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An empirically developed method to aid decisions on architectural technical debt refactoring: AnaConDebt

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Published:14 May 2016Publication History

ABSTRACT

Architectural Technical Debt is regarded as sub-optimal architectural solutions that need to be refactored in order to avoid the payment of a costly interest in the future. However, decisions on if and when to refactor architecture are extremely important and difficult to take, since changing software at the architectural level is quite expensive. Therefore it is important, for software organizations, to have methods and tools that aid architects and managers to understand if Architecture Technical Debt will generate a costly and growing interest to be paid or not. Current knowledge, especially empirically developed and evaluated, is quite scarce. In this paper we developed and evaluated a method, AnaConDebt, by analyzing, together with several practitioners, 12 existing cases of Architecture Debt in 6 companies. The method has been refined several times in order to be useful and effective in practice. We also report the evaluation of the method with a final case, for which we present anonymized results and subsequent refactoring decisions. The method consists of several components that need to be analyzed, combining the theoretical Technical Debt framework and the practical experience of the practitioners, in order to identify the key factors involved in the growth of interest. The output of the method shows summarized indicators that visualizes the factors in a useful way for the stakeholders. This analysis aids the practitioners in deciding on if and when to refactor Architectural Technical Debt items. The method has been evaluated and has been proven useful to support the architects into systematically analyze and decide upon a case.

References

  1. P. Kruchten, R. L. Nord, and I. Ozkaya, "Technical Debt: From Metaphor to Theory and Practice," IEEE Softw., vol. 29, no. 6, pp. 18--21, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. R. L. Nord, I. Ozkaya, P. Kruchten, and M. Gonzalez-Rojas, "In Search of a Metric for Managing Architectural Technical Debt," in 2012 Joint Working IEEE/IFIP Conference on Software Architecture (WICSA) and European Conference on Software Architecture (ECSA), 2012, pp. 91--100. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. A. Martini, J. Bosch, and M. Chaudron, "Investigating Architectural Technical Debt Accumulation and Refactoring over Time: a Multiple-Case Study," Inf. Softw. Technol. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. A. Martini and J. Bosch, "The Danger of Architectural Technical Debt: Contagious Debt and Vicious Circles," in accepted for publication at WICSA 2015, Montreal, Canada. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. N. A. Ernst, S. Bellomo, I. Ozkaya, R. L. Nord, and I. Gorton, "Measure It? Manage It? Ignore It? Software Practitioners and Technical Debt," in Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering, New York, NY, USA, 2015, pp. 50--60. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. E. Tom, A. Aurum, and R. Vidgen, "An exploration of technical debt," J. Syst. Softw., vol. 86, no. 6, pp. 1498--1516, Jun. 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. W. Cunningham, "The WyCash portfolio management system," in ACM SIGPLAN OOPS Messenger, 1992, vol. 4, pp. 29--30. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Z. Li, P. Avgeriou, and P. Liang, "A systematic mapping study on technical debt and its management," J. Syst. Softw., vol. 101, pp. 193--220, Mar. 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. N. Brown, Y. Cai, Y. Guo, R. Kazman, M. Kim, P. Kruchten, E. Lim, A. MacCormack, R. Nord, I. Ozkaya, and others, "Managing technical debt in software-reliant systems," in Proceedings of the FSE/SDP workshop on Future of software engineering research, 2010, pp. 47--52. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Y. Guo, C. Seaman, R. Gomes, A. Cavalcanti, G. Tonin, F. Q. Da Silva, A. L. M. Santos, and C. Siebra, "Tracking technical debt---An exploratory case study," in Software Maintenance (ICSM), 2011 27th IEEE International Conference on, 2011, pp. 528--531. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. C. Seaman, Y. Guo, N. Zazworka, F. Shull, C. Izurieta, Y. Cai, and A. Vetro, "Using technical debt data in decision making: Potential decision approaches," in 2012 Third International Workshop on Managing Technical Debt (MTD), 2012, pp. 45--48. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. J.-L. Letouzey, "The SQALE Method for Evaluating Technical Debt," in Proceedings of the Third International Workshop on Managing Technical Debt, Piscataway, NJ, USA, 2012, pp. 31--36. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. A. Nugroho, J. Visser, and T. Kuipers, "An empirical model of technical debt and interest," in Proceedings of the 2nd Workshop on Managing Technical Debt, New York, NY, USA, 2011, pp. 1--8. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. K. Schmid, "A formal approach to technical debt decision making," in Proceedings of the 9th international ACM Sigsoft conference on Quality of software architectures, 2013, pp. 153--162. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. P. Kruchten, "What do software architects really do?," J. Syst. Softw., vol. 81, no. 12, pp. 2413--2416, Dec. 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. A. Martini, L. Pareto, and J. Bosch, "Role of Architects in Agile Organizations," in Continuous Software Engineering, J. Bosch, Ed. Springer International Publishing, 2014, pp. 39--50.Google ScholarGoogle Scholar
  17. M. A. Babar and I. Gorton, "Comparison of scenario-based software architecture evaluation methods," in Software Engineering Conference, 2004. 11th Asia-Pacific, 2004, pp. 600--607. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. K. Peffers, T. Tuunanen, M. A. Rothenberger, and S. Chatterjee, "A Design Science Research Methodology for Information Systems Research," J. Manag. Inf. Syst., vol. 24, no. 3, pp. 45--77, Dec. 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. ISO - International Organization for Standardization, "System and software quality models." {Online}. Available: http://www.iso.org/iso/catalogue_detail.htm?csnumber=52075. {Accessed: 08-Mar-2015}.Google ScholarGoogle Scholar
  20. J. Carriere, R. Kazman, and I. Ozkaya, "A cost-benefit framework for making architectural decisions in a business context," in 2010 ACM/IEEE 32nd International Conference on Software Engineering, 2010, vol. 2, pp. 149--157. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. P. Runeson and M. Höst, "Guidelines for conducting and reporting case study research in software engineering," Empir. Softw. Eng., vol. 14, no. 2, pp. 131--164, Dec. 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library

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      cover image ACM Conferences
      ICSE '16: Proceedings of the 38th International Conference on Software Engineering Companion
      May 2016
      946 pages
      ISBN:9781450342056
      DOI:10.1145/2889160

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      • Published: 14 May 2016

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