views:

555

answers:

3

Hi I have found this code in the internet and it was for arrays ,I want to change it for doubly linked list(instead of index we should use pointer) would you please help me that how can i change merge method(I have changed sort method by myself) also this is not my home work ,I love working with linked list!!

public class MergeSort {

private DoublyLinkedList LocalDoublyLinkedList;

public MergeSort(DoublyLinkedList list) {
    LocalDoublyLinkedList = list;

}

public void sort() {

    if (LocalDoublyLinkedList.size() <= 1) {
        return;
    }
    DoublyLinkedList listOne = new DoublyLinkedList();
    DoublyLinkedList listTwo = new DoublyLinkedList();
    for (int x = 0; x < (LocalDoublyLinkedList.size() / 2); x++) {
        listOne.add(x, LocalDoublyLinkedList.getValue(x));
}
for (int x = (LocalDoublyLinkedList.size() / 2) + 1; x < LocalDoublyLinkedList.size`(); x++) {`
    listTwo.add(x, LocalDoublyLinkedList.getValue(x));
}
//Split the DoublyLinkedList again
    MergeSort sort1 = new MergeSort(listOne);
    MergeSort sort2 = new MergeSort(listTwo);
    sort1.sort();
    sort2.sort();

    merge(listOne, listTwo);
}

private void merge(DoublyLinkedList a, DoublyLinkedList b) {
    int x = 0;
    int y = 0;
    int z = 0;
    while (x < first.length && y < second.length) {
        if (first[x] < second[y]) {
            a[z] = first[x];
            x++;
        } else {
            a[z] = second[y];
            y++;
        }
        z++;
    }
//copy remaining elements to the tail of a[];
    for (int i = x; i < first.length; i++) {
        a[z] = first[i];
        z++;
    }
    for (int i = y; i < second.length; i++) {
        a[z] = second[i];
        z++;
    }
}
}
A: 

It depends on what DoublyLinkedList is - is it a concrete user-defined type, or just an alias name for a linked list type?

In the first case, you should have indexed get/set methods and/or an iterator defined in it, which make the task simple.

In the latter case, why not use the standard java.util.LinkedList?

In terms of the List interface, the operation could be implemented like this:

<T> List<T> merge(List<T> first, List<T> second, List<T> merged) {
  if (first.isEmpty())
    merged.adAll(second);
  else if (second.isEmpty())
    merged.adAll(first);
  else {
    Iterator<T> firstIter = first.iterator();
    Iterator<T> secondIter = second.iterator();
    T firstElem = firstIter.next();
    T secondElem = secondIter.next();

    do {
      if (firstElem < secondElem) {
        merged.add(firstElem);
        firstElem = firstIter.hasNext() ? firstIter.next() : null;
      } else {
        merged.add(secondElem);
        secondElem = secondIter.hasNext() ? secondIter.next() : null;
      }
    } while (firstIter.hasNext() && secondIter.hasNext());
    //copy remaining elements to the tail of merged
    if (firstElem != null)
      merged.add(firstElem);
    if (secondElem != null)
      merged.add(secondElem);
    while (firstIter.hasNext()) {
      merged.add(firstIter.next());
    }
    while (secondIter.hasNext()) {
      merged.add(secondIter.next());
    }
  }
}

This implementation is a bit more tedious than it would be with arrays, mostly since iterators are "consumed" by the next operation, so one must keep account of the current item in each list. With get, the code would be simpler, quite similar to the array solution, however it would be way slower for big lists, as @sepp2k pointed out.

A couple more notes:

  • the Java tradition is to use lowercase variable names, hence localDoublyLinkedList
  • Java has no pointers, only references.
Péter Török
Mentioning indexed get/set methods without also mentioning that they're O(n) for linked lists seems a bit dangerous to me. You should definitely not use get and set when writing a sorting algorithm.
sepp2k
+1  A: 

Merge sort requires splitting the list quite often. Isn't iterating to the middle of a LinkedList pretty much the most expensive operation you can perform on it (well, short of sorting it)? I could see the merge step working pretty well (you're iterating forwards over two linked lists), but I'm not sure that this implementation is worth the trouble without an O(1) split operation.

Followup

As pointed out to me, the O(n) split operation doesn't really add much to complexity when you're already doing O(n) things during the merge phase. Nevertheless, you're still going to run into trouble doing iteration like you're doing (not using an Iterator but instead using get on a List with poor random-access characteristics).

