Category:Computer Science

Computer Science Outline

The following list is directly from Wikipedia.

Mathematical foundations

• Mathematical logic - Boolean logic and other ways of modeling logical queries; the uses and limitations of formal proof methods
• Number theory - Theory of proofs and heuristics for finding proofs in the simple domain of integers. Used in cryptography as well as a test domain in artificial intelligence.
• Graph theory - Foundations for data structures and searching algorithms.
• Game theory - useful in artificial intelligence and cybernetics.

Theory of computation

• Automata theory - Different logical structures for solving problems.
• Computability theory - What is calculable with the current models of computers. Proofs developed by Alan Turing and others provide insight into the possibilities of what may be computed and what may not.
• Computational complexity theory - Fundamental bounds (especially time and storage space) on classes of computations.
• Quantum computing theory - Explores computational models involving quantum superposition of bits.

Algorithms and data structures

• Algorithms - Sequential and parallel computational procedures for solving a wide range of problems.
• Data structures - The organization and manipulation of data.

Programming languages and compilers

• Compiler theory - Theory of compiler design, based on Automata theory.
• Programing language pragmatics - Taxonomy of programming languages, their strength and weaknesses. Various programming paradigms, such as object-oriented programming.
• Programming language theory
  • Formal semantics - rigorous mathematical study of the meaning of programs.
  • Type theory - Formal analysis of the types of data, and the use of these types to understand properties of programs — especially program safety.

Concurrent, parallel, and distributed systems

• Concurrency - The theory and practice of simultaneous computation; data safety in any multitasking or multithreaded environment.
• Parallel computing - Computing using multiple concurrent threads of execution, devising algorithms for solving problems on multiple processors to achieve maximal speed-up compared to sequential execution.
• Distributed computing - Computing using multiple computing devices over a network to accomplish a common objective or task and there by reducing the latency involved in single processor contributions for any task.

Software engineering

• Formal methods - Mathematical approaches for describing and reasoning about software designs.
• Software engineering - The principles and practice of designing, developing, and testing programs, as well as proper engineering practices.
• Reverse engineering - The application of the scientific method to the understanding of arbitrary existing software
• Algorithm design - Using ideas from algorithm theory to creatively design solutions to real tasks
• Programming - The practice of using a programming language to implement algorithms

Computer architecture

• Computer architecture - The design, organization, optimization and verification of a computer system, mostly about CPUs and Memory subsystem (and the bus connecting them).
• Operating systems - Systems for managing computer programs and providing the basis of a usable system.

Communications and Security

• Networking - Algorithms and protocols for reliably communicating data across different shared or dedicated media, often including error correction.
• Computer security - Practical aspects of securing computer systems and computer networks.
• Cryptography - Applies results from complexity, probability and number theory to invent and break codes, and analyze the security of cryptographic protocols.

Databases

• Relational databases - the set theoretic and algorithmic foundation of databases.
• Data mining - Study of algorithms for searching and processing information in documents and databases; closely related to information retrieval.

Artificial intelligence

• Artificial intelligence - The implementation and study of systems that exhibit an autonomous intelligence or behaviour of their own.
• Automated reasoning - Solving engines, such as used in Prolog, which produce steps to a result given a query on a fact and rule database, and automated theorem provers that aim to prove mathematical theorems with some assistance from a programmer.
• Robotics - Algorithms for controlling the behavior of robots.
• Computer vision - Algorithms for identifying three dimensional objects from a two dimensional picture.
• Machine learning - Automated creation of a set of rules and axioms based on input.

Computer graphics

• Computer graphics - Algorithms both for generating visual images synthetically, and for integrating or altering visual and spatial information sampled from the real world.
• Image processing - Determining information from an image through computation.
• Human computer interaction - The study and design of computer interfaces that people use.

Scientific computing

• Numerical analysis - Approximate numerical solution of mathematical problems such as root-finding, integration, the solution of ordinary differential equations; the approximation of special functions.
• Symbolic computation - Manipulation and solution of expressions in symbolic form, also known as Computer algebra.
• Computational physics - Numerical simulations of large non-analytic systems
• Computational chemistry - Computational modelling of theoretical chemistry in order to determine chemical structures and properties
• Bioinformatics - The use of computer science to maintain, analyse, store biological data and to assist in solving biological problems such as Protein folding, function prediction and Phylogeny.
• Computational neuroscience - Computational modelling of neurophysiology.

Available Notes

See below subcategories.