This Talk 1. Computer science: Definition The Computational ”Paradigm” 2. Why did computing need to be an academic discipline? of Science 3. What characterizes computing as a discipline? ECSS 2015 4. Is everything computing? Matti Tedre Stockholm University, DSV Computer Science Is… Computer Science Is… The art and science of representing and processing information [, and…] Forsythe (1967)
Computer Science Is… Computer Science Is… The study of computing machines (actual The study of computers and the or potential) phenomena surrounding them Finerman (1970) Newell, Perlis & Simon (1969) Computer Science Is… Computer Science Is… The study of algorithms [and related The academic study of what you can do phenomena] with computers and logic together Knuth (1974) Bornat (2006)
Computer Science Is… Computer Science Is… The study of information structures and processes and how [they] can be A study of the theory and practice of implemented on a digital computer programming computers ACM Curriculum (1968) Khalil & Levy (1978) Computer Science Is… Computer Science Is… The science devoted to the extension of A science that studies naturally and the uses of machines in the service of artificially occurring information processes mankind Hammer (1970) Denning (2007)
Computer Science Is… Computer Science Is… A natural science An artificial science Denning (2007) Simon (1969) Computer Science Is… Computer Science Is… An unnatural science A speculative science Knuth (2001) Genova (2010)
Computer Science Is… Computer Science Is… A laboratory science A social science Basili (1996) Goldweber et al. (1997) Computer Science Is… Computer Science Is… A synthetic discipline The fourth, new domain of science Brooks (1996) Rosenbloom (2013)
Computer Science Is… Computer Science Is… the study of […] information structures A spectrum […] with “science” on the one end and “engineering” on the other Wegner (1972) Parlante (2005) Computer Science Is… Computer Science Is… The body of knowledge dealing with […] [about] “what can be automated” processes that transform information Denning (1985) Arden (ed., 1980)
Computer Science Is… Computer Science Is… [about] “what can be (efficiently) The science of abstraction automated” Denning et al. (1989) Aho & Ullman (1995) Computer Science Is… Computer Science Is… The study of procedures Procedural epistemology Shapiro (2001) Abelson & Sussman (1996)
Computer Science Is… Computer Science Is… A branch of philosophy The science of the relations between parts and wholes Wartik (2010) Minsky (1979) Computer Science Is… Computer Science Is… An exact [or axiomatic] science A mathematical science Hoare (1969) cf. McCarthy (1962)
Computer Science Is… Computer Science Is… A new species of engineering Information engineering Loui (1995) Bajcsy & Reynolds (2002) Computer Science Is… Computer Science Is… Engineering of mathematics Conceptual engineering Hartmanis (1981) Wegner (1970)
Computer Science Is… Computer Science Is… A technological discipline A language of technology Wegner (1976) Cohen & Haberman (2007) Computer Science Is… Computer Science Is… Cognitive technology Mechanization of abstraction Kadvany (2010) Aho & Ullman (1995)
Computer Science Is… Computer Science Is… Automation of our abstractions A new paradigm of science. Wing (2008) Denning & Freeman (2009) Who is this emperor? Software engineering? Information systems? Emperor or Plumber? (Theoretical) computer science? Computer engineering? Information technology? Computational science / scientific computing?
…And Whose Emperor? of Natural Science? Computing: The of Mathematics? Logic? of Humanities? Social Sciences? Discipline of Political Science? Theology? of Business? Innovation? of Engineering? Birth of Computing as a Discipline: A Timeline How Much Back Should We Look? When Exactly Is a Discipline Born?
