1.  2002 Prentice Hall Chapter 13 Systems Design & Development

2.  2002 Prentice Hall 2 Topics How People Make Programs From Idea to Algorithm From Algorithm to Program Programming Languages and Methodologies System Analysis and the System Life Cycle The State of Software

3.  2002 Prentice Hall 3 How People Make Programs Programming is a specialized form of problem solving and involves:  Understanding the Problem –Defining the problem  Designing a Solution –Devising, refining, and testing the algorithm  Implementing the Design –Writing the program  Evaluating the Solution –Testing and debugging the program

4.  2002 Prentice Hall 4 From Idea to Algorithm A school teacher needs a program to play a number-guessing game so students can learn to develop logical strategies and practice their arithmetic. In this game the computer picks a number between 1 and 100 and gives the player seven turns to guess the number. After each incorrect try the computer tells the player whether the guess is too high or too low. Start with a statement of the problem:

5.  2002 Prentice Hall 5 From Idea to Algorithm: Stepwise Refinement The first cut at the problem breaks it into three parts: a beginning, a middle, and an end. Each of these parts represents a smaller programming problem to solve. Begin Game Repeat Return until Number is Guessed End Game

6.  2002 Prentice Hall 6 From Idea to Algorithm: Step Refinement The next refinement fills in a few details for each part. 1.Begin Game Display instructions Pick a number between 1 and 100 2. Repeat Turn Until Number is Guessed Input guess from user Respond to guess End Repeat 3.End Game Display end message

7.  2002 Prentice Hall 7 From Idea to Algorithm: Stepwise Refinement Fill in the crucial details.  How to respond to guess If guess = number, then say so and quit; if guess < number, then say guess is too small; if guess> number, then say guess is too high.

8.  2002 Prentice Hall 8 From Idea to Algorithm: Step Refinement Give the computer a way of knowing when seven turns have passed. begin game display instructions pick a number between 1 and 100 set counter to 0 repeat turn until number is guessed or counter = 7 input guess from user if guess = number, then say so and quit; else if guess < number, then say guess is too small; else say guess is too big add 1 to counter end repeat end game display end message

9.  2002 Prentice Hall 9 From Idea to Algorithm: Control Structures Logical structures that control the order in which instructions are carried out Three basic control structures:  Sequence--group of instructions followed in order from first to last  Selection--to choose between alternative courses of action depending on certain conditions.  Repetition--allows a group of steps to be repeated several times, usually until some condition is satisfied

10.  2002 Prentice Hall 10 From Idea to Algorithm: Testing This round of testing is designed to check the logic of the algorithm Test the algorithm by following the instructions using different sets of numbers.

11.  2002 Prentice Hall 11 From Algorithm to Program A simple program contains:  The program heading  The declarations and definition  The body

12.  2002 Prentice Hall 12 Into the Computer A text editor is used to enter and save the program. Use either a translator or compiler to translate the program into machine language.

13.  2002 Prentice Hall 13 Translation Software Translation software, called an interpreter, translates a high-level program to a machine language one statement at a time during execution.

14.  2002 Prentice Hall 14 Compiler A compiler translates an entire high-level program to machine language before executing the program.

15.  2002 Prentice Hall 15 Programming Languages & Methodologies Machine language is the native language of a computer.  Instructions for the four basic arithmetic operations, for comparing pairs of numbers, for repeating instructions, and so on all binary  Instructions, memory locations, numbers, and characters are all represented by strings of zeros and ones

16.  2002 Prentice Hall 16 Programming Languages & Methodologies An assembler translates each statement of assembly language into the corresponding machine-language statement.

17.  2002 Prentice Hall 17 High Level Languages High level languages fall somewhere between natural human languages and precise machine languages Examples: C++, Java, Basic, FORTRAN, COBOL They are easier to write, debug and are transportable between machines.

18.  2002 Prentice Hall 18 Structured Programming Structured programming is a technique to make the programming process easier and more productive. A program is well structured if: - It’s made up of logically cohesive modules - The modules are arranged in a hierarchy - It’s straightforward and readable.

19.  2002 Prentice Hall 19 Unstructured Programming An unstructured program is like a huge, complicated machine that can’t be easily broken down into sections. Any modification would require the entire machine to be disassembled.

