Three Debates about Computing

  • Matti Tedre
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7921)


Computing as a discipline has a short but vivid history. Computing started to develop a disciplinary identity only after the birth of the stored-program paradigm in the 1940s, and its academic image has seen dramatic changes in the past six decades. This article presents three debates that are central in understanding how computing as a discipline developed to what it is now: the formal verification debate, the software engineering debate, and the experimental computer science debate.


Computer Science Theoretical Computer Science Modern Computing Automatic Computing Disciplinary Identity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Aspray, W.: Was early entry a competitive advantage? US universities that entered computing in the 1940s. IEEE Annals of the History of Computing 22(3), 42–87 (2000)CrossRefGoogle Scholar
  2. 2.
    Atchison, W.F., Conte, S.D., Hamblen, J.W., Hull, T.E., Keenan, T.A., Kehl, W.B., McCluskey, E.J., Navarro, S.O., Rheinboldt, W.C., Schweppe, E.J., Viavant, W., David, J., Young, M.: Curriculum 68: Recommendations for academic programs in computer science: a report of the ACM curriculum committee on computer science. Communications of the ACM 11(3), 151–197 (1968)CrossRefGoogle Scholar
  3. 3.
    Basili, V.R., Zelkowitz, M.V.: Empirical studies to build a science of computer science. Communications of the ACM 50(11), 33–37 (2007)CrossRefGoogle Scholar
  4. 4.
    Brooks Jr., F.P.: No silver bullet: Essence and accidents of software engineering. IEEE Computer 20(4), 10–19 (1987)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Campbell-Kelly, M., Aspray, W.: Computer: A History of the Information Machine, 2nd edn. Westview Press, Oxford (2004)Google Scholar
  6. 6.
    Conte, S.D., Hamblen, J.W., Kehl, W.B., Navarro, S.O., Rheinboldt, W.C., David, J., Young, M., Atchinson, W.F.: An undergraduate program in computer science–preliminary recommendations. Communications of the ACM 8(9), 543–552 (1965)CrossRefGoogle Scholar
  7. 7.
    De Millo, R.A., Lipton, R.J., Perlis, A.J.: Social processes and proofs of theorems and programs. Communications of the ACM 22(5), 271–280 (1979)CrossRefGoogle Scholar
  8. 8.
    Denning, P.J., Comer, D.E., Gries, D., Mulder, M.C., Tucker, A., Turner, A.J., Young, P.R.: Computing as a discipline. Communications of the ACM 32(1), 9–23 (1989)CrossRefGoogle Scholar
  9. 9.
    Dijkstra, E.W.: The humble programmer. Communications of the ACM 15(10), 859–866 (1972)CrossRefGoogle Scholar
  10. 10.
    Dijkstra, E.W.: Programming as a discipline of mathematical nature. American Mathematical Monthly 81(6), 608–612 (1974)MathSciNetzbMATHCrossRefGoogle Scholar
  11. 11.
    Dijkstra, E.W.: On a cultural gap. The Mathematical Intelligencer 8(1), 48–52 (1986)MathSciNetzbMATHCrossRefGoogle Scholar
  12. 12.
    Dijkstra, E.W.: On the cruelty of really teaching computer science. Communications of the ACM 32(12), 1398–1404 (1989)Google Scholar
  13. 13.
    Dijkstra, E.W.: The tide, not the waves. In: Denning, P.J., Metcalfe, R.M. (eds.) Beyond Calculation: The Next Fifty Years of Computing, pp. 59–64. Springer, New York (1997)CrossRefGoogle Scholar
  14. 14.
    Eden, A.H.: Three paradigms of computer science. Minds & Machines 17(2), 135–167 (2007)CrossRefGoogle Scholar
  15. 15.
    Egan, L.G.: Closing the “gap” between the university and industry in computer science. SIGCSE Bulletin 8(4), 19–25 (1976)CrossRefGoogle Scholar
  16. 16.
    Ensmenger, N.L.: The ’question of professionalism’ in the computer fields. IEEE Annals of the History of Computing 23(4), 56–74 (2001)MathSciNetCrossRefGoogle Scholar
  17. 17.
    Fein, L.: The role of the university in computers, data processing, and related fields. Communications of the ACM 2(9), 7–14 (1959)CrossRefGoogle Scholar
  18. 18.
    Feldman, J.A., Sutherland, W.R.: Rejuvenating experimental computer science: A report to the National Science Foundation and others. Communications of the ACM 22(9), 497–502 (1979)CrossRefGoogle Scholar
  19. 19.
    Fellows, M.R.: Computer science and mathematics in the elementary schools. In: Fisher, N.D., Keynes, H.B., Wagreich, P.D. (eds.) Mathematicians and Education Reform. Issues in Mathematics Education, vol. 3, pp. 1990–1991. American Mathematical Society, Providence (1993)Google Scholar
  20. 20.
    Fetzer, J.H.: Program verification: the very idea. Communications of the ACM 31(9), 1048–1063 (1988)CrossRefGoogle Scholar
  21. 21.
    Forsythe, G.E.: A university’s educational program in computer science. Communications of the ACM 10(1), 3–11 (1967)CrossRefGoogle Scholar
  22. 22.
    Forsythe, G.E.: What to do till the computer scientist comes. American Mathematical Monthly 75, 454–461 (1968)MathSciNetzbMATHCrossRefGoogle Scholar
  23. 23.
    Galler, B.A.: Letter from a past president: Distinction of computer science. Communications of the ACM 17(6), 300 (1974)CrossRefGoogle Scholar
