Advertisement

A Method to Support the Adoption of Reuse Technology in Large Software Organizations

  • Luiz Amorim
  • Manoel Mendonça
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9679)

Abstract

The process of adopting a software technology in a large organization is significantly influenced by organizational culture and behavioral aspects of the practitioners involved in the process. The adoption of software reuse technology in particular significantly alters the software process of the organization as well as the modus operandi of the practitioners involved. The identification of factors that will facilitate or hinder this process is strongly correlated with the existing system of beliefs and represents a key element to the planning of this process. Our aim is to propose an action model based on classes of beliefs that will support the process of adoption of software reuse technology. An industrial case study was conducted in a large organization to validate and refine the proposed method. As a result, we propose a method based on the identification of classes of beliefs and re-signification of those that hinders the adoption of software reuse technologies.

Keywords

Adoption of software reuse technology Software reuse beliefs Reasoned action model Beliefs system and knowledge Re-signification of beliefs Industrial case study 

References

  1. 1.
    Ahmed, F., Capretz, L., Sheikh, S.: Institutionalization of software product line: An empirical investigation of key organizational factors. JSS 80, 836–849 (2007)Google Scholar
  2. 2.
    Ahmed, F., Campbell, P., Lagharid, M.: Cognitive factors in software product line engineering. In: Proceedings of the UK Sim 2009, pp. 352–355. IEEE, USA (2009)Google Scholar
  3. 3.
    Ajzen, I.: The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50(2), 179–211 (1991)CrossRefGoogle Scholar
  4. 4.
    Almeida, E.: RiDE: The RiSE Process for Domain Engineering. Ph.d Thesis, Universidade Federal de Pernambuco, Brazil (2007)Google Scholar
  5. 5.
    American Psychological Association, Glossary of psychological terms, Apa.org. (2013). http://www.apa.org/research/action/glossary.aspx
  6. 6.
    Argyris, C., Putnam, R., McLain Smith, D.: Action Science: Concepts, Methods, and Skills for Research and Intervention. Jossey-Bass, San Francisco (1985)Google Scholar
  7. 7.
    Bandura, A.: On the functional properties of perceived self-efficacy revisited. J. Manage. 38(1), 9–44 (2012)Google Scholar
  8. 8.
    Basili, V., Briand, L., Melo, W.: How reuse influences productivity in object-oriented systems. Commun. ACM 39(10), 104–116 (1996)CrossRefGoogle Scholar
  9. 9.
    Basili, V., Rombach, D., Selby, R. (eds.): Experimental Software Engineering Issues: Critical Assessment and Future Directions. LNCS, vol. 706. Springer, Heidelberg (1993)MATHGoogle Scholar
  10. 10.
    Bastos, J., Neto, P., Almeida, E., Meira, S.: Adopting software product lines: a systematic mapping study. In: 15th EASE, Durham City (2011)Google Scholar
  11. 11.
    Bosch, J.: Software product lines: organizational alternatives. In: Proceedings of the 23rd ICSE, pp. 91–100. IEEE Computer Society, Washington, DC (2001)Google Scholar
  12. 12.
    Bongard, B., Gronquist, B., Ribot, D.: Impact of reuse on organizations. In: Proceedings of the Reuse 1993. IEEE Computer Society Press, Los Alamitos (1993)Google Scholar
  13. 13.
    Broughton, S., Sinatra, G., Reynolds, R.: The refutation text effect: Influence on learning and attention. American Educational Researchers, Chicago (2007)Google Scholar
  14. 14.
    Caldiera, G.: Domain factory and software reusability. In: Proceedings of the Software Engineering Symposium: New Frontiers for Software Maintenance (1991)Google Scholar
  15. 15.
    Catal, C.: Barriers to the adoption of software product line engineering. SIGSOFT Softw. Eng. Notes 34, 1–4 (2009)CrossRefGoogle Scholar
  16. 16.