20.  2002 Prentice Hall 20 Structured Programming  problems can be isolated to individual modules  the input and output of each module in the assembly line are easier to understand Structured programs are easier to understand and modify because:

21.  2002 Prentice Hall 21 Object-Oriented Programming In object-oriented programming a program is not just a collection of step-by-step instructions or procedures; it’s a collection of objects. Objects contain both data and instructions.

22.  2002 Prentice Hall 22 Object Oriented Programming With OOP technology, programmers can build programs from prefabricated objects in the same way builders construct houses from prefabricated walls. For example, an object that sorts addresses in alphabetical order in a mailing list database can also be used in a program that sorts hotel reservations alphabetically.

23.  2002 Prentice Hall 23 Visual Programming Visual programming tools allow programmers to create large portions of their programs by drawing pictures and pointing to on-screen objects, eliminating much of the tedious coding of traditional programming. Apple’s HyperCard was probably the first popular example of a visual programming environment. Today Microsoft’s Visual Basic is widely used by professionals and hobbyists alike because of its visual approach to programming.

24.  2002 Prentice Hall 24 Languages for Users User-oriented macro languages or scripting languages that allow users to create programs, called macros, that automate repetitive tasks Fourth-generation languages (4GL) - English-like phrases and sentences to issue instructions Nonprocedural; focus on what needs to be done, not on how to do it

25.  2002 Prentice Hall 25 Programming for the Web  HTML  JavaScript  Java  Perl  XML Programmers can, and do, use a variety of languages, including C and C++, to write Web applications. But some programming tools are particularly useful for developing Web applications:

26.  2002 Prentice Hall 26 The Future of Programming Programming languages will continue to evolve in the direction of natural languages like English. The line between programmer and user is likely to grow hazy. Computers will play an ever-increasing role in programming themselves

27.  2002 Prentice Hall 27 System Analysis and the System Life Cycle Information systems—collections of people, machines, data, and methods organized to accomplish specific functions and to solve specific problems

28.  2002 Prentice Hall 28 The Systems Development Life Cycle The graphical “waterfall” model of the SDLC shows a basic sequential flow from identifying the “right things to do” to making sure that “things are done right.” Investigation Analysis Design Development Implementation Maintenance Retirement

29.  2002 Prentice Hall 29 The Systems Development Life Cycle Investigation Define the problem: identify the information needs of the organization examine the current system determine how well it meets the needs of the organization study the feasibility of changing or replacing the current system

30.  2002 Prentice Hall 30 The Systems Development Life Cycle Analysis During the analysis phase the systems analyst : gathers documents interviews users of the current system observes the system in action generally gathers and analyzes data to understand the current system and identify new requirements

31.  2002 Prentice Hall 31 The Systems Development Life Cycle Prototyping is an interactive methodology in which the prototype is continually modified and improved until it meets the needs of the end-user. Identify requirements Develop working model of system Use Prototype Evaluate features of prototype Develop application, install prototype for evaluation by end users, begin new prototype, or abandon application. Additional changes to prototype needed. Design

32.  2002 Prentice Hall 32 The Systems Development Life Cycle The systems analyst must plan and schedule carefully activities in the development phase of the SDLC because they can overlap and occur simultaneously. Testing Documenting Scheduling Programming Purchasing Development

33.  2002 Prentice Hall 33 The Systems Development Life Cycle Implementation Direct cutover approach Parallel systems approach Phase-in approach Pilot approach

34.  2002 Prentice Hall 34 The Systems Development Life Cycle Maintenance The maintenance phase involves monitoring, evaluating, repairing, and enhancing the system throughout the lifetime of the system.

35.  2002 Prentice Hall 35 The Systems Development Life Cycle Retirement Systems are often used for many years, but at some point in the life of a system, ongoing maintenance is not enough..

36.  2002 Prentice Hall 36 The Science of Computing Many computer scientists prefer to call the field computing science because it focuses on the process of computing rather than on computer hardware. Computer science includes a number of focus areas:  Computer theory  Algorithms  Data structures  Programming concepts and languages  Computer architecture  Management information systems  Software engineering

37.  2002 Prentice Hall 37 The State of Software: Software Problems Software errors are difficult to locate and more difficult to remove.  Errors of omission  Syntax errors  Logic errors  Clerical errors  Capacity errors  Judgment errors

38.  2002 Prentice Hall 38 The State of Software: Software Solutions Programming techniques Programming environments Program verification Clean-room programming Human management

39.  2002 Prentice Hall 39