CSC 212 – Data Structures

 Fri., Dec. 14 th from 2:45 – 4:45PM in SH1028  Plan on exam taking full 2 hours  If major problem, come talk to me ASAP  Exam covers material from entire semester  Open-book & open-note so bring what you’ve got  My handouts, solutions, & computers are not allowed  Cannot collaborate with a neighbor on the exam  Problems will be in a similar style to 2 midterms Final Exam

Classes vs. Objects  Classes are blueprints describing data type static  By itself, class only used for static fields & methods  Objects are instances of a class new  New objects created (instantiated) using new  Fields describe state of an object  Object’s behavior represented by methods

static v. Instance-based  Methods that are instance-based have this  Aliased to instance on which method called  Can directly use fields & call methods in class  No this parameter in static methods  Code directly using instance-based members illegal…  … using static fields & methods perfectly legal  As always, can use object to access its members  Call static methods via class if protection allows

Abstract Methods abstract  Methods declared abstract cannot have body  IOU for subclasses which will eventually define it  abstract abstract  abstract methods only in abstract classes abstract  Cannot instantiate an abstract class  But could still have fields & (non-abstract) methods  abstract  abstract methods declared by interfaces  Interfaces cannot declare fields  public abstract  public abstract methods only in interfaces

Interfaces  Can only declare important constant fields  public static final must be used for fields  Interface declares public abstract methods  Methods must be defined by classes implementing it  But method’s body cannot be defined in interface

Interfaces CANNOT INSTANTIATE AN INTERFACE  Only classes can be instantiated

Inheritance  implements extends  implements & extends used for relationships  Both imply there exists an IS - A relationship public class Student extends Person {…} public class Cat extends Mammal { … } public class AQ implements Queue {…}

 All Java classes extend exactly 1 other class  All fields & methods inherited from the superclass  Within subclass, can access non-private members  Private methods inherited, but cannot be accessed  Classes can implement any number of interfaces  Must implement methods from the interface Inheritance

 Subclass can override/overload inherited methods  Instance’s  Instance’s type determines which method is called  Parameter list stays the same to override the method  Overload method by modifying parameter list Overriding & Hiding

 Subclass can override/overload inherited methods  Instance’s  Instance’s type determines which method is called  Parameter list stays the same to override the method  Overload method by modifying parameter list Overriding & Hiding

 Subclass can override/overload inherited methods  Instance’s  Instance’s type determines which method is called  Parameter list stays the same to override the method  Overload method by modifying parameter list Overriding & Hiding

Exceptions in Java  throw  throw an exception when an error detected  Exception s are objects - need an instance to throw  trycatch  try executing code & catch errors to handle  trycatch  try only when you will catch 1 or more exceptions catch  Do not need to catch every exception  If it is never caught, program will crash  Not a bad thing – had an unfixable error! throws  Exceptions listed in methods’ throws clause  Uncaught exception only need to be listed  Should list even if thrown by another method

 Concrete implementations used to hold data  Not ADTs  Arrays are easier to use & provide quicker access  Also are impossible to grow  Implementing ADTs harder due to lack of flexibility  Slower access & more complex to use linked lists  Implementing ADTs easier with increased flexibility  Can be singly, doubly, or circularly linked Arrays vs. Linked Lists

Stack vs. Queue Order read if Queue Order read if Stack

QueueStackDeque Simplest ADTs

D EQUE Q UEUE S TACK addFront() addLast() enqueue()push() getFront() getLast() front()top() removeFront() removeLast() dequeue()pop() ADT Operations

import java.util.Iterator; import java.lang.Iterable; public interface Iterator { E next() throws NoSuchElementException; boolean hasNext(); void remove() throws UnsupportedOperationException; } public interface Iterable { Iterator iterator(); } Iterators & Iterables

Iterable v. Iterator  Iterable class is/has data we want to use  Declaring it Iterable promises generic way to access  Does not do any work, but provides object doing work  While has access, Iterator (usually) separate class  Iterator instance returns values in other class/array  Always (almost) includes field with reference to data holder  Field (cursor) tracks next location in data to be returned

 Abstract work in processing with Iterator Iterable myList; Iterator it;... for (it = myList.iterator(); it.hasNext(); ) { Integer i = it.next();... }  Process Iterable objects in an even easier way... for (Integer i : myList) {... } More Iterator & Iterable

 Collection which we can access all elements  Add element before an existing one  Return the 3 rd element in List  Loop over all elements without removing them  L IST ADTs differ in how they provide access  I NDEX L IST uses indices for absolution positioning  Can only use relative positions in N ODE L IST  All L ISTS are I TERABLE IndexList & NodeList