  24. 24.
    Gibbs, W.W.: Software’s chronic crisis. Scientific American 271(3), 86–95 (1994)CrossRefGoogle Scholar
  25. 25.
    Haigh, T.: The history of information technology. Annual Review of Information Science and Technology 45(1), 431–487 (2011)CrossRefGoogle Scholar
  26. 26.
    Hoare, C.A.R.: The mathematics of programming. In: Maheshwari, S.N. (ed.) FSTTCS 1985. LNCS, vol. 206, pp. 1–18. Springer, Heidelberg (1985)CrossRefGoogle Scholar
  27. 27.
    Hoare, C.A.R.: Retrospective: An axiomatic basis for computer programming. Communications of the ACM 52(10), 30–32 (2009)CrossRefGoogle Scholar
  28. 28.
    Hodges, A.: Alan Turing: The Enigma. Vintage Books, London (1983)zbMATHGoogle Scholar
  29. 29.
    Holloway, C.M.: Software engineering and epistemology. SIGSOFT Software Engineering Notes 20(2), 20–21 (1995)CrossRefGoogle Scholar
  30. 30.
    Johnson, D.S.: A theoretician’s guide to the experimental analysis of algorithms. In: Goldwasser, M.H., Johnson, D.S., McGeoch, C.C. (eds.) Data Structures, Near Neighbor Searches, and Methodology: Fifth and Sixth DIMACS Implementation Challenges. DIMACS Series in Discrete Mathematics and Theoretical Computer Science, vol. 59, pp. 215–250. American Mathematical Society, Providence (2002)Google Scholar
  31. 31.
    Knuth, D.E.: Algorithmic thinking and mathematical thinking. American Mathematical Monthly 92, 170–181 (1985)MathSciNetzbMATHCrossRefGoogle Scholar
  32. 32.
    Mahoney, M.S.: Histories of Computing. Harvard University Press, Cambridge (2011)Google Scholar
  33. 33.
    McCorduck, P.: An interview with Louis Fein. Charles Babbage Institute, The Center for the History of Information Processing (May 9, 1979)Google Scholar
  34. 34.
    McCracken, D.D., Denning, P.J., Brandin, D.H.: An ACM executive committee position on the crisis in experimental computer science. Communications of the ACM 22(9), 503–504 (1979)CrossRefGoogle Scholar
  35. 35.
    Naur, P., Randell, B. (eds.): Software Engineering: Report on a Conference Sponsored by the Nato Science Committee, Garmisch, Germany, October 7-11. NATO Scientific Affairs Division, Brussels (1968, 1969)Google Scholar
  36. 36.
    Newell, A., Perlis, A.J., Simon, H.A.: Computer science. Science 157(3795), 1373–1374 (1967)CrossRefGoogle Scholar
  37. 37.
    Palvia, P., Mao, E., Salam, A.F., Soliman, K.S.: Management information systems research: What’s there in a methodology? Communications of the Association for Information Systems 11(16), 1–32 (2003)Google Scholar
  38. 38.
    Peisert, S., Bishop, M.: I am a scientist, not a philosopher! IEEE Security and Privacy 5(4), 48–51 (2007)CrossRefGoogle Scholar
  39. 39.
    Ralston, A.: Computer science, mathematics, and the undergraduate curricula in both. The American Mathematical Monthly 88(7), 472–485 (1981)MathSciNetCrossRefGoogle Scholar
  40. 40.
    Ralston, A., Shaw, M.: Curriculum ’78–is computer science really that unmathematical? Communications of the ACM 23(2), 67–70 (1980)CrossRefGoogle Scholar
  41. 41.
    Reilly, E.D.: Milestones in Computer Science and Information Technology. Greenwood Press, Westport (2003)Google Scholar
  42. 42.
    Rice, J.R., Rosen, S.: Computer sciences at Purdue University–1962 to 2000. IEEE Annals of the History of Computing 26(2), 48–61 (2004)MathSciNetCrossRefGoogle Scholar
  43. 43.
    Simon, H.A.: The Sciences of the Artificial, 1st edn. MIT Press, Cambridge (1969)Google Scholar
  44. 44.
    Smith, B.C.: Limits of correctness in computers. Technical Report CSLI-85-36, Center for the Study of Language and Information, Stanford University, Stanford, CA, USA (1985)Google Scholar
  45. 45.
    Sommerville, I.: Software Engineering. Addison-Wesley, Bedford Square (1982)zbMATHGoogle Scholar
  46. 46.
    Spier, M.J.: A critical look at the state of our science. SIGOPS Operating Systems Review 8(2), 9–15 (1974)CrossRefGoogle Scholar
  47. 47.
    Tedre, M.: Computing as a science: A survey of competing viewpoints. Minds & Machines 21(3), 361–387 (2011)CrossRefGoogle Scholar
  48. 48.
    Wegner, P.: Research paradigms in computer science. In: ICSE 1976: Proceedings of the 2nd International Conference on Software Engineering, pp. 322–330. IEEE Computer Society Press, Los Alamitos (1976)Google Scholar
  49. 49.
    Williams, S.B.: The association for computing machinery. Journal of the ACM 1(1), 1–3 (1954)CrossRefGoogle Scholar
  50. 50.
    Wood, H.M.: Computer society celebrates 50 years. IEEE Annals of the History of Computing 17(4), 6 (1995)CrossRefGoogle Scholar
  51. 51.
    Zelkowitz, M.V., Wallace, D.R.: Experimental validation in software engineering. Information and Software Technology 39(11), 735–743 (1997)CrossRefGoogle Scholar

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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Matti Tedre
    • 1
  1. 1.Department of Computer and Systems SciencesStockholm UniversityStockholmSweden

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