I was bored while debugging some other issue so wrote you what I consider to be a decent Java implementation of this algorithm. I followed Wikipedia's pseudocode verbatim and sprinkled in some generics and print statements. If you have any questions or concerns, just ask.

import java.util.List;
import java.util.LinkedList;

/**
 * This class implements the mergesort operation, trying to stay
 * as close as possible to the implementation described on the
 * Wikipedia page for the algorithm. It is meant to work well
 * even on lists with non-constant random-access performance (i.e.
 * LinkedList), but assumes that {@code size()} and {@code get(0)}
 * are both constant-time.
 *
 * @author jasonmp85
 * @see <a href="http://en.wikipedia.org/wiki/Merge_sort"&gt;Merge sort</a>
 */
public class MergeSort {
    /**
     * Keeps track of the call depth for printing purposes
     */
    private static int depth = 0;

    /**
     * Creates a list of 10 random Longs and sorts it
     * using {@link #sort(List)}.
     *
     * Prints out the original list and the result.
     *
     */
    public static void main(String[] args) {
        LinkedList<Long> list = new LinkedList<Long>();

        for(int i = 0; i < 10; i++) {
            list.add((long)(Math.random() * 100));
        }

        System.out.println("ORIGINAL LIST\n" + 
                           "=================\n" +
                           list + "\n");

        List<Long> sorted = sort(list);

        System.out.println("\nFINAL LIST\n" +
                           "=================\n" +
                           sorted + "\n");
    }

    /**
     * Performs a merge sort of the items in {@code list} and returns a
     * new List.
     *
     * Does not make any calls to {@code List.get()} or {@code List.set()}.
     * 
     * Prints out the steps, indented based on call depth.
     *
     * @param list the list to sort
     */
    public static <T extends Comparable<T>> List<T> sort(List<T> list) {
        depth++;
        String tabs = getTabs();

        System.out.println(tabs + "Sorting: " + list);

        if(list.size() <= 1) {
            depth--;
            return list;
        }

        List<T> left   = new LinkedList<T>();
        List<T> right  = new LinkedList<T>();
        List<T> result = new LinkedList<T>();

        int middle = list.size() / 2;

        int added = 0;
        for(T item: list) {
            if(added++ < middle)
                left.add(item);
            else
                right.add(item);
        }

        left = sort(left);
        right = sort(right);

        result = merge(left, right);

        System.out.println(tabs + "Sorted to: " + result);

        depth--;
        return result;
    }

    /**
     * Performs the oh-so-important merge step. Merges {@code left}
     * and {@code right} into a new list, which is returned.
     *
     * @param left the left list
     * @param right the right list
     * @return a sorted version of the two lists' items
     */
    private static <T extends Comparable<T>> List<T> merge(List<T> left,
                                                           List<T> right) {
        String tabs = getTabs();
        System.out.println(tabs + "Merging: " + left + " & " + right);

        List<T> result = new LinkedList<T>();
        while(left.size() > 0 && right.size() > 0) {
            if(left.get(0).compareTo(right.get(0)) < 0)
                result.add(left.remove(0));
            else
                result.add(right.remove(0));
        }

        if(left.size() > 0)
            result.addAll(left);
        else
            result.addAll(right);

        return result;
    }

    /**
     * Returns a number of tabs based on the current call depth.
     *
     */
    private static String getTabs() {
        StringBuffer sb = new StringBuffer("");
        for(int i = 0; i < depth; i++)
            sb.append('\t');
        return sb.toString();
    }
}

To Run

  1. Save the code to a file named MergeSort.java
  2. Run javac MergeSort.java
  3. Run java MergeSort
  4. Marvel
  5. Optionally, run javadoc -private MergeSort.java to create the documentation. Open the index.html file it creates.
jasonmp85
@jasonmp85: The split operation is expensive indeed, but note that the overall complexity is still optimal. The recurrence relation is T(N) = 2T(N/2)+1.5N, and it can be shown easily that T(N) = O(N log N)
Eyal Schneider
+1  A: 

First of all, you must NOT use indexes when dealing with linked lists. Do it like this:

while (i < in.size/2){
  listOne.addLast( in.remove(in.first()) );
  i++
}
while(!in.isEmptly){
  listTwo.addLast( in.remove(in.first()) );
}

And for merging

merge(a, b, out){
  while(!a.empty && !b.empty){
    if(a.first() >= b.first())
      out.addLast( a.remove(a.first()) );
    else
     out.addLast( b.remove(b.first()) );

  //remember to take care of the remaining elements 
  while(!a.empty)
    out.addLast( a.remove(a.first()) );
  while(!b.empty)
    out.addLast( b.remove(b.first()) );
}

This way it will still be O(n log n)

takoi