println(binarySearch(array, key)); System.out.println(new IterativeBinarySearch().find(array, key));
System.out.println(Arrays.binarySearch(array, key)); System.out.println(Arrays.binarySearch(array, key));
} }
} }

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@ -0,0 +1,63 @@
package search;
import java.util.Random;
import java.util.stream.Stream;
/**
* Linear search is the easiest search algorithm
* It works with sorted and unsorted arrays (an binary search works only with sorted array)
* This algorithm just compares all elements of an array to find a value
*
* Worst-case performance O(n)
* Best-case performance O(1)
* Average performance O(n)
* Worst-case space complexity
*
*
* @author Varun Upadhyay (https://github.com/varunu28)
* @author Podshivalov Nikita (https://github.com/nikitap492)
*
*
* @see BinarySearch
* @see SearchAlgorithm
*/
public class LinearSearch implements SearchAlgorithm {
/**
* Generic Linear search method
*
* @param array List to be searched
* @param value Key being searched for
* @return Location of the key
*/
@Override
public <T extends Comparable<T>> int find(T[] array, T value) {
for (int i = 0; i < array.length ; i++) {
if (array[i].compareTo(value) == 0) {
return i;
}
}
return -1;
}
public static void main(String[] args) {
//just generate data
Random r = new Random();
int size = 200;
int maxElement = 100;
Integer[] integers = Stream.generate(() -> r.nextInt(maxElement)).limit(size).toArray(Integer[]::new);
//the element that should be found
Integer shouldBeFound = integers[r.nextInt(size - 1)];
LinearSearch search = new LinearSearch();
int atIndex = search.find(integers, shouldBeFound);
System.out.println(String.format("Should be found: %d. Found %d at index %d. An array length %d"
, shouldBeFound, integers[atIndex], atIndex, size));
}
}

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@ -0,0 +1,20 @@
package search;
/**
* The common interface of most searching algorithms
*
* @author Podshivalov Nikita (https://github.com/nikitap492)
*
**/
public interface SearchAlgorithm {
/**
*
* @param key is an element which should be found
* @param array is an array where the element should be found
* @param <T> Comparable type
* @return first found index of the element
*/
<T extends Comparable<T>> int find(T array[], T key);
}