    Chi, M.: Three types of conceptual change: Belief revision, mental model transformation, and categorical shift. In: Vosniadou, S. (ed.) International Handbook of Research on Conceptual Change. Erlbaum, Hillsdale (2008)Google Scholar
  17. 17.
    Davis, F., Bagozzi, R., Warshaw, P.: User acceptance of computer technology: A comparison of two theoretical models. Manage. Sci. 35, 982–1003 (1989)CrossRefGoogle Scholar
  18. 18.
    Douglas, N., Wykowski, T.: From Belief to Knowledge Achieving and Sustaining an Adaptive Culture in Organizations. CRC Press, USA (2011)Google Scholar
  19. 19.
    Easterbrook, S., Singer J., Storey, M., Damian, D.: Selecting empirical methods for software engineering research. In: Shull, F., Singer, J., Sjøberg, D.I.K. (eds.) Guide to AESE, Section III, pp. 285–311. Springer, London (2008)Google Scholar
  20. 20.
    Ezran, M., Morisio, M., Tully, C.: Practical Software Reuse. Springer, London (2002)CrossRefMATHGoogle Scholar
  21. 21.
    Fishbein, M., Ajzen, I.: Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Addison-Wesley, Reading (1975)Google Scholar
  22. 22.
    Fishbein, M., Ajzen, I.: Predicting and Changing Behavior: The Reasoned Action Approach. Psychology Press, New York (2010)Google Scholar
  23. 23.
    Frakes, W., Kang, K.: Software Reuse Research, Status and Future. IEEE Trans. Software Eng. 31(7), 529–536 (2006)CrossRefGoogle Scholar
  24. 24.
    Gacek, C., Knauber, P., Schmid, K., Clements, P.: Successful software product line development in a small organization. In: SPL: Practices and Patterns. Addison Wesley (2001)Google Scholar
  25. 25.
    Garcia, V., Lisboa, L., Meira, S., Almeida, E., Lucrécio, D., Fortes, R.: Towards a maturity model for a reuse incremental adoption. In: SBCARS (2007)Google Scholar
  26. 26.
    Gardner, H.: Changing Minds. Harvard Business School Publishing, Boston (2006)Google Scholar
  27. 27.
    Griss, M.: Software Reuse: Objects and Frameworks are not Enough. Object Mag. 5(2), 77–87 (1995)Google Scholar
  28. 28.
    Hoffman, N., Keppler, R.: Assimilating New Technologies: The Role of Organizational Culture. Inf. Syst. Manage. 17(3), 36–42 (2000)CrossRefGoogle Scholar
  29. 29.
    Joanes, L., Northrop, L.: Clearing the way for software product line success. IEEE Softw. 27, 22–28 (2010)CrossRefGoogle Scholar
  30. 30.
    Knauber, P., Muthig, D., Schmid, K., Widen, T.: Applying product line concepts in small and medium-sized companies. IEEE Softw. 17, 88–95 (2000)CrossRefGoogle Scholar
  31. 31.
    Li, D., Chang, C.: Initiating and institutionalizing software product line engineering: from bottom-up approach to top-down practice. In: Proceedings of the 2009 33rd Annual IEEE ICSAC, vol. 01, pp. 53–60. IEEE Computer Society, USA (2009)Google Scholar
  32. 32.
    Livari, J., Livari, N.: The relationship between organizational culture and the deployment of agile methods. IST 53(5), 509–520 (2011)Google Scholar
  33. 33.
    Lloréns, J., Fuentes, J.M., Prieto-Diaz, R., Astudillo, H.: Incremental Software Reuse. In: Morisio, M. (ed.) ICSR 2006. LNCS, vol. 4039, pp. 386–389. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  34. 34.
    Lucredio, D., Brito, K., Alvaro, A., Garcia, V., Almeida, E., Fortes, R., Meira, S., Software reuse: The brazilian industry scenario. JSS 81, 996–1013 (2008)Google Scholar
  35. 35.
    Lynex, A., Layzell, P.: Organizational considerations for software reuse. Ann. Softw. Eng. 5, 105–124 (1998)CrossRefGoogle Scholar
  36. 36.
    Lytras, M., Pablos, P.: Software Technologies in Knowledge Society. J. UCS 17(9), 1219–1221 (2011)Google Scholar
  37. 37.
    Mannion, M., Organizing for software product line engineering. In: Proceedings of the 10th International Workshop on STEP. IEEE Computer Society, USA (2002)Google Scholar
  38. 38.
    Morisio, M., Ezran, M., Tully, C.: Success and failure factors in software reuse. IEEE Trans. Softw. Eng. 28(04), 340–357 (2002)CrossRefMATHGoogle Scholar
  39. 39.
