datastructures1 barb ericson georgia tech [email protected] july 2008
TRANSCRIPT
DataStructures 2
Learning Objectives
• Understand at the conceptual level– The need to group objects– Limitations of Arrays– Collections– Lists and Linked Lists– Sets and Maps– Stacks and Queues– Trees
DataStructures 3
Grouping Objects
• We often group objects – A list of items to buy at a grocery store– Your friends names and phone numbers– Your homework for each class– A record of all of your ancestors– A sorted list of people in a class
DataStructures 4
Array Limitations
• You can use arrays to store multiple objects– You need to know many items there will be
• You specify the size when you create an arrayItem[] shoppingList = new Item[10];
– What happens if the array runs out of space?• If you try to add an element passed the last valid index you
get – java.lang.ArrayIndexOutOfBoundsException
• You could create a bigger array• You would have to copy all the elements from the old array to
the new array
– What if you don’t need all the space in an array?
DataStructures 5
Collection Classes
• Java has collection classes to handle grouping objects– The classes don’t require you to know how
many objects you will need to store• The collections will grow and shrink as needed
• There are different types of collections depending on what you need– Keep the order of the objects - List– Make sure there are no duplicates – Set– Associate one object with another - Map
DataStructures 6
Collection Exercise
• Look up the Collection Interface– How do you add objects to a collection?– Is there a way to add two collections
together?– Is there a way to get an intersection of two
collections?– Is there a way to remove an object from a
collection?– How do you empty a collection?– Can you get an array from a collection?
DataStructures 7
Collections hold object references
• When you add an object to a collection– You add a reference to
the object• Not a copy of the object
– Many collections can hold references to the same object
– Variables may also reference the same object
Cheerios: ItemLettuce: Item
Ham: Item Eggs: Item
DataStructures 8
List and Set Interfaces and Classes<<interface>>
Collection
<<interface>>List
<<interface>>Set
<<interface>>SortedSetArrayList Vector LinkedList
TreeSet
HashSet
DataStructures 9
List
• We often keep ordered lists of things– “To do” list– People in a line– Parts
• A list has an order– First thing, second thing, third thing, etc.
• Lists may have duplicate items
• You can get, add, or remove an item anywhere in a list
DataStructures 10
Java Lists
• The first index is 0– The last valid index is list.size() – 1
• ArrayList is a class that implements the List interface – Using an array and allows null values in the list
• Vector is an older class that also uses an array – It is like ArrayList but it is synchronized
• LinkedList is a class that implements the List interface– Using a linked structure, not an array
DataStructures 11
Linked List - java.util.LinkedList
• A linked list has nodes that contain data and a reference to the next node
• A doubly linked list has references to previous nodes as well
Sue Mary Tasha nullhead
Sue Mary Tasha null
head tail
null
DataStructures 12
Ideas for Teaching Linked Lists
• Give random students a paper that tells them who the next and previous student is– Give one student the name of the first person
in the list
• Walk through – adding a new student to the front of the list– getting the 5th person in the list– removing the 3rd person in the list– removing the 1st person in the list
DataStructures 13
Arrays versus Linked List
• A book is like an array– The pages are ordered sequentially – It is easy to find a particular page
• A magazine article is like a linked list– Has groups of pages and– a reference to the next group of pages
• A treasure hunt is like a linked list– You start with one clue that takes you to the
location of the next clue
DataStructures 14
ArrayList versus LinkedList
• If you need to access items randomly– Use an ArrayList
• Quick to access a random location• Can be slower to add to and remove from
– If it needs to create a new array and copy old items
• If you are doing lots of adding/removing from a list– Use a LinkedList
• Quick to add to or remove from• Slow to do random access
DataStructures 15
Using Iterator
• One way to access all elements of a List is to use a for loop and increment the index from 0 to < list.size()– Use the index to get items from the list
item = itemList.get(index);
• Another approach is to use an iteratorIterator<Item> iterator = itemList.iterator();
while (iterator.hasNext())
item = iterator.next();
DataStructures 16
Iterator Exercise
• Is it better to use an iterator or an index to get all of the elements – of an ArrayList?– of a LinkedList?
• What about if you want to access every other element – of an ArrayList?– of a LinkedList?
• Which should you use if you don’t know the implementing class?
DataStructures 17
ListIterator
• Inherits from Iterator
• Adds – The ability to traverse a list in either direction– The ability to modify the list during iteration
• Add a new element before the current next element
– public void add(Object obj);
• Change the last accessed element– public void set(Object obj);
DataStructures 18
ListNode AP Class
• Has value and next fields – Can get and set the
fields
• Has a constructor that take the value and next node
• Uses the keyword null to indicate the end of the linked list
ListNode
Object value
ListNode next
public Object getValue()
public ListNode getNext()
public void setValue(Object value)
public void setNext(ListNode node)
DataStructures 19
Loop through a linked list with ListNode
• Start with a reference to the head of the list
• Each time through the loop move the reference to the next node
• Stop the loop when the reference is null– Continue while the reference is not null
ListNode node = null;
for (node = head; node != null; node = node.getNext())
DataStructures 20
Testing the Loop
• Does this work when head is null?