Sequence ADT  Combines D EQUE, I NDEX L IST, & P OSITION L IST  Includes all methods defined by these interfaces  Adds 2 methods to convert between systems  Get Position at index using atIndex(i)  indexOf(pos) returns index of a Position

Sequence ADT  Combines D EQUE, I NDEX L IST, & P OSITION L IST  Includes all methods defined by these interfaces  Adds 2 methods to convert between systems  Get Position at index using atIndex(i)  indexOf(pos) returns index of a Position

Trees vs. Binary Trees  Both represent parent-child relationships  Both consist of single "root" node & its descendants  Nodes can have at most one parent  Root nodes are orphans -- do not have a parent must  All others, the non-root nodes must have parent  Children not required for any node in the tree  No limit to number of children for non-binary trees  2 children for node in binary tree is the maximum

Traversal Methods  Many traversals, differ in order nodes visited  Do parent then do each kid in pre-order traversal

Traversal Methods  Many traversals, differ in order nodes visited  Do parent then do each kid in pre-order traversal  Post-order traversal does kids before doing parents

Traversal Methods  Many traversals, differ in order nodes visited  Do parent then do each kid in pre-order traversal  Post-order traversal does kids before doing parents  Do left kid, parent, then right kid in in-order traversal

Traversal Methods  Many traversals, differ in order nodes visited  Do parent then do each kid in pre-order traversal  Post-order traversal does kids before doing parents  Do left kid, parent, then right kid in in-order traversal  Really, really, really simple to record what is done  Follow simple algorithm to see how it works

Traversal Methods  Many traversals, differ in order nodes visited  Do parent then do each kid in pre-order traversal  Post-order traversal does kids before doing parents  Do left kid, parent, then right kid in in-order traversal  Really, really, really simple to record what is done  Follow simple algorithm to see how it works  Took CSC212 before you were born & I need to trace it

Traversal Methods  Many traversals, differ in order nodes visited  Do parent then do each kid in pre-order traversal  Post-order traversal does kids before doing parents  Do left kid, parent, then right kid in in-order traversal  Really, really, really simple to record what is done  Follow simple algorithm to see how it works  Took CSC212 before you were born & I need to trace it  Pro tip: Just trace it on paper

Tree D Visualization of Tree B D A CE F B AF CE Tree root size  6 

BinaryTree   Picturing Linked BinaryTree B C A D   BACD BinaryTree root size  4

Priority Queue ADT  Priority queue uses strict ordering of data  Values assigned priority when added to the queue completely biased order  Priorities used to process in completely biased order First you get the sugar, then you get the power, then you get the women

Priority Queue ADT  PriorityQueue yet another Collection  Prioritize each datum contained in the collection  PQ is organized from lowest to highest priority  Access smallest priority only sort of like Queue  min() & removeMin() return priority & value  Implementation not defined: this is still an ADT  Remember that organization & order is theoretical only

 PriorityQueue yet another Collection  Prioritize each datum contained in the collection  PQ is organized from lowest to highest priority  Access smallest priority only sort of like Queue  min() & removeMin() return priority & value  Implementation not defined: this is still an ADT  Remember that organization & order is theoretical only Priority Queue ADT order is theoretical only

Entry s in a PriorityQueue  PriorityQueues use Entry to hold data  As with Position, implementations may differ  Entry has 2 items that define how it gets used  PQ will only use key – the priority given to the Entry  Value is important data to be processed by program

Sequence -based Priority Queue

Heaps  Binary-tree based PQ implementation  Still structured using parent-child relationship  At most 2 children & 1 parent for each node in tree  Heaps must also satisfy 2 additional properties  Parent at least as important as its children  Structure must form a complete binary tree

Hints for Studying  Will NOT require memorizing:  ADT’s methods  Node implementations  Big-Oh time proofs  (Memorizing anything)

(& be ready to look up):  You should know (& be ready to look up):  How ADT implementations work (tracing & more)  For each method what it does & what it returns  Where & why each ADT would be used  For each ADT implementations, its pros & cons  How to compute big-Oh time complexity Hints for Studying

1. What does the ADT do? Where in the real-world is this found? 2. How is the ADT used? What are the applications of this ADT? How is it used and why? 3. How do we implement the ADT? Given the implementation, why do we do it like that? What tradeoffs does this implementation make? Studying For the Exam

“Subtle” Hint

Final Exam Schedule  Lab Mastery Exam is: Tues., Dec. 11 th from 3:45 – 4:45PM in SH1008  Final Exam is: Fri., Dec. 14 th from 2:45 – 4:45PM in SH1028