Chapter 1.

The Phases of Software

Development

Data Structure 2

Chapter outline

Objectives Use Javadoc to write a method’s complete specification Recognize quadratic, linear, and logarithmic runtime be

havior in sample algorithm Create and recognize test data that is appropriate for a

problem Contents

Specification, Design, Implementation Running Time Analysis Testing and Debugging

Data Structure 3

Data structure is

Collection of data, generally organized so that items can be stored and retrieved by some fixed techniques

Data Structure 4

The Phase of Software Development Problem analysis understand the problem

Requirements definition specify what program will do

High- and low-level design how it meets requirements

Implementation of design code it

Testing and verification detect errors, show correct

Delivery turn over to customer

Operation use the program

Maintenance change the program

Obsolescence

Data Structure 5

An Algorithm is

A procedure or sequence of instructions for solving a problem

Expressed in many different ways In English, in a particular programming

language In a pseudo code

Data Structure 6

Design Technique

Decomposing the problem Break down a task into a few subtask Then decompose each subtask into smaller subtasks Each subtask is implemented as a separate Java meth

od (“function” or “Procedures”) Produces a good final program

What makes a good decomposition? Subtasks should help you produce short pseudocode

What are good subtasks? Potential for code reuse Possibility of future changes

Data Structure 7

How to write a specification

Tells what the method does, but not how it does its work

Information hiding : “knows only as much as you need, but no more…”

Procedural abstraction Method specification Includes

Short introduction Parameter description Precondition Returns condition or postcondition “Throws” List

Data Structure 8

How to write a specification

Example)

celsiusToFahrenheit public static double celsiusToFahrenheit(double c) Convert a temperature from Celsius degrees to Fahrenheit degrees

Parameters: c – a temparature in Celsius degrees Preconditon: c >= -273.16 Returns: the temperature c converted to Fahrenheit degrees Throws: IllegalArgumentException Indicates that c is less than the smallest Celsius temperature

(-273.16)

Data Structure 9

Precondition and Postcondition

Precondition Is a statement giving the condition that is

supposed to be true when a method is called

Postcondition Is a statement describing what will be true when

a method call is completed. If the method is correct and the precondition

was true when the method was called, then the method will complete

Data Structure 10

Precondition and Postcondition

Example

// Precondition: x >= 0.// Postcondition: The square root of x has// been written to the standard output.

public void writeSqrt( double x)

...

The precondition and postcondition appear as commentThe precondition and postcondition appear as comments in your program.s in your program.They are usually placed before the method implementatiThey are usually placed before the method implementation.on.

Data Structure 11

Precondition and Postcondition

Another Example

// Precondition: letter is an uppercase or// lowercase letter (in the range 'A' ... 'Z' or 'a' // ... ‘z') .// Postcondition: The value returned by the method is // true if letter is a vowel; otherwise the value// returned by the method is false. public boolean isVowel( char letter )

...

“Always make sure the precondition is valid . . .. . . so the postcondition becomes true at the method end.”

Data Structure 12

Exceptions

Exceptions Messages for serious programming errors

Throwing an exception The act of halting work and passing a message to the calli

ng program

Public static double celToFah(double c)

{

final double MINIMUM_CELSIUS = -273.16 ;

if( c < MINIMUM_CELSIUS)

throw new IllegalArgumentException(“Argument” + c + “is too small.”);

return (9.0/5.0) * c + 32;

}

Data Structure 13

Exception

Exception handling

throw new ( “ “)

This is the type of exception we are throwing. All of our exceptionswill be the type IllegalArgumentException

This is an error message that willbe passed as part of the exceptionThe message should describe the error well

Data Structure 14

Running Time Analysis

Time analysis Consists of reasoning about an algorithm’s

speed Does the algorithm work fast enough for my

needs? How much longer does the algorithm take when

the input gets larger?

The Stair-Counting Problem You and Judy at the top of the Eiffel Tower “How many steps there are to the bottom?”

There are Three Techniques for this problem !

Data Structure 15

Three techniques for the stair-counting problem

Technique 1: Walk Down and keep a Tally Each time you take a step down, mark on the

sheet of paper

Technique 2: Walk Down, but Let Judy keep the Tally

Each time you take a step down, Judy mark on the sheet of paper (step down, lay a hat, step up)

Technique 3: Jervis to the Rescue Use the Jervis’s sign “There are 2689 steps”Actual elapsed time and vary depending on other factorsSo, Count certain operations

Data Structure 16

Analysis for the stair-counting problem Certain operations for analysis

Walk up or down : one operation Mark on the paper : one operation

Total operations of three techniques Technique 1: 3 * 2689 Technique 2: downward steps = (1 + 2 + … +

2689) upward steps = (1 + 2 + … +

2689) marks made = 2689 7,236,099 Technique 3: 4

Data Structure 17

Time analysis

Similar to the analysis of the stair-counting techniques

Counts the number of operations Depends on the program’s input

The time expressions for three techniques Technique 1 : 3n Technique 2 : n2 + 2n Technique 3 : log10n + 1

Data Structure 18

Big-O Notation

Quadratic Time If the largest term is no more than a constant times n2, the algorit

hm is “big-O of n2, O(n2) Doubling the input size makes the number of operations increase f

our fold

Linear Time If the largest term is a constant times n, the algorithm is “big-O of

n, O(n) Doubling the input size makes the number of operations increase t

wo fold

Logarithmic Time If the largest term is a constant times a logarithm of n, the algorith

m is “big-O of the logarithm of n, O(logn)

Data Structure 19

Big-O Notation

The Big-O notation of Three techniques Technique 1 : O(n) Technique 2 : O(n2) Technique 3: O(logn)

Order of the algorithm Big-O analysis loses some information about

relative times

Data Structure 20

Time analysis of java methods

public static boolean search(double[] data, double target)

{

int i;

for ( i=0; i<data.length; i++ )

{

if(data[i] == target)

return true;

}

return false;

}

Analysis parts When the for-loop starts Execute the body of loop After the loop finishes

Analysis results Total operations : Kn + 3 O(n)

Worst-case analysis Average-case analysis best-case analysis

Data Structure 21

Testing and Debugging

Program testing Occurs when run a program and observe its

behavior How the program works for that particular input How long the program takes to complete

Properties of Good test data Must know output of each test input Test inputs that are most likely to cause errors

Boundary Values “One step away from different behavior” Example) 0, 1 & -1

Data Structure 22

Testing and Debugging

Fully Exercising code Each line of code is executed at least once Profiler

Help fully exercise code Indicates how many times each method was

called

Using a Debugger Track down the reason why a test case is failing

Data Structure 23

Testing and Debugging

Assert statements Is boolean expressions that can be checked for validity

while a program is running

assert : “ “;

This is boolean expression that we want to make sure is true at this point in the program

This is an error message that will Be generated if the boolean expression is false

Data Structure 24

Testing and Debugging

Assert statementsPublic static int max0f3( int a, int b, int c )

{

int answer;

answer = a;

if ( b > answer )

answer = b;

if ( c > answer )

answer = c;

assert (answer == a)|| (answer == b)|| (answer == c)

: “max0f3 answer is not equal to one of the arguments”;

assert (answer >= a)&&(answer >= b)&&(answer >= c)

: “max0f3 answer is not equal to the largest argument”;

return answer;

}