Brief review of classical Effort Estimation models for Software development projects

Authors

  • Diego Bravo-Estrada Unidad de Posgrado, Facultad de Ciencias Matemáticas, UNMSM, Lima, Perú.
  • Roxana López-Cruz Departamento de Matemáticas, Universidad Nacional Mayor de San Marcos, Lima, Perú. http://orcid.org/0000-0002-7703-5784

DOI:

https://doi.org/10.17268/sel.mat.2023.01.17

Keywords:

Software effort estimation, software planning, software engineering

Abstract

A critical synthesis on the most representative models for software development project effort estimation is provided. This work is a basis for a discussion about the methodological and practical challenges which entail the effort estimation field, specially in the mathematical/statistical modelling fundamentals, and its empirical verification in the software industry.

Author Biography

Roxana López-Cruz, Departamento de Matemáticas, Universidad Nacional Mayor de San Marcos, Lima, Perú.

Mathematics, Ph.D. (Arizona State University-USA)

Full Professor, Mathematics Department

Universidad Nacional Mayor de San Marcos, Lima, Perú

References

Albrecht AJ. Measuring application development productivity. InProc. joint share, guide, and ibm application development symposium 1979 (pp. 83-92).

Arnuphaptrairong T. The state of practice of software cost estimation: Evidence from thai software firms. InProceedings of the International MultiConference of Engineers and Computer Scientists 2018 (Vol. 2).

Beck K, Beedle M, Van Bennekum A, Cockburn A, Cunningham W, Fowler M, Grenning J, Highsmith J, Hunt A, Jeffries R, Kern J. Manifesto for agile software development. https://agilemanifesto.org/, 2001

Boehm BW. Software engineering economics. IEEE transactions on Software Engineering. 1984 Jan(1):4-21.

Barry W. Boehm, Clark, Horowitz, Brown, Reifer, Chulani, Ray Madachy, and Bert Steece. 2000. Software Cost Estimation with Cocomo II with Cdrom (1st. ed.). Prentice Hall PTR, USA.

Boehm BW, Valerdi R. Achievements and challenges in cocomo-based software resource estimation. IEEE software. 2008 Aug 19;25(5):74-83.

Brooks Jr FP. The mythical man-month: essays on software engineering. Pearson Education; 1995 Aug 2.

Cant SN, Jeffery DR, Henderson-Sellers B. A conceptual model of cognitive complexity of elements of the programming process. Information and Software Technology. 1995 Jan 1;37(7):351-62.

Chemuturi M. Software estimation best practices, tools & techniques: A complete guide for software project estimators. J. Ross Publishing; 2009 Jul 15.

Chhabra JK, Aggarwal KK, Singh Y. Code and data spatial complexity: two important software understandability measures. Information and software Technology. 2003 Jun 1;45(8):539-46.

Coulter NS. Software science and cognitive psychology. IEEE Transactions on Software Engineering. 1983 Mar(2):166-71.

El Emam K, Koru AG. A replicated survey of IT software project failures. IEEE software. 2008 Aug 19;25(5):84-90.

Glass RL. Some heresy regarding software engineering. IEEE Software. 2004 Jul 6;21(4):104-3.

Halstead MH. Elements of Software Science (Operating and programming systems series). Elsevier Science Inc.; 1977 May 1.

Hetzel WC. The sorry state of software practice measurement and evaluation. Journal of Systems and Software. 1995 Nov 1;31(2):171-9.

IFPUG. International Function Point User's Group. Function Point Counting Practices Manual, 2010.

ISBSG. International software benchmarking standards group.

http://isbsg.org/, n.d. Accedido el 13/01/2019.

C. Jones. Sources of Software Benchmarks. 2011.

https://insights.cermacademy.com/14-sources-of-software-benchmarks-c-capers-jones-2/.

Jones C. Software project management practices: Failure versus success. CrossTalk: The Journal of Defense Software Engineering. 2004 Oct;17(10):5-9.

Jones C. Applied software measurement. McGraw-Hill Education; 2008.

Jones C. The technical and social history of software engineering. Addison-Wesley; 2013 Nov 21.

Jones C. A guide to selecting software measures and metrics. CRC Press; 2017 Mar 3.

Derek Jones. Software effort estimation is mostly fake research. http://shape-of-code.coding-guidelines. com/2021/01/17/software-effort-estimation-is-mostly-fake-research/, 2021.

Bertrand Meyer. The origin of software engineering.

https://bertrandmeyer.com/2013/04/04/the-origin-of-software-engineering/, 2013.

