Data science & AI · Reference
What is computer science?
Computer science is the study of computation, algorithms, information, and the design of computing systems — spanning the theoretical foundations of what can be computed and the practical engineering of software and hardware.
What computer science studies
At its core, computer science asks what can be computed, how efficiently, and by what means. An algorithm — a precise, finite procedure for solving a problem — is a central object of study, as is the data on which algorithms operate. The discipline combines mathematical theory with engineering practice: it both proves what is and is not possible in principle and builds working systems. It is therefore broader than programming, which is one tool computer scientists use rather than the subject itself.
Major subfields
Computer science spans many subfields. Theory of computation and algorithms study what can be computed and how efficiently. Systems covers operating systems, networks, and databases; architecture covers hardware design.
Artificial intelligence and machine learning study systems that perceive and learn. Other areas include programming languages, software engineering, security and cryptography, human-computer interaction, graphics, and computer vision — each a substantial field in its own right.
Theoretical foundations
Computer science has deep theoretical roots. Alan Turing's 1936 work on the Turing machine formalised the notion of computation and identified problems that no algorithm can solve (the limits of computability). The theory of computational complexity classifies problems by the resources — time and memory — needed to solve them, including the famous open question of whether P equals NP. These foundations underpin the whole discipline, setting the boundaries within which all practical computing operates.
Computer science and research
As a discipline, computer science both advances its own knowledge and provides methods and tools used across all of science — from simulation and data science to the management of large datasets. Computational methods are now integral to research in fields as varied as biology, physics, and the social sciences. This pervasiveness places a premium on reproducible computational practice: sharing code, documenting environments, and validating results so that computation-based findings can be checked and reused.
Key facts
At a glance
- Definition: the study of computation, algorithms and information
- Central object: the algorithm
- Scope: from theoretical foundations to applied engineering
- Foundational figure: Alan Turing (Turing machine, 1936)
- Key open question: whether P equals NP
- Broader than: programming (one tool of the field)
Common questions
FAQ
What is the difference between computer science and programming?+
Programming is the practice of writing code, and is one tool computer scientists use. Computer science is the broader study of computation, algorithms, information, and systems — including theory about what can be computed and how efficiently, much of which involves no programming directly.
What are the main subfields of computer science?+
They include theory of computation and algorithms, systems and networks, computer architecture, artificial intelligence and machine learning, programming languages, software engineering, security and cryptography, human-computer interaction, and graphics, among others.
Who is considered a founder of computer science?+
Alan Turing is widely regarded as a founder of the field. His 1936 work formalised the concept of computation through the Turing machine and identified the existence of problems that no algorithm can solve.
The step most authors miss
Doing CRediT right? Don’t stop at the statement.
A CRediT statement credits you inside one paper. The recognition CRediT was built for happens when those roles are tied to you, persistently. Sign in with your ORCID — free — and claim your CRediT contributions on casrai.org, the home of the standard. They become a verified, portable part of your identity, not a line that disappears into one PDF.
Free: claim your contributions, then export a journal-ready CRediT statement, schema.org structured data, JATS XML, CSV or BibTeX — and preview your public profile. A membership publishes that profile publicly and verifies the journals you serve.
