UNIT V. TEXT 1. Computer Science

A. Read what computer science is and what it studies.

Computer science, or Computing science, is the study of the theoretical foundations of information and computation and their implementation and application in computer systems.

It is a science, because given a system of interest, it performs /analyses/ and seeks general principles to explain that system.

Computer Science is a relatively young academic discipline that has matured rather quickly due to the rapidly changing technological environment.

Computer science is much more than knowing how to use the latest application package or access nodes on the Internet. Like other academic disciplines, computer science is a collection of related subfields that share a fundamental of knowledge and practice.

Here are some of the areas that lie within the broad concept of computer science.

Computer programming

To write a program means to implement algorithms using a programming language to solve a particular task. Current emphasis on object-oriented programming is an attempt to incorporate into software construction engineering principles, such as system modularization of components that have successfully reduced size and cost of hardware products. Programming in industry is generally a team activity using productivity tools and adhering to sound engineering practices.

Computer Architecture

All computer professionals should have sound knowledge of how bits of information are moved and processed in the computer. The computer architect is concerned with organizing the data paths, functional units and instruction set of the machine to maximize its performance given the constraints on the cost and typical use of the machine.

Programming Languages

The various programming languages have features such as scooping of identifier, parameter passing, recursion, and function return that can be implemented in different ways, or not at all. A language can be based upon a particular mathematical system, or be described within a mathematical framework.

Artificial Intelligence

Specialists in artificial intelligence concern themselves with one or two central projects: (1) studying the nature of intelligence by trying to simulate it computationally, or (2) building machines that can communicate with people on human terms using natural language. These machines can also function in a rapidly changing environment, using visual and other forms of information gathering and general reasoning capabilities.

Databases

An important class of applications programs deals with the storage and retrieval of information form large banks of data. Design and maintenance of databases requires a particular expertise. Different organizing principles are employed to associate selected keys and retrieve relevant records from a database.

Systems Programming

Systems programming deals with the topic of concurrently running processes and how to appropriately regulate their access to shared system resources.

Computer graphics

Algorithms both for generating visual images synthetically, and for integrating or altering visual and spatial information sampled from the real world.

Human - computer interaction

The study of making computers and computations useful, usable and universally accessible to people, including the study and design of computer interfaces through which people use computers.

Data mining

Study of algorithms for searching and processing information in documents and databases; closely related to information retrieval.

B. This exercise includes other areas of computer science that have not been mentioned in the text above. Try to match the name of a computer science subfield (1-20) with what it deals with (A-T).

1. Compilers

2. Networking

3. Computability theory

4. Automata theory

5. Concurrency

6. Parallel computing

7. Symbolic mathematics

8. Formal methods

9. Bioinformatics

10. Numerical algorithms

11. Data structures

12. Computer vision

13. Cognitive Science

14. Machine learning

15. Image processing

16. Computational neuroscience

17. Cryptography

18. Computer Audio

19. Robotics

20. Operating systems

1. Manipulation and solution of expressions in symbolic form, also known as Computer algebra.

2. Determining information from an image through computation.

3. Different logical structures for solving problems.

4. Applies results from complexity, probability and number theory to invent and break codes.

5. Computing using multiple concurrent threads of execution.

6. Computational modeling of real minds.

7. Numerical solution of mathematical problems such as root-finding, integration, the solution of ordinary differential equations and the approximation of special functions.

8. Algorithms for controlling the behavior of robots

9. Computational modeling of real brains.

10. The use of computer science to maintain, analyze, store biological data and to assist in solving biological problems such as Protein folding, function prediction and Phylogeny.

11. Algorithms and data structures for the creation, manipulation, storage, and transmission of digital audio recordings. Also important in voice recognition applications.

12. Algorithms for identifying three dimensional objects from a two dimensional picture.

13. Automated creation of a set of rules and axioms based on input.

14. What is calculable with the current models of computers.

15. The organization of and rules for the manipulation of data.

16. Mathematical approaches for describing and reasoning about software designs.

17. Algorithms and protocols for reliably communicating data across different shared or dedicated media, often including error correction.

18. Systems for managing computer programs and providing the basis of a usable system.

19. Ways of translating computer programs, usually from higher level languages to lower level ones.

20. The theory and practice of simultaneous computation; data safety in any multitasking or multithreaded environment.

Check up your answers in the supplementary section.

C. Agree or disagree with the following statements:

1. Mathematics is considered a living part of any applied aspects in computer science.

2. Computer science should be taught more pragmatically without too much pure mathematics.

3. There is not much difference between a programmer and an advanced self-educated user.

4. By integrating the concepts, theory, and practice of computer science in a challenging curriculum, students are prepared for professional employment or for further study.