Jørgensen M. A review of studies on expert estimation of software development effort. Journal of Systems and Software. 2004 Feb 1;70(1-2):37-60.

Jørgensen M. A critique of how we measure and interpret the accuracy of software development effort estimation. In First International Workshop on Software Productivity Analysis and Cost Estimation. Information Processing Society of Japan, Nagoya 2007 Dec 4.

Jureta I. The Design of Requirements Modelling Languages. Springer International Publishing; 2015.

Keshta IM. Software cost estimation approaches: A survey. Journal of Software Engineering and Applications. 2017 Sep 28;10(10):824.

Kitchenham B, Taylor NR. Software cost models. ICL technical journal. 1984 May;4(1):73-102.

Kitchenham B, Linkman S. Estimates, uncertainty, and risk. IEEE Software. 1997 May;14(3):69-74.

Kitchenham BA, Pickard LM, MacDonell SG, Shepperd MJ. What accuracy statistics really measure. IEE Proceedings-Software. 2001 Jun 1;148(3):81-5.

Laird LM, Brennan MC. Software measurement and estimation: a practical approach. John Wiley & Sons; 2006 Jun 5.

Lokan CJ. Function points. Advances in Computers. 2005 Jan 1;65:297-347.

McCabe TJ. A complexity measure. IEEE Transactions on software Engineering. 1976 Dec(4):308-20.

McConnell S. Software estimation: demystifying the black art. Microsoft press; 2006 Feb 22.

Menzies T, Yang Y, Mathew G, Boehm B, Hihn J. Negative results for software effort estimation. Empirical Software Engineering. 2017 Oct;22:2658-83.

Molokken K, Jorgensen M. A review of software surveys on software effort estimation. In2003 International Symposium on Empirical Software Engineering, 2003. ISESE 2003. Proceedings. 2003 Sep 30 (pp. 223-230). IEEE.

Norden PV. Project life cycle modeling: Background and application of the life cycle curves. US Army Computer Systems Command. 1977 Aug 21.

Osmanbegović E, Suljić M, Agić H. A review of estimation of software products development costs. Ekonomski Vjesnik/Econviews-Review of Contemporary Business, Entrepreneurship and Economic Issues. 2017 Jun 29;30(1).

Papoulis A, Unnikrishna Pillai S. Probability, random variables and stochastic processes. 2002.

Pmi I. Software Extension to the PMBoK Guide. Project Management Institute, Philadelphia, USA. 2013.

Putnam LH. A general empirical solution to the macro software sizing and estimating problem. IEEE transactions on Software Engineering. 1978 Jul(4):345-61.

Sharma K, Garg R, Nagpal CK, Garg RK. Selection of optimal software reliability growth models using a distance based approach. IEEE Transactions on Reliability. 2010 May 6;59(2):266-76.

Shepperd M, Cartwright M, Kadoda G. On building prediction systems for software engineers. Empirical Software Engineering. 2000 Nov;5:175-82.

Shepperd M, Ince DC. A critique of three metrics. Journal of systems and software. 1994 Sep 1;26(3):197-210.

Stepanek G. Software project secrets. George Stepanek; 2005.

Stutzke RD. Estimating software-intensive systems: projects, products, and processes. Pearson Education; 2005 Apr 26.

Suelmann H. Putnam's effort-duration trade-off law: is the software estimation problem really solved?. In 2014 Joint Conference of the International Workshop on Software Measurement and the International Conference on Software Process and Product Measurement 2014 Oct 6 (pp. 79-84). IEEE.

Trendowicz A, Jeffery R, Trendowicz A, Jeffery R. Classification of Effort Estimation Methods. Software Project Effort Estimation: Foundations and Best Practice Guidelines for Success. 2014:155-208.

Vera T, Ochoa SF, Perovich D. Survey of software development effort estimation taxonomies. Computer Science Department, University of Chile: Santiago, Chile. 2017 Dec.

Verhoef C. Quantitative IT portfolio management. Science of computer programming. 2002 Oct 1;45(1):1-96.

Wen J, Li S, Lin Z, Hu Y, Huang C. Systematic literature review of machine learning based software development effort estimation models. Information and Software Technology. 2012 Jan 1;54(1):41-59.

Published

2023-07-26

How to Cite

Bravo-Estrada, D., & López-Cruz, R. (2023). Brief review of classical Effort Estimation models for Software development projects. Selecciones Matemáticas, 10(01), 199 - 209. https://doi.org/10.17268/sel.mat.2023.01.17

Most read articles by the same author(s)