Data Structures Course Review Final Exam Information
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Details about the final exam for Data Structures course, including exam format, topics covered, and important guidelines. Includes a review of key course content, such as classes vs. objects, inheritance, abstract methods, overriding, exceptions in Java, and comparisons between arrays and linked lists, as well as stacks and queues.
Data Structures Course Review Final Exam Information
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CSC 212 – Data Structures Lecture 41:Course Review
Final Exam • Tues., Dec. 10thfrom 8:00 – 10:ooAM in OM220 • 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
Classes vs. Objects • Classes are blueprints describing data type • By itself, class only used for staticfields & 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 thisparameter in staticmethods • Code directlyusing instance-based members illegal… • … using staticfields & methods perfectly legal • As always, can use object to access its members • Call staticmethods via class if protection allows
Abstract Methods • Methods declared abstractcannot have body • IOU for subclasses which will eventually define it • abstractmethods only in abstract classes • Cannot instantiate an abstract class • But could still have fields & (non-abstract) methods • abstractmethods declared by interfaces • Interfaces cannot declare fields • public abstract methods only in interfaces
Interfaces • Can only declare important constant fields • publicstaticfinalmust be used for fields • Interface declares publicabstractmethods • 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& extendsused for relationships • Both imply there exists anis-arelationship public class Student extends Person {…} public class Cat extends Mammal { … } public class AQ<E> implements Queue<E>{…}
Inheritance • 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
Overriding & Hiding • Subclass can override/overload inherited methods • Instance’stype 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’stype 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’stype determines which method is called • Parameter list stays the same to override the method • Overload method by modifying parameter list
Exceptions in Java • throw an exception when an error detected • Exceptions are objects - need an instance to throw • try executing code & catcherrors to handle • try only when you will catch 1 or more exceptions • Do not need to catchevery exception • If it is never caught, program will crash • Not a bad thing– had an unfixable error! • Exceptions listed in methods’ throwsclause • Uncaught exception only need to be listed • Should list even if thrown by another method
Arrays vs. Linked Lists • 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
Stack vs. Queue • Access data with Stackin 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 Order read if Stack Order read if Queue
Iterators & Iterables import java.util.Iterator;import java.lang.Iterable;public interface Iterator<E> {Enext() throws NoSuchElementException;booleanhasNext(); voidremove()throws UnsupportedOperationException;}public interface Iterable<E> {Iterator<E> iterator();}
Iterable v. Iterator • Iterable class is/has data we want to use • Declaring it Iterablepromises 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
More Iterator & Iterable • Abstract work in processing with Iterator Iterable<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) {...}
List Subinterfaces Defined public interface OrderedList<T> extends List<T> { public void add(T element);} public interface UnorderedList<T> extends List<T> { public void addToFront(T element); public void addToRear(Telement); public void addAfter(Telem, Ttgt); }
List Key Idea Lists are Iterable
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
D C B A Picturing LinkedBinaryTree B A C D
Priority Queue ADT • Priority queue uses strict ordering of data • Elements assigned priority when added to 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 • find() & remove()return element • Implementation not defined: this is still an ADT • Remember that organization & order is theoretical only
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 order is theoretical only
Heaps • Binary-tree based PQimplementation • 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 5 9 7 6
Hints for Studying • Will NOTrequire memorizing: • ADT’s methods • Nodeimplementations • Big-Oh time proofs • (Memorizing anything)
Hints for Studying • 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-Ohtime complexity
Studying For the Exam • What does the ADT do? • Where in the real-world is this found? • How is the ADT used? • What are the applications of this ADT? • How is it used and why? • How do we implement the ADT? • Given the implementation, why do we do it like that? • What tradeoffsdoes this implementation make?
“Subtle” Hint Do NOT bother with memorization Be ready to lookup &use information quickly
Final Exam Schedule • Final Exam is: Tues., Dec. 10thfrom 8:00 – 10:ooAM in OM220 • Lab Mastery Exam is:Fri., Dec. 13thfrom 2:45 – 3:45PM in SH1008