A Systematic Review of Productivity Factors in Software Development

01/19/2018
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by   Stefan Wagner, et al.
∙
Siemens AG
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Technische Universität München
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0
∙

Analysing and improving productivity has been one of the main goals of software engineering research since its beginnings. A plethora of studies has been conducted on various factors that resulted in several models for analysis and prediction of productivity. However, productivity is still an issue in current software development and not all factors and their relationships are known. This paper reviews the large body of available literature in order to distill a list of the main factors influencing productivity investigated so far. The measure for importance here is the number of articles a factor is mentioned in. Special consideration is given to soft or human-related factors in software engineering that are often not analysed with equal detail as more technical factors. The resulting list can be used to guide further analysis and as basis for building productivity models.

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References

  • [1] A. J. Albrecht. Measuring application development productivity. In Proc. Joint SHARE/GUIDE/IBM Application Development Symposium, pages 83–92, 1979.
  • [2] R. Berntsson-Svensson and A. Aurum. Successful software project and products: An empirical investigation. In Proc. ISESE ’06, pages 144–153. ACM Press, 2006.
  • [3] J. D. Blackburn, G. D. Scudder, and L. N. Van Wassenhove. Improving speed and productivity of software development: A global survey of software developers. IEEE Trans. Softw. Eng., 22(12), 1996.
  • [4] B. W. Boehm, C. Abts, A. W. Brown, S. Chulani, B. K. Clark, E. Horowitz, R. Madachy, D. Reifer, and B. Steece. Software Cost Estimation with COCOMO II. Prentice-Hall, 2000.
  • [5] B. W. Boehm and P. N. Papaccio. Understanding and controlling software costs. IEEE Trans. Softw. Eng., 14(10):1462–1477, 1988.
  • [6] F. C. Brodbeck. Intensive Kommunikation lohnt sich für SE-Projekte. In Brodbeck and Frese [8], pages 51–67.
  • [7] F. C. Brodbeck. Software-Entwicklung: Ein Tätigkeitsspektrum mit vielfältigen Kommunikations- und Lernanforderungen. In Brodbeck and Frese [8], pages 13–34.
  • [8] F. C. Brodbeck and M. Frese, editors. Produktivität und Qualität in Software-Projekten. R. Oldenbourg Verlag, 1994.
  • [9] W. D. Brooks. Software technology payoff: Some statistical evidence. J. Syst. Software, 2(1):3–9, 1981.
  • [10] P. D. Chatzoglou and L. A. Macaulay. The importance of human factors in planning the requirements capture stage of a project. Int. J. Proj. Manag., 15(1):39–53, 1997.
  • [11] T. DeMarco and T. Lister. Peopleware. Productive Projects and Teams. Dorset House Publishing, 1987.
  • [12] M. Frese and F. C. Brodbeck. Einleitung. In Brodbeck and Frese [8], pages 7–10.
  • [13] R. L. Glass. Software runaways–some surprising findings. J. Sys. Software, 41(2):75–77, 1998.
  • [14] L. Hatton. The chimera of software quality. Computer, 40(8):102–104, 2007.
  • [15] E. J. Hill, B. C. Miller, S. P. Weiner, and J. Colihan. Influences of the virtual office on aspects of work and work/life balance. Person. Psychol., 51:667–683, 1998.
  • [16] D. R. Jeffery and M. J. Lawrence. Some issues in the measurement and control of programming productivity. Inform. Manag., 4(4):169–176, 1981.
  • [17] C. Jones. Programming Productivity: Steps Toward a Science. McGraw-Hill, 1986.
  • [18] C. Jones. Software Assessments, Benchmarks, and Best Practices. Addison-Wesley, 2000.
  • [19] B. Kitchenham and E. Mendes. Software productivity measurement using multiple size measures. IEEE Trans. Softw. Eng., 30(12):1023–1035, 2004.
  • [20] B. Lakhanpal. Understanding the factors influencing the performance of software development groups: An exploratory group-level analysis. Inform. Software Tech., 35(8):468–473, 1993.
  • [21] K. Maxwell, L. Van Wassenhove, and S. Dutta. Software development productivity of european space, military and industrial applications. IEEE Trans. Softw. Eng., 22(10):706–718, 1996.
  • [22] K. D. Maxwell and P. Forselius. Benchmarking software development productivity. IEEE Softw., 17(1):80–88, 2000.
  • [23] P. Mohagheghi and R. Conradi. Quality, productivity and economic benefits of software reuse: a review of industrial studies. Empir. Software Eng., 12(5):471–516, 2007.
  • [24] D. Port and M. McArthur. A study of productivity and efficiency for object-oriented methods and languages. In Proc. APSEC ’99. IEEE CS, 1999.
  • [25] Y. W. Ramírez and D. A. Nembhard. Measuring knowledge worker productivity: A taxonomy. J. Intel. Cap., 5(4):602–628, 2004.
  • [26] R. H. Rasch. An investigation of factors that impact behavioral outcomes of software engineers. In Proc. SIGCPR. ACM Press, 1991.
  • [27] M. Ruhe and S. Wagner. Using the ProdFLOW approach to address the myth of productivity in R&D organizations. In Proc. ESEM ’08. ACM Press, 2008.
  • [28] K. Spiegl. Projektmanagement Life – Best Practices und Significant Events im Software-Projektmanagement. Masterarbeit, Universität Wien, 2007.
  • [29] S. Wagner and M. Ruhe. A structured review of productivity factors in software development. Technical Report TUM-I0832, TU München, 2008.
  • [30] C. E. Walston and C. P. Felix. A method of programming measurement and estimation. IBM Sys. J., 16(1):54–73, 1977.
  • [31] C. Wohlin and M. Ahlgren. Soft factors and their impact on time to market. Software Qual. J., 4(3):189–205, 1995.

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