Empirical Knowledge Discovery by Triangulation in Computer Science

Advances in Computers

Volumn 80, Issue C, 2010, Pages 163-190

  Singh, Ravi I ^a   Miller, James ^a  

^a UNIVERSITY OF ALBERTA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84944618026     PISSN: 00652458     EISSN: None     Source Type: Book Series    
DOI: 10.1016/S0065-2458(10)80004-X     Document Type: Chapter

References (70)

1. Denning, P.J., Comer, D.E., Gries, D., Mulder, M.C., Tucker, A.B., Turner, A.J., et al. Computing as a discipline. Commun. ACM, 32(1), 1989 January.
2. Li, M., Li, X., Ma, B., Vitanyi, P., The similarity metric. IEEE Trans. Inf. Theory 50 (2004), 3250–3264 December.
3. Brooks, F., No silver bullet: Essence and accidents of software engineering. IEEE Comput. 20:4 (1987), 10–19 April.
4. Brooks, F., Three great challenges for half-century-old computer science. J. ACM 50:1 (2003), 25–26.
5. Simon, H.A., Sciences of the Artificial. third ed., 1996, MIT, Cambridge.
6. Miller, J., Triangulation as a basis for knowledge discovery in software engineering. Empir. Softw. Eng. J., 13(2), 2008, 224.
7. Simon, H.A., Cognitive science: The newest science of the artificial. Cogn. Sci. 4:1 (1980), 33–46.
8. Hines, A.M., Linking qualitative and quantitative methods in cross-cultural survey research: Techniques from cognitive science. Am. J. Community Psychol. 21:6 (1993), 729–746.
9. Guindon, R., Designing the design process: Exploiting opportunistic thoughts. Hum. Comput. Interact. 5 (1990), 305–344.
10. Chaitin, G., Algorithmic Information Theory, 1987, Cambridge University Press, Cambridge.
11. Sommerville, I., Rodden, T., Sawyer, P., Bentley, R., Twidale, M., Integrating ethnography into the requirements engineering process., Proceedings of the IEEE Requirements Engineering Conference, San Diego, 1993.
12. Chaitin, G., Algorithmic information theory. IBM J. Res. Dev., 21, 1977, 350 (Toward a mathematical theory of life, in: The Maximum Entropy Formalism (R.D. Levine and M. Tribus, Ed.), MIT press, Cambridge, MA, 1979).
13. Vitányi, P., Li, M., Minimum description length induction, Bayesianism, and Kolmogorov complexity. 1999 arxiv.org cs.LG/9901014.
14. Cilibrasi, R., Vitanyi, P., Clustering by compression, IEEE International Symposium on Information Theory Yokohama, Japan, 2003.
15. Blelloch, G., Introduction to data compression. 2000 (Course notes for: Algorithms for the real world).
16. Wallace, G.K., The JPEG Still Picture Compression Standard. Commun. ACM 34 (1991), 30–44 April.
17. Adams, M.D., The JPEG-2000 Still Image Compression Standard, ISO/IEC JTC 1/SC 29/WG 1N 2412. 2001, Int. Org. for Stand./Org. Int. de Normal, Paris, France.
18. Beatty, P., Reay, I., Dick, S., Miller, J., Consumer Trust in E-Commerce Websites: A Meta-Study, 2008, ACM Computing Surveys (in print).
19. Schadewitz, N., Nguyen-Ngoc, A.V., Law, E., Identifying design patterns in international collaborative learning—Two contrasting case studies. 2009.
20. Basili, V., Selby, R., Hutchens, D., Experimentation in software engineering. IEEE Trans. Softw. Eng., 1986.
21. Glass, R., Vessey, I., Ramesh, V., Research in Software Engineering: An Analysis of the Literature. J. Inf. Softw. Technol. 44:8 (2002), 491–506 June.
22. Basili, V., Shull, F., Lanubile, F., Building knowledge through families of experiments. IEEE Trans. Softw. Eng. 25:4 (1999), 456–473.
