Advertisement

Evaluating the Perceived Effect of Software Engineering Practices in the Italian Industry

  • Evgenia Egorova
  • Marco Torchiano
  • Maurizio Morisio
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5543)

Abstract

A common limitation of software engineering research consists in its detachment from the industrial practice. Researchers have analyzed several practices and identified their benefits oand drawbacks but little is known about their dissemination in the industry. For a set of commonly studied practices, this paper investigates diffusion, perceived usefulness, and effect on the success for actual industrial projects. We found a match between academia recommendation and industry perception for more than 3 / 4 of the best practices. But we also found a few misperceptions of well-known practices.

Keywords

Software Process Project Factors Survey Case-Control Study 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Berntsson-Svensson, R., Aurum, A.: Successful software project and products: an empirical investigation. In: Proceedings of the ACM/IEEE international symposium on Empirical Software Engineering, pp. 144–153 (2006)Google Scholar
  2. 2.
    Basili, V., Musa, J.: The Future Engineering of Software: A Management Perspective. IEEE Computer Magazine 24(9), 90–96 (1991)CrossRefGoogle Scholar
  3. 3.
    British Medical Association, http://www.bmj.com
  4. 4.
    Camera di commercio di Torino - UNIMATICA di Torino: L’ICT in Provincia di Torino: La sfida dell’innovazione nel mercato globale. Turin (2006)Google Scholar
  5. 5.
  6. 6.
    Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13(3), 319–340 (1989)CrossRefGoogle Scholar
  7. 7.
    Dybå, T.: An Empirical Investigation of the Key Factors for Success in Software Process Improvement. IEEE Trans. Software Eng. 31(5), 410–424 (2005)CrossRefGoogle Scholar
  8. 8.
    Field, T.: When BAD Things Happen to GOOD Projects. CIO Magazine, pp. 55–62 (1997)Google Scholar
  9. 9.
    Holland, C., Light, B.: A critical success factors model for ERP implementation. IEEE Software 16, 30–36 (1999)CrossRefGoogle Scholar
  10. 10.
    Istituto Nazionale di Statistica: Classificazione delle attività economiche Ateco (2007), http://www.istat.it/strumenti/definizioni/ateco/
  11. 11.
    Iivari, J.: Factors affecting perceptions of CASE effectiveness. European Journal of Information Systems 4(3), 143–158 (1995)CrossRefGoogle Scholar
  12. 12.
    Iivari, J.: Why are CASE tools not used? Comm. of the ACM 39(10), 94–103 (1996)CrossRefGoogle Scholar
  13. 13.
    Keil, M., Cule, P.E., Lyytinen, K., Schmidt, R.C.: A framework for identifying software project risks. Commun. ACM 41(11), 76–83 (1998)CrossRefGoogle Scholar
  14. 14.
    Linberg, K.R.: Software developer perceptions about software project failure: a case study. Journal of Systems and Software 49(2-3), 177–192 (1999)CrossRefGoogle Scholar
  15. 15.
    Reel, J.S.: Critical Success Factors In Software Projects. IEEE Software 16(3), 18–23 (1999)CrossRefGoogle Scholar
  16. 16.
    Rosenzweig, P.: The Halo Effect: And the Eight Other Business Delusions That Deceive Managers. Free Press (2007)Google Scholar
  17. 17.
    Saridakis, T., Maccari, A.: Software architecture in industry: misuse and non-use. Technical report HK/R-RES 99/13 SE, University of Karlskrona i Ronneby 1999 (1999)Google Scholar
  18. 18.
    Strassburger, K, Bretz, F.: Compatible simultaneous lower confidence bounds for the Holm procedure and other Bonferroni-based closed tests. Stat. Med. (2008) Google Scholar
  19. 19.
    Sumner, M.: Critical success factors in enterprise wide information management systems projects. In: Proceedings of the Americas Conference on Information Systems (AMCIS), pp. 232–234 (1999)Google Scholar
  20. 20.
    Verner, J.M., Evanco, W.M.: In-House Software Development: What Project Management Practices Lead to Success? IEEE Software 22(1), 86–93 (2005)CrossRefGoogle Scholar
  21. 21.
    Weber, R., Waller, M., Verner, J., Evanco, W.: Predicting Software Development Project Outcomes. In: Ashley, K.D., Bridge, D.G. (eds.) ICCBR 2003. LNCS, vol. 2689, pp. 595–609. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  22. 22.
    Wohlin, C., Ahlgren, M.: Soft Factors and Their Impact on Time to Market. Software Quality Journal 4, 189–205 (1995)CrossRefGoogle Scholar
  23. 23.
    Wohlin, C., Andrews, A.: Evaluation of Three Methods to Predict Project Success: A Case Study. In: Bomarius, F., Komi-Sirviö, S. (eds.) PROFES 2005. LNCS, vol. 3547, pp. 385–398. Springer, Heidelberg (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Evgenia Egorova
    • 1
  • Marco Torchiano
    • 1
  • Maurizio Morisio
    • 1
  1. 1.Politecnico di TorinoTurinItaly

Personalised recommendations