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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 4336))

Abstract

Empirical software engineering has grown in importance in the software engineering research community over the last 20 years. This means that it has become very important to also include empirical studies systematically into the curricula in computer science and software engineering. This chapter presents several aspects and challenges to have in mind when doing this. The chapter presents three different educational levels to have in mind when introducing empirical software engineering into the curricula. An introduction into the curricula also means increased possibilities to run empirical studies in student settings. Some challenges in relation to this is presented and the need to balance educational and research objectives is stressed.

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References

  1. Basili, V.R., Selby, R.W., Hutchens, D.H.: Experimentation in software engineering. IEEE Trans. on Software Engineering 12(7), 733–743 (1986)

    Google Scholar 

  2. Basili, V.R., Shull, F., Lanubile, F.: Building knowledge through families of experiments. IEEE Trans.on Software Engineering 25(4), 456–473 (1999)

    Article  Google Scholar 

  3. Berander, P.: Using students as subjects in requirements prioritization. In: Proc. 3rd Int. Symposium on Empirical Software Engineering, pp. 167–176 (2004)

    Google Scholar 

  4. Carver, J., et al.: Issues in using students in empirical studies in software engineering education. In: Proc. Int. Software Metrics Symposium, pp. 239–249 (2003)

    Google Scholar 

  5. Hayes, W.: Research synthesis in software engineering: A case for meta-analysis. In: Proc. 6th Int. Software Metrics Symposium, pp. 143–151 (1999)

    Google Scholar 

  6. Höst, M., Regnell, B., Wohlin, C.: Using students as subjects – a comparative study of students and professionals in lead-time impact assessment. An International Journal 5(3), 201–214 (2000)

    MathSciNet  MATH  Google Scholar 

  7. Höst, M.: Introducing empirical software engineering methods in education. In: Proc. Int. Conf. on Software Engineering Education and Training, pp. 170–179 (2002)

    Google Scholar 

  8. Höst, M., Wohlin, C., Thelin, T.: Experimental context classification: Incentives and experience of subjects. In: Proc. Int. Conference on Software Engineering, pp. 470–478 (2005)

    Google Scholar 

  9. Juristo, N., Moreno, A.M.: Basics of Software Engineering Experimentation. Kluwer Academic Publishers, Dordrecht (2001)

    MATH  Google Scholar 

  10. Juristo, N., Moreno, A. (eds.): Lecture Notes on Empirical Software Engineering. World Scientific Publishers, Singapore (2003)

    MATH  Google Scholar 

  11. Kitchenham, B.A., Dybå, T., Jørgensen, M.: Evidence-based software engineering. In: Proc. Int. Conference on Software Engineering, pp. 273–281 (2004)

    Google Scholar 

  12. Miller, J.: Can results from software engineering experiments be safely combined? In: Proc. 6th Int. Software Metrics Symposium, pp. 152–158 (1999)

    Google Scholar 

  13. Shull, F., et al.: Replicating software engineering experiments: Addressing the tacit knowledge problem. In: Proc. 1st Int. Symposium on Empirical Software Engineering, pp. 7–16 (2002)

    Google Scholar 

  14. Sjøberg, D.I.K., et al.: Conducting realistic experiments in software engineering. In: Proc. 1st Int. Symposium on Empirical Software Engineering, pp. 17–26 (2002)

    Google Scholar 

  15. Sjøberg, D.I.K., et al.: A survey of controlled experiment in software engineering. IEEE Trans. on Software Engineering 31(9), 733–753 (2005)

    Article  Google Scholar 

  16. Staron, M., Kuzniarz, L., Wohlin, C.: Empirical assessment of using stereotypes to improve comprehension of UML models: A set of experiments. Journal of Systems and Software 79(5), 727–742 (2006)

    Article  Google Scholar 

  17. Thelin, T., Runeson, P., Wohlin, C.: An Experimental Comparison of Usage-Based and Checklist-Based Reading. IEEE Transactions on Software Engineering 29(8), 687–704 (2003)

    Article  Google Scholar 

  18. Conradi, R., Wang, A.I. (eds.): Empirical Methods and Studies in Software Engineering. LNCS, vol. 2765. Springer, Heidelberg (2003)

    MATH  Google Scholar 

  19. Wohlin, C., et al.: Experimentation in Software Engineering – An Introduction. Kluwer Academic Publishers, Dordrecht (1999)

    Google Scholar 

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Authors

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Victor R. Basili Dieter Rombach Kurt Schneider Barbara Kitchenham Dietmar Pfahl Richard W. Selby

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© 2007 Springer Berlin Heidelberg

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Wohlin, C. (2007). Empirical Software Engineering: Teaching Methods and Conducting Studies. In: Basili, V.R., Rombach, D., Schneider, K., Kitchenham, B., Pfahl, D., Selby, R.W. (eds) Empirical Software Engineering Issues. Critical Assessment and Future Directions. Lecture Notes in Computer Science, vol 4336. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71301-2_42

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  • DOI: https://doi.org/10.1007/978-3-540-71301-2_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71300-5

  • Online ISBN: 978-3-540-71301-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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