Upcoming SlideShare
×

# Beekman5 std ppt_13

869 views

Published on

Published in: Technology
0 Likes
Statistics
Notes
• Full Name
Comment goes here.

Are you sure you want to Yes No
• Be the first to comment

• Be the first to like this

Views
Total views
869
On SlideShare
0
From Embeds
0
Number of Embeds
3
Actions
Shares
0
5
0
Likes
0
Embeds 0
No embeds

No notes for slide

### Beekman5 std ppt_13

1. 1. Chapter 13 Systems Design & Development
2. 2. Topics <ul><li>How People Make Programs </li></ul><ul><li>From Idea to Algorithm </li></ul><ul><li>From Algorithm to Program </li></ul><ul><li>Programming Languages and Methodologies </li></ul><ul><li>System Analysis and the System Life Cycle </li></ul><ul><li>The State of Software </li></ul>
3. 3. How People Make Programs <ul><li>Programming is a specialized form of problem solving and involves: </li></ul><ul><ul><li>Defining the problem </li></ul></ul><ul><ul><li>Devising, refining, and testing the algorithm </li></ul></ul><ul><ul><li>Writing the program </li></ul></ul><ul><ul><li>Testing and debugging the program </li></ul></ul>
4. 4. From Idea to Algorithm <ul><li>Start with a statement of the problem: </li></ul>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.
5. 5. From Idea to Algorithm: Stepwise Refinement <ul><li>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. </li></ul>Begin Game Repeat Return until Number is Guessed End Game
6. 6. From Idea to Algorithm: Step Refinement <ul><li>The next refinement fills in a few details for each part. </li></ul><ul><li>Begin Game </li></ul><ul><li>Display instructions </li></ul><ul><li>Pick a number between 1 and 100 </li></ul>2. Repeat Turn Until Number is Guessed Input guess from user Respond to guess End Repeat <ul><li>End Game </li></ul><ul><li>Display end message </li></ul>
7. 7. From Idea to Algorithm: Stepwise Refinement <ul><li>Fill in the crucial details. </li></ul><ul><ul><li>If guess = number, then say so and quit; </li></ul></ul><ul><ul><li>if guess < number, then say guess is too small; </li></ul></ul><ul><ul><li>if guess> number, then say guess is too high. </li></ul></ul>
8. 8. From Idea to Algorithm: Step Refinement <ul><li>Give the computer a way of knowing when seven turns have passed. </li></ul>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. 9. From Idea to Algorithm: Control Structures <ul><li>Logical structures that control the order in which instructions are carried out </li></ul><ul><li>Three basic control structures: </li></ul><ul><ul><li>Sequence - -group of instructions followed in order from first to last </li></ul></ul><ul><ul><li>Selection - -to choose between alternative courses of action depending on certain conditions. </li></ul></ul><ul><ul><li>Repetition - -allows a group of steps to be repeated several times, usually until some condition is satisfied </li></ul></ul>
10. 10. From Idea to Algorithm: Testing <ul><li>This round of testing is designed to check the logic of the algorithm </li></ul><ul><li>Test the algorithm by following the instructions using different sets of numbers. </li></ul>
11. 11. From Algorithm to Program <ul><li>A simple program contains: </li></ul><ul><ul><li>The program heading </li></ul></ul><ul><ul><li>The declarations and definition </li></ul></ul><ul><ul><li>The body </li></ul></ul>
12. 12. Into the Computer <ul><li>A text editor is used to enter and save the program. </li></ul><ul><li>Use either a translator or compiler to translate the program into machine language. </li></ul>
13. 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. 14. Compiler A compiler translates an entire high-level program to machine language before executing the program.
15. 15. Programming Languages & Methodologies <ul><li>Machine language is the native language of a computer. </li></ul><ul><ul><li>Instructions for the four basic arithmetic operations, for comparing pairs of numbers, for repeating instructions, and so on all binary </li></ul></ul><ul><ul><li>Instructions, memory locations, numbers, and characters are all represented by strings of zeros and ones </li></ul></ul>
16. 16. Programming Languages & Methodologies An assembler translates each statement of assembly language into the corresponding machine-language statement.
17. 17. High Level Languages <ul><li>High level languages fall somewhere between natural human languages and precise machine languages </li></ul><ul><li>Examples: C++, Java, Basic, FORTRAN, COBOL </li></ul><ul><li>They are easier to write, debug and are transportable between machines. </li></ul>
18. 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. 19. Unstructured Programming <ul><li>An unstructured program is like a huge, complicated machine that can’t be easily broken down into sections. </li></ul><ul><li>Any modification would require the entire machine to be disassembled. </li></ul>
20. 20. Structured Programming <ul><ul><li>problems can be isolated to individual modules </li></ul></ul><ul><ul><li>the input and output of each module in the assembly line are easier to understand </li></ul></ul><ul><li>Structured programs are easier to understand and modify because: </li></ul>
21. 21. Object-Oriented Programming <ul><li>In object-oriented programming a program is not just a collection of step-by-step instructions or procedures; it’s a collection of objects. </li></ul><ul><li>Objects contain both data and instructions and can send and receive messages. </li></ul>
