CSCI 1112 Data Structures & Algorithms I Mona Diab Lecture 1 - - PowerPoint PPT Presentation

CSCI 1112 Data Structures & Algorithms I

Mona Diab Lecture 1

RoadMap

• Class Logistics
• Brief Introduction
• Survey

Class Logistics

• Instructor: Mona Diab
• Lab TA: Tianyi Song
• Grading TA: Hanan AlDarmaki
• Class: TH 2:20-3:35pm
• Lab: M 9:00-10:50am, W 11:10-1:00pm
• URL for class
• http://www.seas.gwu.edu/~mtdiab/Courses/

CS1112/index.htm

• THIS IS YOUR KEY RESOURCE … it will be

updated frequently, make sure to check it often

Course Logistics

• Textbook (not required but recommended)

– Data Structures & Other Objects Using Java, 2012, 4th Edition, Michael Main

• All course material for reading and

assignments is provided from the course website

• Supplementary material for reading will be

pointed out from both the course website and the book ahead of class

• You MUST read the material before class

Course Mechanics

• Class and Lab attendance is mandatory
• Occasionally, we will have in-class

assignments that need to be worked on in class

• Typically, I would be lecturing for half the

class and then we do hands on application

• f the different concepts learned and

possibly an in-class exercise

• The in-class assignments are due right

after class within 1 hr.

Grading

30% in class assignments (15%), attendance (5%), participation (5%), lab attendance and participation (5%) 40% HW (25%) and Lab exercises (15%) 30% Midterm (15%), final (15%)

Assignment Submission

• Assignments will be submitted as tarred

zipped encrypted files either via BB or on the unix SEAS “shell.seas.gwu.edu” server

• In-class assignment submissions can’t be

late

• HW can be late but 20% of the grade will

be shaved off for every 24hrs after due date (calendar days)

• We determine submission by the file date
• n the crypt file.

Important Assignment Considerations

• Pseudocode for the algorithm
• Proper indentation and coding style
• Sufficient documentation with comments

and readable/expressive variable names

• Correctness
• Robustness
• Efficiency
• Modularity

Other important considerations

• Email policy

– Do not send debugging questions over email, always check with TAs first – I will be checking emails at a slower pace than the class – Questions about course material should happen in my office hours, labs, over email and

• n Piazza (be sure to log onto the class)
• Academic integrity

– I expect the work to be yours alone (in class assignments can be worked on in pairs)

What is this course about

• Data structures: arrays, lists, queues,

stacks, trees.

• Memory models of these data structures.
• Problem-solving: recursion, using data

structures.

• Software skills: harder programs, trickier

code, debugging.

• Algorithm analysis: reasoning about

program execution time.

What will we learn

• We will learn how fundamental data

structures work, how they are used, and how to build them ourselves.

• We will learn why they work, for example,

why one is faster/better than another.

• We will learn how data structures are

represented in memory.

• We will strengthen our programming skills

and learn more about Java to be able to implement data structures.

• Along the way, we will also learn about

problem-solving and recursion.

Course Outline

• Introduction to basic overall concepts
• Unidimensional & Multidimensional Arrays
• Sorting, Recursion, Objects, Sets, Lists
• Analysis of Algorithms Performance
• Stacks, Queues, Abstract Data Types

(ADT)

• Recursion (again)
• Trees & Hashtables

Objectives

• Organizing the data for processing is a

computer program is a critical step in the solution of a problem.

• Selecting the data organization strongly

affect the performance of the computer program solution

• Most programming languages offer a set
• f primitive (basic) data types and ways to

build complex data types.