• Does it work when there is one node in the list?
• Does it work when there is more than one node in the list?
Sue Mary Tasha nullhead
Sue nullhead
headnull
DataStructures 21
Add to the front of a linked list
• Set the new nodes next to the node referenced by head
• Change head to point to the new node
Sue Mary Tasha nullhead
Fred Sue Mary Tasha null
Fred null
head
DataStructures 22
Stacks
• A stack holds objects with the last object put in the stack being the first one returned– Last-in-first-out structure (LIFO)
• Like a stack of cafeteria plates• Or a holder for bathroom cups• Or a Pez container
• Stacks are used to hold the list of operations that you might want to undo– When you click “Undo” the last thing you did
is undone
DataStructures 23
Teaching Stacks
• Have each student put a book on a stack of books– Then ask a student to
take off a book from the stack
• Where did people put the new books?
• Where did people take books from?
DataStructures 24
Stack Class
• Java 5.0 has a Stack Class– class java.util.Stack<E>– E push(E x)
• Add x to the top of the stack
– E pop()• Remove the top of the stack and return it
– E peek()• Return the top item on the stack
– boolean isEmpty()• Return true if the stack is empty
DataStructures 25
Queues
• A queue holds objects with the first object put in the queue the first one returned– First-in-first-out structure (FIFO)
• Like the ticket line at the movies• Or a car wash with cars moving through
• Use queues to track events and objects– A queue of requests for printing
• Handle the first one before the next one
– A queue of people in line to buy tickets for a movie
• People at the front of the queue buy tickets first
DataStructures 26
Teaching Queues
• Have some students form a line as if in line to buy tickets for a movie– Who should be waited
on first? Who would be waited on next?
– When new people come where do they enter the line?
DataStructures 27
Queue Interface• java.util.Queue has a Queue Interface• Implemented by two Classes
– java.util.LinkedList– Java.util.PriorityQueue
• New methods– boolean add(E x)
• Add to the end (tail) of the queue– E remove()
• Remove front of queue and return it– E peek()
• Return the front of the queue– boolean isEmpty()
• Return true if the queue is empty
DataStructures 28
Set
• A set does not preserve order– The order things are retrieved from a set is
not necessarily the same order they were placed in a set
• Sets do not allow duplicate elements– elementA.equals(elementB)– If you try to add an element that is equal to
another element of the set it won’t add it• And will return false
DataStructures 29
Set Classes
• HashSet– Uses equals and
hashCode to compare objects and to check for duplicates
• TreeSet– Objects must
implement Comparable and are sorted based on the results of compareTo
<<interface>>Set
<<interface>>SortedSet
TreeSet
HashSet
DataStructures 30
Maps
• Maps hold key and value pairs– Use a key to put a value into the map– Use a key to get a value from a map– There can’t be duplicate keys– There can be duplicate values
• A value can be associated with different keys
• Used to look up associated data– Like look up a customer record from a phone
number– Or like safety deposit boxes
DataStructures 31
Map Interface
• Get the number of keys in the mappublic int size();
• Put a value in the map for the given key– Returns the old object stored for this key
public Object put(Object key, Object value);
• Get a value from the map for the given keypublic Object get(Object key);
• Check if the key is used in the mappublic boolean containsKey(Object key);
• Get a set of the keys used in the mappublic Set keySet();
DataStructures 32
Map Interfaces and Classes
<<interface>>Map
<<interface>>SortedMap
TreeMap
HashMap Hashtable
DataStructures 33
Map Classes
• HashMap– Stores keys and values without regards to
order entered – Allows null values and a null key
• Hashtable– Older class like HashMap – Synchronized
• TreeMap– Holds keys in sorted order
DataStructures 34
Hashing
• HashMap and Hashtable use hashing on the key to find the location where the value is stored– Using the hashCode() method inherited from
Object– This method is overridden for String– You should override this method in your
classes
• Maps the key to an index in an array
DataStructures 35
Hashing Procedure
• When you put a value in a HashMap for a key– First the hashCode method is called on the
key object– This returns an int value which is mapped
from 0 to the array length – 1• Often by using remainder (%)
– There may be a value at that index from a different key
• This is called a collision
DataStructures 36
Handling Collisions
• The array is often an array of lists– A bucket that holds more than one hash node– A good hashCode() method should result in
few collisions and small lists
• When more than one key has the same index– The hash node is added to the list
• When you look for a value based on a key– If it maps to an index with a list
• It looks for the key using equals
DataStructures 37
hashCode() Method
• The goal is to get a good spread of int results
• Use some combination of fields – Like the hashCode for some String fields
added to some prime number times some other field
• Different keys can result in the same hashCode() result
• The same key object must give the same hashCode() result
DataStructures 38
Trees
• Linked lists have nodes that hold a value and a reference to the “next” node
• What if you need to track more than one “next” node?– Like you want to record your ancestors
• You can use a tree– Each tree node has a value (a person)– And a reference to the person’s mother– And a reference to the person’s father
DataStructures 39
Example Ancestor Tree
Barbara Ericson
Janet Hund Charles Ericson
Opal Peters Francis Hund Edna Wenzel Edward Ericson
root
DataStructures 40
Binary Tree
• Each tree node has at most one parent node
