Computer science

Computer science studies computation, information, algorithms, and computational systems. It spans theoretical questions about what can be computed and practical methods for designing software and hardware.

Algorithm: A finite, well-defined procedure for solving a problem or performing a computation. Algorithms are the central objects whose correctness and efficiency computer science investigates.
Turing machine: An abstract machine that computes by reading and writing symbols on an unbounded tape according to fixed rules. It provides a precise model for defining computation and computability.
Database: An organized collection of data designed for efficient storage, retrieval, and updating. Database systems apply algorithms and data models to persistent information.
Computer engineering: The discipline concerned with designing and building computer hardware and integrated hardware-software systems. It emphasizes physical implementation, while computer science also studies abstract computation.
Alan Turing: A British mathematician whose work helped establish theoretical computer science and wartime codebreaking. His abstract machine gave a durable formal account of computation.
Data structure: A way of organizing data to support particular operations efficiently. Data structures shape how algorithms store, retrieve, and transform information.
Lambda calculus: A formal system for expressing computation through function definition and application. It offers a foundational model of computation closely connected to programming languages.
Computer network: A set of interconnected devices that exchange data using communication protocols. Networking applies computation to communication across devices and distances.
Information systems: The study and practice of systems that collect, process, store, and distribute information in organizations. It centers organizational uses of technology rather than computation as a general subject.
Alonzo Church: An American mathematician who developed lambda calculus and contributed to the foundations of computability. His formal system helped define which problems can be computed.

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