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An Introduction to Programming and Object-Oriented Design Using Java. By Jaime Niño and Fred Hosch Slides by Darwin Baines and Robert Burton. Chapter 1. Introduction. This chapter discusses. Computing as a science. Analysis of large software systems.
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An Introduction to Programming and Object-Oriented Design Using Java By Jaime Niño and Fred Hosch Slides by Darwin Baines and Robert Burton
Chapter 1 Introduction
This chapter discusses • Computing as a science. • Analysis of large software systems. • Fundamental hardware and software concepts. • Basic notions necessary to survive.
What is Computer Science? • Computer science is a science of abstraction – creating the right model for a problem and devising the appropriate mechanizable technique to solve it. • A. Aho and J. Ullman • Not the “science of computers.” • Many concepts were framed and studied before the electronic computer. • To the mathematicians and logicians of the ‘20’s and ‘30’s, a computer was a person with pencil and paper.
The Science of Computing • Automated problem solving. • Automated systems that produce solutions. • Methods to develop solution strategies for these systems. • Application areas for automatic problem solving.
Foundations of computing • Fundamental mathematical and logical structures for • Understanding computing. • Analyzing and verifying the correctness of software and hardware.
Systems definitions • computer architecture: organization and structure of hardware. • operating systems: fundamental resource management software. • distributed systems:connecting computers together in order to share resources and information (networking).
Applications • There are numerous applications of computer science. • Artificial intelligence • Data base management • Computer graphics • Etc.
Methods • Design and assessment of techniques and software tools for creating automated problem solutions. • programming language: a precise, formal notation for expressing and analyzing a natural, correct, efficient program solution.
Methods (cont.) • software engineering: the study of methods for producing and evaluating software. This is the primary topic of the course.
What is a Software System? • Sometimes called a program or application. • A temporary solution to a changing problem. • 2 major attributes inherent in Software Systems: • dynamics • complexity
Dealing with complexity: Composition • composite structure: a software system composed of manageable pieces. • The smaller the component, the easier it is to build and understand. • The more parts, the more possible interactions there are between parts and the more complex the resulting structure.
Dealing with complexity: Composition (cont.) • Balance between simplicity and interaction minimization. • Example: An audio system is easy to manage because each component has a carefully specified function and the components are easily integrated i.e. The speakers are easily connected to the amplifier.
Counterexample • The function of a “Rube Goldberg” device is not obvious, modification is almost unthinkable, the parts lack an intrinsic relationship to the problem the device solves, and the complexity is high.
Dealing with complexity: Abstraction • Dealing with system components and their interactions without worrying about specific details. • Not “vague” or “imprecise.” • Limitation of view to a few properties. • Elimination of the irrelevant and amplification of the essential. • Capturing commonality between different things.
Two aspects of a system: • data: the information the program deals with. • functionality: what the program does with the data.
Systems:Data • data descriptions: the type of data to be stored; fixed for a program. • data values: actual values stored for each descriptor. Variable each time the program is run. • Example: Descriptor: Name Value:John
Systems: Functionality • computation: Performance of some sequence of goal-directed actions with a set of data values. • processor: Whatever performs the actions. • algorithm: A set of instructions describing a pattern of behavior guaranteed to achieve some goal.
Object-oriented systems • Composite, modular constructions, built using abstraction, consisting of components, and organized around the data. • model: an abstraction of a real-world problem that can be represented and manipulated with a computing system. • software system: a collection of abstractions that work together to solve problems.
Object-oriented systems (cont.) • These abstractions are called objects. • Each object has its own properties and functionality. • Reusable components are the key to the efficient production of reliable systems.
Computer system • Input/Output:communication with the outside world. • processor: performs computation using the instruction set. • memory: stores the data and algorithms the system is using, i.e. RAM. • file system: stores data and algorithms not currently being used. i.e. disks. • network: several connected computers and other devices.
Memory • Data encoding schemes: letters, digits, punctuation marks, etc. often are encoded as 8-bit sequences. • “A” might be represented as 01000001. • Memory is divided into fixed size locations, each with a unique address. • Data and instructions are accessed using their addresses and by knowing their sizes.
Software tools • operating system: fundamental hardware-resource management software. • programming language: the formal expression of data descriptions and algorithms. • text editor: the means provided for us to write and edit programs.
Software tools (cont.) • compiler: a program that translates programs written in a specific programming language into a a more machine-like language. • interpreter: software that reads and executes a machine-independent intermediate language (called “byte-code” in the case of Java).
Operating system • MS-DOS, Windows NT, Solaris, etc. • Performs functions such as verifying user names and passwords, deciding where in memory a program will be loaded, loading programs from disk, etc.
Programming languages • Java, C++, Pascal, etc. • syntax: the set of grammatical and punctuation rules for the language. • semantics: the set of rules that specify the meaning of syntactically legal constructs. • Each legal construct has exactly one meaning.
Errors in the programming process • error: a mistake made in the design, programming, or use of a system. • failure: inability of the system to perform its intended function. • Errors cause failures.
Errors in the programming process (cont.) • Computer systems fail because of • conceptual errors • data errors • hardware failures • software errors • Conceptual errors:misunderstanding of the system.
Errors in the programming process (cont.) • data errors: incorrect data. • software errors: • Syntactic errors: writing something that the programming language doesn’t understand. They are found during compilation. • Logical errors: syntactically correct but not programmed logically (“wok your dog”)
We’ve covered • Large systems are complex and change over time. • To address this, we build systems that are modular, with composite construction, and make extensive use of abstraction. • We also covered, a conceptual model of the supporting hardware system; • And a basic understanding of the purpose of fundamental software such as operating systems, compilers, and interpreters.
