尽管计算机科学（computer science）的名字里包含计算机这几个字，但实际上计算机科学相当数量的领域都不涉及计算机本身的研究。因此，一些新的名字被提议出来。某些重点大学的院系倾向于术语计算科学（computing science），以精确强调两者之间的不同。丹麦科学家彼得·諾爾建议使用术语"datalogy"，以反映这一事实，即科学学科是围绕着数据和数据处理，而不一定要涉及计算机。第一个使用这个术语的科学机构是哥本哈根大学计算科学系（英语：UCPH Department of Computer Science），该学院成立于1969年，彼得·諾爾便是第一任教授。这个术语主要被用于北欧国家。同时，在计算技术发展初期，《ACM通讯》建议了一些针对计算领域从业人员的术语：圖靈工程師（turingineer），turologist，流程圖人（flow-charts-man），應用元數學家（applied meta-mathematician）及應用認識論者（applied epistemologist）。[10] 三个月后在同样的期刊上，comptologist被提出，第二年又变成了hypologist。[11] 术语computics也曾经被提议过。在欧洲大陆，起源于信息（information）和数学或者自动（automatic）的名字比起源于计算机或者计算（computation）更常见，如informatique（法语），Informatik（德语），informatika（斯拉夫语族）。
著名计算机科学家艾兹赫尔·戴克斯特拉曾经指出：“计算机科学并不只是关于计算机，就像天文学并不只是关于望远镜一样。”（"Computer science is no more about computers than astronomy is about telescopes."）设计、部署计算机和计算机系统通常被认为是非计算机科学学科的领域。例如，研究计算机硬件被看作是计算机工程的一部分，而对于商业计算机系统的研究和部署被称为信息技术或者信息系统。然而，现如今也越来越多地融合了各类计算机相关学科的思想。计算机科学研究也经常与其它学科交叉，比如数学、工程学、认知科学和经济学等。
虽然最初很多人并不相信计算机可能成为科学研究的领域，但是随后的50年里也逐渐被学术界认可。[20]IBM公司是那段时期计算机科学革命的参与者之一。在那段探索时期，IBM（International Business Machines的缩写）发布的IBM 704以及之后的IBM 709计算机被广泛使用。“不过，使用IBM电脑工作仍然是一件很沮丧的事情。如果你弄错了一条指令中的一个字母，程序将会崩溃，而你也得从头再来。”[20]20世纪50年代后期，计算机科学学科還在发展階段，这種問題在当时是一件很常見的事情。
按照Peter J. Denning的说法，计算机科学的最根本问题是“什么能够被有效地自动化？”[12]计算理论的研究就是專注于回答这个根本问题，关于什么能够被计算，去实施这些计算又需要用到多少资源。为了试图回答第一个问题，递归论检验在多种理论计算模型中哪个计算问题是可解的。而计算复杂性理论则被用于回答第二个问题，研究解决一个不同目的的计算问题的时间与空间消耗。
^Comer, D. E.; Gries, David; Mulder, Michael C.; Tucker, Allen; Turner, A. Joe; Young, Paul R. /Denning. Computing as a discipline. Communications of the ACM. 1989-01-01, 32 (1): 9–23. ISSN 0001-0782. doi:10.1145/63238.63239. Computer science and engineering is the systematic study of algorithmic processes-their theory, analysis, design, efficiency, implementation, and application-that describe and transform information.
^Wegner, P. Research paradigms in computer science. Proceedings of the 2nd international Conference on Software Engineering. San Francisco, California, United States: IEEE Computer Society Press, Los Alamitos, CA. October 13–15, 1976. Computer science is the study of information structures
^Abelson, H.; G.J. Sussman with J. Sussman. Structure and Interpretation of Computer Programs 2nd. MIT Press. 1996. ISBN 978-0-262-01153-2. The computer revolution is a revolution in the way we think and in the way we express what we think. The essence of this change is the emergence of what might best be called procedural epistemology – the study of the structure of knowledge from an imperative point of view, as opposed to the more declarative point of view taken by classical mathematical subjects.
"Within more than 70 chapters, every one new or significantly revised, one can find any kind of information and references about computer science one can imagine. [...] all in all, there is absolute nothing about Computer Science that can not be found in the 2.5 kilogram-encyclopaedia with its 110 survey articles [...]." (Christoph Meinel, Zentralblatt MATH)
"[...] this set is the most unique and possibly the most useful to the [theoretical computer science] community, in support both of teaching and research [...]. The books can be used by anyone wanting simply to gain an understanding of one of these areas, or by someone desiring to be in research in a topic, or by instructors wishing to find timely information on a subject they are teaching outside their major areas of expertise." (Rocky Ross, SIGACT News)
"Since 1976, this has been the definitive reference work on computer, computing, and computer science. [...] Alphabetically arranged and classified into broad subject areas, the entries cover hardware, computer systems, information and data, software, the mathematics of computing, theory of computation, methodologies, applications, and computing milieu. The editors have done a commendable job of blending historical perspective and practical reference information. The encyclopedia remains essential for most public and academic library reference collections." (Joe Accardin, Northeastern Illinois Univ., Chicago)
"Covering a period from 1966 to 1993, its interest lies not only in the content of each of these papers — still timely today — but also in their being put together so that ideas expressed at different times complement each other nicely." (N. Bernard, Zentralblatt MATH)
Research evaluation for computer science, Informatics Europe report. Shorter journal version: Bertrand Meyer, Christine Choppy, Jan van Leeuwen and Jorgen Staunstrup, Research evaluation for computer science, in Communications of the ACM, vol. 52, no. 4, pp. 31-34, April 2009.
Norman Gibbs, Allen Tucker. "A model curriculum for a liberal arts degree in computer science". Communications of the ACM, Volume 29 Issue 3, March 1986.
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