23. Bratthall, L., J⊘rgensen, M., Can you trust a single data source exploratory software engineering case study?. Empir. Softw. Eng. 7:1 (2002), 9–26.
24. Webb, E., Campbell, D., Schwartz, R., Sechrest, L., Unobtrusive Measures: Nonreactive Research in the Social Sciences. 1966, Rand McNally, Chicago, IL.
25. Denzin, N.K., The Research Act in Sociology. 1970, Butterworth, London.
26. Cheng, L., Changing Language Teaching Through Language Testing: A Wash Back Study, 2005, Cambridge University Press, Cambridge, 72.
27. Hammersley, M., Atkinson, P., Ethnography: Principles in practice. 1983, Tavistock, London.
28. Miles, M.B., Huberman, A.M., Qualitative Data Analysis, 1984, Sage, Beverly Hills, 235.
29. Denzin, N.K., The Research Act: A Theoretical Introduction to Sociological Methods. 1978, McGraw-Hill, New York, NY.
30. Daly, J., Replication and a Multi-Method Approach to Empirical Software Engineering Research, 1996 (Ph.D. Thesis. Department of Computer Science, University of Strathclyde, Glasgow, UK).
31. Denzin, N.K., Lincoln, Y., (eds.) Collecting and Interpreting Qualitative Materials, 1988, Sage Publications, Thousand Oaks, CA.
32. Kaplan, B., Duchon, D., Combining qualitative and quantitative methods in information systems research: A case study. MIS Q., 1988.
33. Patton, M.Q., Qualitative Evaluation Methods. 1980, Sage, Beverly Hills, CA.
34. Downward, P., Mearman, A., Methodological triangulation at the Bank of England: An investigation. 2005 (Discussion Paper 505. University of the West of England press, Bristol School of Economics).
35. Kimchi, J., Polivka, B., Stevenson, J.S., Triangulation: Operational definitions. Nurs. Res. 40:6 (1991), 364–366.
36. Mathison, S., Why triangulate?. Educ. Res. 77:2 (1988), 13–17.
37. Fielding, N.G., Fielding, J.L., Linking Data: Qualitative and Quantitative Methods in Social Research. 1986, Sage, Beverley Hills, CA.
38. Rittel, H., Webber, M., Dilemmas in a general theory of planning. Policy Sci. 4 (1973), 155–169.
39. Gigerenzer, G., Selten, R., Bounded Rationality. 2002, MIT, Cambridge, MA.
40. Gomory, R.E., An essay on the known, the unknown and the unknowable. Sci. Am., 272, 1995, 120.
41. Lethbridge, T.C., Sim, S.E., Singer, J., Studying software engineers: Data collection techniques for software field studies. Empir. Softw. Eng. 10:3 (2005), 311–341.
42. Dickson, G., A programmatic approach to information systems research: An experimentalist's view. Benbasat, I., (eds.) The Information Systems Research Challenge: Experimental Research Methods, 1989, Harvard Business School,.
43. Kitchenham, B., Pickard, L., Pfeeger, S.-L., Case studies for method and tool evaluation. IEEE Softw., 1995, 52–62.
44. Yin, R.K., Case Study Research: Design and Methods. second ed., 1984, Sage Publications, USA.
45. Jick, T., Mixing qualitative and quantitative methods: Triangulation in action. Admin. Sci. Quart., 24, 1979.
46. Glass, R., The software research crisis. IEEE Softw., 11(6), 1994.
47. Creswell, J., Research Design: Qualitative, Quantitative and Mixed Methods Approaches, second ed., 2003, Sage publications.
48. Singer, J., Vinson, N.G., Ethical issues in empirical studies of software engineering. IEEE Trans. Softw. Eng. 28:12 (2002), 1171–1180 December.
