Who Needs a Computer Science Degree When There’s Wikipedia?

Update1 [6/25/08]: Welcome Stumblers

Update 2 [11/20/08]: I stumbled on this GREAT list of Algorithms, highly recommended reading.

I was looking up a computer science term on Wikipedia the other week and as is wont to happen, one thing led to another and I was about 5 or 6 articles deep on a trail of discovery and research to build up my knowledge.

As I realized I was randomizing myself and getting way off the original track, I decided to start assembling the links in one location for my own reference if not some other geek without the funds for their own degree.

Yes, there’s much more that I don’t have below, I wound up throttling back quite a bit after a while to leave it as is…for now.

History:

• History of computer science
• difference engine
• Wilhelm Schickard
• Ada Lovelace
• Charles Babbage
• Edsger Dijkstra
• Grace Hopper
• Kurt Gödel
• Alan Turing
• Dartmouth Time-Sharing System
• IBM System/370

Extra Credit:

• Animated Sorting Algorithm Demos

Languages:

• assembly languages
• structured programming
• procedural language
• Fortran
• BASIC
• Python
• Perl
• Java
• C#
• C
• C++
• Lisp programming language
• Pascal
• COBOL
• PHP
• Ruby
• ALGOL 68 (obscure)
• Simula 67 (obscure)

Computer Science Fields:

• Theory of computation
• Operating Systems
• Numerical computation
• Compilers
• Software Engineering
• Databases
• Real-time computing
• Distributed system
• Computer Networking
• Data Communication
• Computer graphics
• Artificial Intelligence
• Multimedia

General CS articles:

• Abstraction (computer science)
• address space
• alphanumeric code
• array
• artificial intelligence
• atomic
• big endian
• binary tree
• bit array
• buffer overflow
• call stack
• Cheney’s algorithm
• Class (computer science)
• compiler
• computability
• computation
• computational complexity theory
• computer programming
• Concurrency (computer science)
• context switching
• Coupling (computer science)
• cryptography
• dangling pointers
• data
• data structure
• deadlocks
• Design pattern (computer science)
• Digital Revolution
• dynamic memory allocation
• exceptions
• exploits
• function
• function prototype
• Garbage Collection
• halting problem
• Hashing
• Heap overflow
• heuristic
• Heuristic algorithm
• Information Age
• Inheritance (computer science)
• Instruction (computer science)
• Integer (computer science)
• Kernel (computer science)
• Library (computing)
• linked list
• little endian
• Lock (computer science)
• malloc
• memory allocator
• Memory leak
• Memory management
• memory pool
• Method (computer science)
• Microsoft .NET Framework
• Modula-3
• Object (computer science)
• object inheritance
• object-oriented programming
• opcode
• paged memory
• Persistence (computer science)
• Polling (computer science)
• polymorphic code
• polymorphism
• process
• Process (computing)
• programming language theory
• quantum computing
• real-time
• Reflection (computer science)
• Reversible computing
• scheduler
• semipredicate problem
• serialize
• shared memory
• software engineering
• sorting algorithm
• Stack buffer overflow
• stack frame
• Standard Template Library
• state
• String (computer science)
• struct
• syntax
• system call
• system call
• thread
• type inference
• virtual memory
• void pointer
• Weak reference
• Whitespace (computer science)

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.

Type theory

Formal analysis of the types of data, and the use of these types to understand properties of programs, especially program safety.

Category theory

Category theory provides a means of capturing all of math and computation in a single synthesis.

Computational geometry

The study of algorithms to solve problems stated in terms of geometry.

Numerical analysis

Foundations for algorithms in discrete mathematics, as well as the study of the limitations of floating point computation, including round-off errors.

Theory of Computation:

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 can be computed and what cannot.

Computational complexity theory

Fundamental bounds (especially time and storage space) on classes of computations.

Quantum computing theory

Representation and manipulation of data using the quantum properties of particles and quantum mechanism.

Algorithms and data structures

Analysis of algorithms

Time and space complexity of algorithms.

Algorithms

Formal logical processes used for computation, and the efficiency of these processes.

Data structures

The organization of and rules for the manipulation of data.

Programming languages and compilers

Compilers

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

Interpreters

A program that takes in as input a computer program and executes it.

Programming languages

Formal language paradigms for expressing algorithms, and the properties of these languages (e.g., what problems they are suited to solve).

Concurrent, parallel, and distributed systems:

Concurrency

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

Distributed computing

Computing using multiple computing devices over a network to accomplish a common objective or task and thereby reducing the latency involved in single processor contributions for any task.

Parallel computing

Computing using multiple concurrent threads of execution.

Software engineering:

Algorithm design

Using ideas from algorithm theory to creatively design solutions to real tasks

Computer programming

The practice of using a programming language to implement algorithms

Formal methods

Mathematical approaches for describing and reasoning about software designs.

Reverse engineering

The application of the scientific method to the understanding of arbitrary existing software

Software development

The principles and practice of designing, developing, and testing programs, as well as proper engineering practices.

System architecture:

Computer architecture

The design, organization, optimization and verification of a computer system, mostly about CPUs and memory subsystems (and the bus connecting them).

Computer organization

The implementation of computer architectures, in terms of descriptions of their specific electrical circuitry

Operating systems

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

Communications:

Computer audio

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

Networking

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

Cryptography

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

Databases:

Data mining

Data mining is the extraction of relevant data from all sources of data.

Relational databases

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

OLAP

Online Analytical Processing, or OLAP, is an approach to quickly provide answers to analytical queries that are multi-dimensional in nature. OLAP is part of the broader category business intelligence, which also encompasses relational reporting and data mining.

Artificial intelligence:

Artificial intelligence

The implementation and study of systems that exhibit an autonomous intelligence or behaviour of their own.

Artificial life

The study of digital organisms to learn about biological systems and evolution.

Automated reasoning

Solving engines, such as used in Prolog, which produce steps to a result given a query on a fact and rule database.

Computer vision

Algorithms for identifying three dimensional objects from one or more two dimensional pictures.

Machine learning

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

Natural language processing/Computational linguistics

Automated understanding and generation of human language

Robotics

Algorithms for controlling the behavior of robots.

Visual rendering (or 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:

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.

Scientific computing:

Bioinformatics

The use of computer science to maintain, analyse, and store biological data, and to assist in solving biological problems such as protein folding, function prediction and phylogeny.

Cognitive Science

Computational modelling of real minds

Computational chemistry

Computational modelling of theoretical chemistry in order to determine chemical structures and properties

Computational neuroscience

Computational modelling of real brains

Computational physics

Numerical simulations of large non-analytic systems

Numerical algorithms

Algorithms for the numerical solution of mathematical problems such as root-finding, integration, the solution of ordinary differential equations and the approximation/evaluation of special functions.

Symbolic mathematics

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