LISTS ===== Let's consider two different data structures for storing a list of things: an array and a linked list. An array is a pretty obvious way to store a list, with a big advantage: it enables very fast access of each item. However, it has two disadvantages. First, if we want to insert an item at the beginning or middle of an array, we have to slide a lot of items over one place to make room. This takes time proportional to the length of the array. Second, an array has a fixed length that can't be changed. If we want to add items to the list, but the array is full, we have to allocate a whole new array and move all the ints from the old array to the new one. public class AList { int a[]; int lastItem; public AList() { a = new int[10]; // The number "10" is arbitrary. lastItem = -1; } public void insertItem(int newItem, int location) { int i; if (lastItem + 1 == a.length) { // No room left in the array? int b[] = new int[2 * a.length]; // Allocate a new array, twice as long. for (i = 0; i <= lastItem; i++) { // Copy items to the bigger array. b[i] = a[i]; } a = b; // Replace the too-small array with the new one. } for (i = lastItem; i >= location; i--) { // Shift items to the right. a[i + 1] = a[i]; } a[location] = newItem; lastItem++; } } LINKED LISTS (a recursive data type) ============ We can avoid these problems by choosing a Scheme-like representation of lists. A linked list is made up of _nodes_. Each node has two components: an item, and a reference to the next node in the list. These components are analogous to "car" and "cdr". However, our node is an explicitly defined object. public class ListNode { // ListNode is a recursive type public int item; public ListNode next; // Here we're using ListNode before } // we've finished declaring it. Let's make some ListNodes. ListNode l1 = new ListNode(), l2 = new ListNode(), l3 = new ListNode(); l1.item = 7; l2.item = 0; l3.item = 6; ------------- ------------- ------------- | ----- | | ----- | | ----- | | item| 7 | | | item| 0 | | | item| 6 | | l1-->| ----- | l2-->| ----- | l3-->| ----- | | ----- | | ----- | | ----- | | next| ? | | | next| ? | | | next| ? | | | ----- | | ----- | | ----- | ------------- ------------- ------------- Now let's link them together. l1.next = l2; l2.next = l3; What about the last node? We need a reference that doesn't reference anything. In Java, this is called "null". l3.next = null; ------------- ------------- ------------- | ----- | | ----- | | ----- | | item| 7 | | | item| 0 | | | item| 6 | | l1-->| ----- | l2-->| ----- | l3-->| ----- | | ----- | | ----- | | ----- | | next| .-+-+-------->| next| .-+-+-------->| next| X | | | ----- | | ----- | | ----- | ------------- ------------- ------------- To simplify programming, let's add some constructors to the ListNode class. public ListNode(int i, ListNode n) { item = i; next = n; } public ListNode(int i) { this(i, null); } These constructors allow us to emulate Scheme's "cons" operation. ListNode l1 = new ListNode(7, new ListNode(0, new ListNode(6))); Linked lists vs. array lists ---------------------------- Linked lists have several advantages over array-based lists. Inserting an item into the middle of a linked list takes just a small constant amount of time, if you already have a reference to the previous node (and don't have to walk through the whole list searching for it). The list can keep growing until memory runs out. The following method inserts a new item into the list immediately after "this". public void insertAfter(int item) { next = new ListNode(item, next); } l2.insertAfter(3); ------------- ------------- ------------- ------------- | ----- | | ----- | | ----- | | ----- | | item| 7 | | | item| 0 | | | item| 3 | | | item| 6 | | l1-->| ----- | l2-->| ----- | | ----- | l3-->| ----- | | ----- | | ----- | | ----- | | ----- | | next| .-+-+------>| next| .-+-+-->| next| .-+-+------>| next| X | | | ----- | | ----- | | ----- | | ----- | ------------- ------------- ------------- ------------- However, linked lists have a big disadvantage compared to arrays. Finding the nth item of an array takes a tiny, constant amount of time. Finding the nth item of a linked list takes time proportional to n. You have to start at the head of the list and walk forward n - 1 nodes, one "next" at a time. Many of the data structures we will study in this class will be attempts to find a compromise between arrays and linked lists. We'll learn data structures that are fast for both arbitrary lookups (like arrays) _and_ arbitrary insertions (like linked lists). Lists of Objects ---------------- For greater generality, let's change ListNodes so that each node contains not an int, but a reference to any Java object. In Java, we can accomplish this by declaring a reference of type Object. public class SListNode { public Object item; public SListNode next; } The "S" in "SListNode" stands for singly-linked. This will make sense when we contrast these lists with doubly-linked lists later. A List Class ------------ There are two problems with SListNodes. (1) Suppose x and y are pointers to the same shopping list. Suppose we insert a new item at the beginning of the list thusly: x = new SListNode("soap", x); y doesn't point to the new item; y still points to the second item in x's list. If y goes shopping for x, he'll forget to buy soap. (2) How do you represent an empty list? The obvious way is "x = null". However, Java won't let you call a SListNode method--or any method--on a null object. If you write "x.insertAfter(item)" when x is null, you'll get a run-time error, even though x is declared to be a SListNode. The solution is a separate SList class, whose job is to maintain the head (first node) of the list. We will put many of the methods that operate on lists in the SList class, rather than the SListNode class. public class SList { private SListNode head; // First node in list. private int size; // Number of items in list. public SList() { // Here's how to represent an empty list. head = null; size = 0; } public void insertFront(Object item) { head = new SListNode(item, head); size++; } } SList object SListNode object ------------- ------------- String object ----- | ----- | | ----- | ---------- x | .