Computer Programs in CS

• Use a computer to efficiently solve a

problem:

– Understand the requirements of the problem – Implementing these requirements with a computer program – Computer programs consist of the following:

• Algorithm + Data Structure(s)

Data Structure

• A means of storing a collection of data
• It is the requirement of the elements of

the structure, the relationships between them, and the operations that may be performed on them

• The choice of a data structure can affect

the performance of a solution: slow vs. fast

Data Structure Taxonomy

• Linear and non-linear data structures
• Homogenous and non-homogenous data

structures

• Primitive and non-primitive data

structures

Linear and Non-linear Data Structures

• Linear Data Structures

– Data elements are arranged in a linear sequence

• Examples: Array, Linked List, Queue, Stack
• Non-linear Data Structures:

– Data elements are not stored in a sequence – Examples: Tree, Graph, Forest

Primitive and Non-primitive Data Structures

• Primitive Data Structures

primitive (basic) types: Integer, float

• Non-primitive Data Structures

– Composite data structures: Array, records

Homogeneous and Non- homogeneous Data Structures

• Homogenous Data Structures:

– Data elements are of the same type

• Example: Array
• Non-homogenous Data Structures:

– Data elements are of different types

• Examples: Records or Structure

Basic Definitions

A data type is a set of values and a set of

• perations defined on those values

– Values

• For example, the values of the primitive data type

int are integers between -231 and 231

– Operations

• The operations of int are the basic arithmetic and

logical operations.

Basic Data Types

• Byte: an 8-bit signed twos complement integer
• Boolean: True or False
• Short: a 16-bit signed twos complement
• Int: a 32-bit signed twos complement
• Long: a 64-bit signed twos complement
• Float: a single-precision 32-bit IEEE 754 floating

point

• Double: a double-precision 64-bit IEEE 754

floating point

• Char: The char data type is a single 16-bit Unicode
• character. It has a minimum value of '\u0000' (or

0) and a maximum value of '\uffff' (or 65,535 inclusive)

Algorithm

• To implement the business logic of the

problem

• It is a concise list of steps to solve a

problem

• There are more than one algorithm for a

problem

• How to choose an efficient algorithm
• How to choose the best algorithm
• What are criteria for performance

analysis

How to develop applications?

• Preconditions and Postconditions

– Increase the reliability of your application. – They are a method of specifying what a function accomplishes. – Frequently a programmer must communicate precisely what a function accomplishes, without any indication of how the function does its work.

Precondition Statement

• Indicates what must be true before the

function is called.

• The programmer who calls the function is

responsible for ensuring that the precondition is valid when the function is called.

Postcondition Statement

• Indicates what will be true when the

function finishes its work.

• The programmer who writes the function

counts on the precondition being valid, and ensures that the postcondition becomes true at the function’s end.

Example

• bool is_vowel( char letter )

//Precondition: letter is an uppercase or lowercase letter (in the range 'A' ... 'Z' or 'a' ... 'z') . //Postcondition: The value returned by the function is true if Letter is a vowel; otherwise the value returned by the function is false. What values will be returned by these function calls? is_vowel( 'A' ); is_vowel(' Z' ); is_vowel( '?' );

Testing & Debugging

• Is Compile-Run-Generate-Outputs enough?

– Required Testing!!! – Which test data?

• You must know which output a correct program should

produce for each test data.

• The test inputs should include those inputs that are most

likely to cause errors.

• Tips for Test data:

– Boundary values – Fully Exercising Code: make sure each line of your code is executed. – Values of variables: negative, zero, positive – Expecting numbers or strings, etc.

Java

• Programming in Java is largely based on

doing so with data types known as reference types.

• Java has eight primitive data types:

boolean, byte, char, double, float, int, long, and short.

Basic Concepts in Java

//Comment1 public class SyntaxExample1 { //Comment2

public static void main (String[] argv) { //Comment 3 } }

Basic concepts in Java

public class HelloWorld {

public static void main (String[] argv) {

System.out.println ("Hello World!"); }}

• The main syntactic elements are:

– Java reserved words such as: public, class, static, void. – Method (procedure or function) names: main, println. – Names of variables and objects, such as System, String, HelloWorld, argv and out. – Delimiters for the class, and the method main. – An end-of-statement symbol, the semicolon. – Parentheses for enclosing method parameters (arguments). – A string literal, Hello World!. – Array brackets []

Survey

• Name
• Level
• Major
• Have you taken CSCI 1111?
• Have you coded in Java before? (Yes/No)
• What other CS languages are you familiar

with?

• Are you familiar with unix?
• Are you familiar with Eclipse?