LECTURE 41:COURSE REVIEW

CSC 212 – Data Structures

Fri., Dec. 14th 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 By itself, class only used for static fields &

methods Objects are instances of a class

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

Methods declared abstract cannot have body IOU for subclasses which will eventually

define it abstract methods only in abstract

classes Cannot instantiate an abstract class But could still have fields & (non-abstract)

methods abstract methods declared by

interfaces Interfaces cannot declare fields 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 used for relationships Both imply there exists an IS-A relationship

public class Student extends Person {…}

public class Cat extends Mammal { … }

public class AQ<E> implements Queue<E>{…}

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 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 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 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 an exception when an error detected Exceptions are objects - need an instance to throw

try executing code & catch errors to handle try only when you will catch 1 or more exceptions

Do not need to catch every exception If it is never caught, program will crash Not a bad thing – had an unfixable error!

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

Access data with Stack in LIFO order Last In-First Out is totally unfair (unless

always late) Data accessed in Queue using FIFO

order First In-First Out ensures early bird gets

the worm

Ord

er r

ead

if Q

ueue

Order read if S

tack

Queue Stack Deque

Simplest ADTs

DEQUE QUEUE STACK

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> { E next() throws NoSuchElementException; boolean hasNext(); void remove() throws UnsupportedOperationException;}

public interface Iterable<E> { Iterator<E> 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 IteratorIterable<Integer> myList;Iterator<Integer> 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 3rd element in List Loop over all elements without removing

them LIST ADTs differ in how they provide

access INDEXLIST uses indices for absolution

positioning Can only use relative positions in NODELIST

All LISTS are ITERABLE

IndexList & NodeList

Sequence ADT

Combines DEQUE, INDEXLIST, & POSITIONLIST 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 DEQUE, INDEXLIST, & POSITIONLIST 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

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

DA

C E

F

B

A F

C E

Tree

root

size6

BinaryTree

Picturing Linked BinaryTree

B

CA

D

B

A C

D

BinaryTree

root

size4

Priority Queue ADT

Priority queue uses strict ordering of data Values assigned priority when added to the

queue 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

Entrys 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 Simplest implementation of a Priority

Queue Instance of Sequence used to store Entrys

Many implementations possible for Sequence But we already know how to do that, so… Assume O(1) access and ignore all other

details But how to store Entrys in the Sequence? Order Entrys by priority within the Sequence

-OR- Sequence unordered & searched when

needed

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

2

95

67

Hints for Studying

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

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

Do NOT bother with

memorizationBe ready to lookup &use information quickly

Final Exam Schedule

Lab Mastery Exam is:Tues., Dec. 11th from 3:45 – 4:45PM in SH1008

Final Exam is: Fri., Dec. 14th from 2:45 – 4:45PM in SH1028