    Muthig, D.: A Light-weight Approach Facilitating an Evolutionary Transition Towards Software product Lines. Ph.d. thesis, Universitär Kaiserlautern (2002)Google Scholar
  40. 40.
    Northrop, L.: Software product line adoption roadmap. Technical Note CMU/SEI-2004-TR-022, SEI (2004)Google Scholar
  41. 41.
    Partala, T., Saari, T.: Understanding the most influential user experiences in successful and unsuccessful technology adoptions. CHB 53, 381–395 (2015)Google Scholar
  42. 42.
    Passos, C., Braun, A., Cruzes, D., Mendonça, M.: Analyzing the impact of beliefs in software project practices. In: ESEM (2011)Google Scholar
  43. 43.
    Passos, C., Mendonça M., Cruzes, D.: The role of organizational culture in software development practices: a cross-case analysis of four software companies. In: Proceedings of SBES 2014, Maceio, Brazil (2014)Google Scholar
  44. 44.
    Poulin, J.S.: The Business Case for Software Reuse: Reuse Metrics, Economic Models, Organizational Issues, and Case Studies. In: Morisio, M. (ed.) ICSR 2006. LNCS, vol. 4039, p. 439. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  45. 45.
    Prieto-Díaz, R.: Making software reuse work: An implementation model. ACM SIGSOFT Softw. Eng. Notes 16, 61–68 (1991)CrossRefGoogle Scholar
  46. 46.
    Psychology Dictionary (2015). http://psychologydictionary.org/
  47. 47.
    Punter, T., Krikhaar, R., Bril, R.: Software engineering technology innovation: turning research results into industrial success. JSS 82(1), 993–1003 (2009)Google Scholar
  48. 48.
    Rine, D.: Success factors for software reuse that are applicable across domains and businesses. In: ACM Symposium on Applied Computing, USA, pp. 182–186 (1997)Google Scholar
  49. 49.
    Rine, D., Sonnemann, R.: Investment in reusable software. A study on software reuse investment success factors. J. Syst. Softw. 41, 17–32 (1998)CrossRefGoogle Scholar
  50. 50.
    Runeson, P., Host, M.: Guidelines for conducting and reporting case study research in software engineering. Empirical Softw. Eng. 14(2), 131–164 (2008)CrossRefGoogle Scholar
  51. 51.
    Schwitzgebel, E.: Belief. In: Zalta, E. (ed.) The Stanford Encyclopedia of Philosophy, Stanford. http://plato.stanford.edu/entries/belief/
  52. 52.
    Sharp, H.: Software reuse: Survey and Research Directions. J. Manage. Inf. Syst. 14(4), 113–147 (1998)CrossRefGoogle Scholar
  53. 53.
    Sherif, K., Vinze, A.: Barriers to adoption of software reuse A qualitative study. Inf. Manage. 419, 159–175 (2003)CrossRefGoogle Scholar
  54. 54.
    Sherif, K., Appan, R., Lin, Z.: Resources and incentives for the adoption of systematic software reuse. Int. J. Inf. Manage. 26, 70–80 (2006)CrossRefGoogle Scholar
  55. 55.
    Sjoberg, D., Hannay, J., Hansen, O., Kampenes, V., Karahasanović, A., Liborg, N.: A survey of controlled experiments in software engineering. IEEE TSE 31(9), 733–753 (2005)Google Scholar
  56. 56.
    Straub, E.: Understanding technology adoption: Theory and future directions for informal learning. Rev. Educ. Res. 79(2), 625–649 (2009)CrossRefGoogle Scholar
  57. 57.
    Venkatesh, V., Davis, F.: A theoretical extension of the technology acceptance model: four longitudinal field studies. Manage. Sci. 45(2), 186–204 (2000)CrossRefGoogle Scholar
  58. 58.
    Venkatesh, V., Bala, H.: Technology acceptance model 3 and a research agenda on interventions. Decis. Sci. 39(2), 273–315 (2008)CrossRefGoogle Scholar
  59. 59.
    Wernick, P., Hall, T.: Can Thomas Kuhn’s paradigms help us understand software engineering. Eur. J. Inf. Syst. 13(3), 235–243 (2004)CrossRefGoogle Scholar
  60. 60.
    Wohlinf, C., Runeson, P., Höst, M., Ohlsson, M., Regnell, B., Wesslén, A.: Experimentation in Software Engineering. Springer, Heidelberg (2012)CrossRefMATHGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Computer ScienceFederal University of BahiaSalvadorBrazil
  2. 2.Fraunhofer Project Center at UFBASalvadorBrazil

Personalised recommendations