1940s: A New Kind of Computer 1. Why Did It Need to ● Universities: important role in computer revolution Be a Discipline? – Differential Analyzers (MIT) – ABC Computer (Iowa State) 1950s–1960s: The Birth – Harvard Mark(s) (Harvard) – ENIAC (U. of Pennsylvania) – SSEM “Baby” (Manchester) – IAS (Princeton) Some Cornerstone Ideas From Universities In Established Disciplines ● From engineering projects ● From engineering projects engineering) Electrical) – programmable computer – programmable computer – digital and fully electronic operation – digital and fully electronic operation – treating instructions as data – treating instructions as data ● From mathematics + logic ● From mathematics + logic Mathema/cs) And)Logic) – binary arithmetic (simplified design) – binary arithmetic (simplified design) – computable functions – computable functions – instructions = data – instructions = data
Problems for Academic 1950s: Outsourcing Innovation Computing Pioneers ● Private sector R&D labs ● The field’s foundations take over hardware already well covered by development established disciplines – IBM (hard drive, etc.) ● Why start a new field for a tool ? – Bell Labs (transistor, etc.) ● No warm welcome in – Texas Instruments research universities (integrated circuit, etc.) – Xerox PARC (e.g. GUI) Driving Agenda: Independence! Driving Agenda: Independence! ● Own budgets ● Representation: national / intn’l ● Own student boards, policy quota committees ● Own staff quota ● Academic + public ● Leverage in image university politics ● Directed grants ● Societal influence ● Field’s own funding calls
“Science of Computing” Emerged… The Dilemma of Reducibility ● To convince university administrators, ● McCarthy: It’s computing had to be: going to be like Physics 1. Strongly connected with mathematics so that it is treated as ● Hoare: It’s a fundamental research (and not as natural science technology!) ● Dijkstra: 2. Different from mathematics so that Computing science it’s not treated as another branch of mathematics Gulfs of Rhetoric …But Things Weren’t What They Seemed ● Mathematical theory of computation (McCarthy) – Not empirical science (like physics) ● Axiomatic basis for programming (Hoare) – No empirical research (like natural sciences) ● Computing science (Dijkstra) – Implementation details are irrelevant – Far from software engineering
What’s in a Name? (Impressions, at least…) ’50s-60s: Plumber or Emperor? ● Physics: the King of Hypology' Computer'science(s)' Autonomics' sciences Turology' Computerology' Bionics' Applied'epistemology' Intellectronics' Cyberne:cs' ● Mathematics: the Queen Applied'metamathema:cs' Technetronics' Synnoe:cs' of sciences Compu:ng'science' Turingineering' ● Computing in the Royal Comptology' Compu:cs' Court? Informa:cs' Algorithmics' Datalogy' Summary: Computing’s Entry to Academia 2. What ● Born out of a need to govern its own Characterizes research agenda and resources Computing as ● Competing visions for development and resources a Discipline? ● A strong instrumentalist identity ● Emerging intellectual identity 1970s–1990s: Search for Disciplinary Identity
What Is It Science of ? Diversification and Change ● Some branches diminish ● Computers ● Programming ● New branches are born ● Classes of ● Programs computations (executable) ● Computing’s user base diversifies ● Automation ● Data ● Concept appropriation ● Procedures ● Information into CS concepts ● Complexity ● Algorithms – Graphs, matrices, etc. Curricula Follows the Training Needs What Kind of Science Is It? ● Axiomatic ACM)CC)1968) ACM)CC’78)Preliminary) ● Mathematical Report) ● Artificial “…academic'program'in' “…no'mathema:cal' ● Synthetic computer'science'must' background'beyond'the' ● Unnatural be'well'based'in' ability'to'perform'simple' ● Experimental mathema:cs”' algebraic'manipula:on'is' ● Natural a'prerequisite'to'an' ● “ Fourth domain ” understanding'of'the' ● “ A new paradigm ” topics”'
Experimental Computer Science Mistakes ● Attempted to change how ● Failure to establish terminology we talk about computing – No consensus over (~1979) “experimental” – Fueled by the ● Politicized term from the mid-1980s great beginning epistemic change in – Tied to funding and influence science – A rush to label one’s work ● Numerical analysis on the “expcs” rise “Experiment” in CS? ’70s-’80s: Emperor or Plumber? “What'should'logically'happen?”' Thought'experiment' E.g.'“Chinese'Room”'against'SAI' ● Physics: the King of sciences “Can'it'be'done?”' ● Mathematics: the Queen of sciences Feasibility'experiment' Demonstra:on,'proof'of'concept' “Does'it'meet'the'specifica:ons?”' Trial'experiment' Prototypes,'laboratory'/'par:al'tests' ● Computing? “Does'it'meet'the'requirements?”' – Increasingly important for science Field'experiment' Tests'with'real'environment'and'users' – Contributions to mathematics “Does'A'outperform'B?”' Compara:ve'experiment' Comparisons'between'solu:ons' – Not very coherent within “Do'the'hypotheses'hold'under'X?”,' Controlled'experiment' “What'variables'affect'Y?”,'etc.''
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