49. Basili, V., The role of experimentation in software engineering: Past, current, and future., 18th International Conference on Software Engineering, 1996, IEEE, Berlin, Germany, 442–449.
50. Miller, J., Daly, J., Wood, M., Roper, M., Brooks, A., Statistical power and its subcomponents—Missing and misunderstood concepts in empirical software engineering research. Inf. Softw. Technol. 4:39 (1997), 285–295.
51. Miller, J., Statistical significance testing—A panacea for software technology experiments?. J. Syst. Softw. 2:73 (2004), 183–192.
52. Zelkowitz, M., Wallance, D., Experimental validation in software engineering. Inf. Softw. Technol. 11:39 (1997), 735–743.
53. Dyba, T., Kampenes, V., Sj⊘berg, D., A systematic review of statistical power in software engineering experiments. Inf. Softw. Technol. 8:48 (2006), 745–755.
54. Kitchenham, B., Pfleeger, S., Pickard, L., Jones, P., Hoaglin, D., El Emam, K., et al. Preliminary guidelines for empirical research in software engineering. IEEE Trans. Softw. Eng. 8:28 (2002), 721–734.
55. Miller, J., Replicating software engineering experiments: A poisoned chalice or the Holy Grail. Inf. Softw. Technol. 47:4 (2005), 233–244.
56. Brooks, A., Daly, J., Miller, J., Roper, M., Wood, W., Replication's role in experimental computer science. 1994 (Technical Report EFoCS-5-941 [RR/94/172], Department of Computer Science, University of Strathclyde, Glasgow, Scotland, UK).
57. Oivo, M., New opportunities for empirical research. Basili, V.R., Rombach, H.D., Schneider, K., Kitchenham, B., Pfahl, D., Selby, R.W., (eds.) Empirical Software Engineering Issues. LNCS, vol. 4336, 2007, Springer, Heidelberg, Germany, 22.
58. Curtis, B., Measurement and experimentation in software engineering. Proceedings of IEEE, 1980, Los Alamitos, CA, 1144–1157.
59. Trochim, W.M.K., Research Methods: The Concise Knowledge Base, 2006, Atomic Dog Publishing.
60. Mandic, V., Markkula, J., Oivo, M., Towards Multi-Method Research Approach in Empirical Software Engineering, 2009 (University of Oulu, Department of Information Processing Science, Rakentajantie 3, 90014 University of Oulu, Finland).
61. Shaw, M., What makes good research in software engineering?. Int. J. Softw. Tools Technol. Transf. 4:1 (2002), 1–7.
62. Hramiak, A., Initial evaluation and analysis of post graduate trainees' use of a virtual learning environment in initial teacher training. Electron. J. e-Learn. 5:2 (2007), 103–112.
63. Li, M., Vitanyi, P., An Introduction to Kolmogorov Complexity and its Applications. second ed., 1997, Springer, New York, NY.
64. Ball, L., Ormerod, T., Putting ethnography to work: The case for a cognitive ethnography of design. Int. J. Hum. Comput. Stud. 53:1 (2000), 147–168.
65. Brewer, J., Hunter, A., Multimethod Research: A Synthesis of Styles. 1989, Sage, Thousand Oaks.
66. Campbell, D.T., Fiske, D.W., Convergent and discriminant validation by the multitrait-multimethod matrix. Psychol. Bull. 56 (1959), 81–105.
67. Fenton, N., Peeger, S., Glass, R., Science and substance: A challenge to software engineers. IEEE Software 11:4 (1994), 86–95.
68. Hammersley, M., What's wrong with ethnography?. 1992, London, Routledge.
69. Smith, H.W., Strategies of Social Research: The Methodological Imagination. 1975, Prentice Hall, Englewood Cliffs, NJ.
70. Wood, M., Daly, J., Miller, J., Roper, M., Multi-Method Research: An Empirical Investigation of Object-Oriented Technology. Syst. Softw. 48:1 (1999), 13–26.