-+----->| size| 1 | | | item| .-+-+---->| milk | ----- | ----- | | ----- | ---------- ----- | ----- | | ----- | y | .-+----->| head| .-+-+-------------------->| next| X | | ----- | ----- | | ----- | ------------- ------------- Now, when you call x.insertFront("fish"), every reference to that SList can see the change. SList SListNode SListNode ------------- ------------- ------------- ----- | ----- | | ----- | -------- | ----- | -------- x | .-+-->| size| 2 | | | item| .-+-+->| fish | | item| .-+-+->| milk | ----- | ----- | | ----- | -------- | ----- | -------- ----- | ----- | | ----- | | ----- | y | .-+-->| head| .-+-+-->| next| .-+-+----------->| next| X | | ----- | ----- | | ----- | | ----- | ------------- ------------- ------------- Another advantage of the SList class is that it can keep a record of the SList's size (number of SListNodes). Hence, the size can be determined more quickly than if the SListNodes had to be counted. The SList ADT ------------- We want the SList ADT to enforce two invariants: (1) An SList's "size" variable is always correct. (2) A list is never circularly linked; there is always a tail node whose "next" reference is null. Both these goals are accomplished by making sure that _only_ the methods of the SList class can change the lists' internal data structures. SList ensures this by two means: (1) The fields of the SList class (head and size) are declared "private". (2) No method of SList returns an SListNode. The first rule is necessary so that the evil tamperer can't change the fields and corrupt the SList or violate invariant (1). The second rule prevents the evil tamperer from changing list items, truncating a list, or creating a cycle in a list, thereby violating invariant (2). DOUBLY-LINKED LISTS =================== As we saw last class, inserting an item at the front of a linked list is easy. Deleting from the front of a list is also easy. However, inserting or deleting an item at the end of a list entails a search through the entire list, which might take a long time. (Inserting at the end is easy if you have a `tail' pointer, as you will learn in Lab 3, but deleting is still hard.) A doubly-linked list is a list in which each node has a reference to the previous node, as well as the next node. class DListNode { | class DList { Object item; | private DListNode head; DListNode next; | private DListNode tail; DListNode prev; | } } | ------------- ------------- ------------- | item| | item| | item| head | -----| | -----| | -----| tail ----- |----- | 4 || |----- | 1 || |----- | 8 || ----- | . +->|| X | -----|<-----++-. | -----|<-----++-. | -----|<-+-. | ----- |----- -----| |----- -----| |----- -----| ----- |prev | .-++----->|prev | .-++----->|prev | X || | -----| | -----| | -----| | next| | next| | next| ------------- ------------- ------------- DLists make it possible to insert and delete items at both ends of the list, taking constant running time per insertion and deletion. The following code removes the tail node (in constant time) if there are at least two items in the DList. tail.prev.next = null; tail = tail.prev; You'll need a special case for a DList with no items. You'll also need a special case for a DList with one item, because tail.prev.next does not exist. (Instead, head needs to be changed.) Let's look at a clever trick for reducing the number of special cases, thereby simplifying our DList code. We designate one DListNode as a _sentinel_, a special node that does not represent an item. Our list representation will be circularly linked, and the sentinel will represent both the head and the tail of the list. Our DList class no longer needs a tail pointer, and the head pointer points to the sentinel. class DList { private DListNode head; private int size; } sentinel ------------- ----- | item|<---+-. | --------------->| -----| ----- | |prev | X || head | |----- -----| | || .-+------+----------------- | |----- -----| | | ---------+------+-. || | | | | next-----|<---------------+----- | | ------------- | | | v v | ---+--------- ------------- ------------- | | | item| | item| | item| | | | -----| | -----| | -----| | |--+-- | 4 || |----- | 1 || |----- | 8 || | || . | -----|<-----++-. | -----|<-----++-. | -----| | |----- -----| |----- -----| |----- -----| | |prev | .-++----->|prev | .-++----->|prev | .-++--- | -----| | -----| | -----| | next| | next| | next| ------------- ------------- ------------- The invariants of the DList ADT are more complicated than the SList invariants. The following invariants apply to the DList with a sentinel. (1) For any DList d, d.head != null. (There's always a sentinel.) (2) For any DListNode x, x.next != null. (3) For any DListNode x, x.prev != null. (4) For any DListNode x, if x.next == y, then y.prev == x. (5) For any DListNode x, if x.prev == y, then y.next == x. (6) A DList's "size" variable is the number of DListNodes, NOT COUNTING the sentinel (denoted by "head"), that can be accessed from the sentinel by a sequence of "next" references. An empty DList is represented by having the sentinel's prev and next fields point to itself. Here's an example of a method that removes the last item from a DList. public void removeBack() { if (head.prev != head) { // Do nothing if the DList is empty. head.prev = head.prev.prev; // Sentinel now points to second-last item. head.prev.next = head; // Second-last item now points to sentinel. size--; } }