• Each tree node can have at most 2 children
• The top node in the tree is called the root
• Tree nodes without any children nodes are called leaves
root
leaves
Left child Right child
DataStructures 41
Tree Node AP Class
• Has fields: value, left, and right
• Can get and set all fields
• Has a constructor that takes a value, left tree node and right tree node
TreeNode
private Object value
private TreeNode left
private TreeNode right
public Object getValue()
public TreeNode getLeft()
public TreeNode getRight()
public void setValue(Object o)
public void setLeft(TreeNode n)
public void setRight(TreeNode n)
DataStructures 42
Trees are Recursive
• Each tree node is the root of a sub-tree of the original tree
• This allows the use of recursion– A method invokes itself
• On a subset of the original problem• Like a subtree
– There has to be an end condition• That stops the recursion• No more subtrees
DataStructures 43
Get the Number of Nodes in a Tree
• If the root is null – The number of nodes is 0
• If the root isn’t null– Add one to the count– Add to the count the number of nodes in the
left subtree– Add to the count the number of nodes in the
right subtree
DataStructures 44
Get the Number of Nodes Method
• Some books use a class (static) method to count the number of nodes– And pass in the current node
public static int getNumNodes(TreeNode node)
{
if (node == null)
return 0;
else
return 1 + getNumNodes(node.getLeft()) + getNumNodes(node.getRight());
}
DataStructures 45
What is wrong with this?
• Static methods are used when there is no current object – Or for general methods
• In this case there is a current tree node – And the method does operate on it– It is explicitly passed to the method
• So this should be an object method– And the current object should be implicitly
passed
DataStructures 46
Modified Get Number of Nodes public int getNumNodes() { int count = 0; // increment count count = count + 1; // add to the count the number of nodes in the left subtree if (left != null) count = count + left.getNumNodes(); // add the to count the number of nodes in the right subtree if (right != null) count = count + right.getNumNodes(); return count; }
DataStructures 47
Tree class getNumNodes()
public int getNumNodes() { int count = 0; // the default is no nodes // if the root isn't null get the number of nodes if (root != null) count = root.getNumNodes(); return count; }
DataStructures 48
Tree Traversals• In-order traversal (left-data-right)
– Do the recursive call on the left subtree– Do something with the value at the node– Do the recursive call on the right subtree
• Pre-order traversal (data-left-right)– Do something with the value at the node– Do the recursive call on the left subtree– Do the recursive call on the right subtree
• Post-order traversal (left-right-data)– Do the recursive call on the left subtree– Do the recursive call on the right subtree– Do something with the value at the node
DataStructures 49
Tree Traversals
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13 11
18 7 8
DataStructures 50
Binary Search Trees (BSTs)
• A binary tree where the value at each node – is greater than the
values in all of the nodes in the left subtree
– and less than the values in all of the nodes in the right subtree
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21 38
6 23
26
44
DataStructures 51
Binary Search Tree
• Orders values– Usually using the Comparable Interface
• Allows for quick search – For a “well filled” tree O(log n)– And quick insertion and deletion of nodes
• An in-order traversal of a BST will give values in ascending order
• Used by TreeSet and TreeMap
DataStructures 52
Priority Queue
• Used to store items with various priorities– Like printer requests– Or airplanes waiting to land
• Can hold several items with the same priority
• Can item an object to the queue
• Can get the item with the highest priority– Often considered to be the “minimum” item
DataStructures 53
PriorityQueue Class
• class java.util.PriorityQueue<E>• boolean add(E x)
– Add the passed item to the queue
• E remove()– Remove top of the queue and return it
• E peek()– Return the top item on the queue
• boolean isEmpty()– Return true if the queue is empty
DataStructures 54
Heaps
• A heap is a complete binary tree– Each level other than the
last one is full of nodes– The last level must have all
missing nodes grouped to the right
• The value at each node is less than the values– In both the left and right
subtrees
• The minimum value is at the root
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8 16
12 23
13
2344
DataStructures 55
Adding a Node to a Heap
• Add it to the first missing child reference
• Then move node values as required to satisfy the requirement that the each node’s value is less than the values in the left and right subtree– Called Heapify
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8 16
6
3
8 16
6
8
3
6 16
DataStructures 56
Data Structures Exercise
• What data structure would you use to hold a known number of students in an order?
• What data structure would you use to store your friends names and cell phone numbers?
• What data structure would you use to store orders in a fast-food restaurant?
• What data structure would you use to store recent commands to allow undo?
• What data structure would you use to store a sorted list of teachers?
DataStructures 57
Summary• Collection classes hold groups of objects
– Collections can grow and shrink• Lists hold objects in order and allow duplicate
objects– Linked lists have nodes that hold a value and a
reference to the next node• Doubly linked list nodes also hold a reference to the previous
node
• Sets hold objects without preserving order and do not allow duplicate objects in the set
• Maps associate a key object with a value object• Trees have nodes that hold values and
references to children nodes