22. 22. The Three Faces of Basic <ul><li>Early BASIC - The program with numbered lines. Statements are executed in numerical order unless control is transferred to another statement with a GoTo statement. </li></ul><ul><li>2. Structured BASIC - The modular program with many structured programming features. The main program has been reduced to a handful of statements at the top of the listing. These statements display the overall logic of the program. As it is running, the main program uses Call statements to transfer control to each subprogram. </li></ul><ul><li>3. Visual BASIC - A modern programming environment that includes many of the ideas and tools of object-oriented programming. </li></ul>
23. 23. Object Oriented Programming <ul><li>With OOP technology, programmers can build programs from prefabricated objects in the same way builders construct houses from prefabricated walls. </li></ul><ul><li>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. </li></ul>
24. 24. Visual Programming <ul><li>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. </li></ul><ul><li>Apple’s HyperCard was probably the first popular example of a visual programming environment. </li></ul><ul><li>Today Microsoft’s Visual Basic is widely used by professionals and hobbyists alike because of its visual approach to programming. </li></ul>
25. 25. Languages for Users <ul><li>User-oriented macro languages or scripting languages that allow users to create programs, called macros, that automate repetitive tasks </li></ul><ul><li>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 </li></ul>
26. 26. Component Software <ul><li>Construct small custom applications from software components </li></ul><ul><li>Customizability is possible only if applications are programmed to allow it. More and more software programs, including operating systems, are designed with extensibility in mind. </li></ul>
27. 27. Programming for the Web <ul><ul><li>HTML </li></ul></ul><ul><ul><li>JavaScript </li></ul></ul><ul><ul><li>Java </li></ul></ul><ul><ul><li>Perl </li></ul></ul><ul><ul><li>XML </li></ul></ul>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:
28. 28. The Future of Programming <ul><li>Programming languages will continue to evolve in the direction of natural languages like English. </li></ul><ul><li>The line between programmer and user is likely to grow hazy. </li></ul><ul><li>Computers will play an ever-increasing role in programming themselves </li></ul>
29. 30. 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
30. 31. The Systems Development Life Cycle Investigation <ul><li>Define the problem: </li></ul><ul><li>identify the information needs of the organization </li></ul><ul><li>examine the current system </li></ul><ul><li>determine how well it meets the needs of the organization </li></ul><ul><li>study the feasibility of changing or replacing the current </li></ul><ul><li>system </li></ul>
31. 32. The Systems Development Life Cycle Analysis <ul><li>During the analysis phase the systems analyst : </li></ul><ul><li>gathers documents </li></ul><ul><li>interviews users of the current system </li></ul><ul><li>observes the system in action </li></ul><ul><li>generally gathers and analyzes data to understand </li></ul><ul><li>the current system and identify new requirements </li></ul>
32. 33. 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. Design 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.
33. 34. 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. Development Testing Documenting Scheduling Programming Purchasing
34. 35. The Systems Development Life Cycle Implementation <ul><li>Direct cutover approach </li></ul><ul><li>Parallel systems approach </li></ul><ul><li>Phase-in approach </li></ul><ul><li>Pilot approach </li></ul>
35. 36. The Systems Development Life Cycle Maintenance The maintenance phase involves monitoring, evaluating, repairing, and enhancing the system throughout the lifetime of the system.
36. 37. 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. .
37. 38. The Science of Computing <ul><li>Many computer scientists prefer to call the field computing science because it focuses on the process of computing rather than on computer hardware. </li></ul><ul><li>Computer science includes a number of focus areas: </li></ul><ul><ul><li>Computer theory </li></ul></ul><ul><ul><li>Algorithms </li></ul></ul><ul><ul><li>Data structures </li></ul></ul><ul><ul><li>Programming concepts and languages </li></ul></ul><ul><ul><li>Computer architecture </li></ul></ul><ul><ul><li>Management information systems </li></ul></ul><ul><ul><li>Software engineering </li></ul></ul>
38. 39. The State of Software: Software Problems <ul><li>Software errors are difficult to locate and more difficult to remove. </li></ul><ul><ul><li>Errors of omission </li></ul></ul><ul><ul><li>Syntax errors </li></ul></ul><ul><ul><li>Logic errors </li></ul></ul><ul><ul><li>Clerical errors </li></ul></ul><ul><ul><li>Capacity errors </li></ul></ul><ul><ul><li>Judgment errors </li></ul></ul>
39. 40. The State of Software: Software Solutions <ul><li>Programming techniques </li></ul><ul><li>Programming environments </li></ul><ul><li>Program verification </li></ul><ul><li>Clean-room programming </li></ul><ul><li>Human management </li></ul>