Abstract
[Context] Lean and agile software development processes encourage delivering software in small increments so as to generate early business value, be able to adapt to changes, and reduce risks. Deciding what to build in each iteration is an important requirements engineering activity. The Incremental Funding Method (IFM) partly supports such decisions by identifying sequences of features delivery that optimize Net Present Value (NPV). [Problem] The IFM, however, does not deal explicitly with uncertainty and considers the maximization of NPV as the only objective, without explicit consideration for other objectives such as minimizing upfront investment costs and maximizing learning so as to reduce uncertainty and risk for future iterations. [Ideas] This short paper presents our ongoing research to address these limitations by extending IFM with Bayesian decision analysis to reason about uncertainty and with Pareto-based optimization to support decisions with respect multiple conflicting objectives. [Contributions] The paper presents the current version of our tool-supported extension of the IFM, illustrate it on a small example, and outlines our research agenda.
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References
Larman, G., Basili, V.R.: Iterative and incremental development: a brief history. IEEE Comput. 6, 47–56 (2003)
Leffingwell, D.: Agile Software Requirements: Lean Requirements Practices for Teams, Programs, and the Enterprise. Addison-Wesley Professional, Boston (2010)
Greer, D., Ruhe, G.: Software release planning: an evolutionary and iterative approach. Inf. Softw. Technol. 46(4), 243–253 (2004)
Denne, M., Cleland-Huang, J.: Software by Numbers. Sun Microsystems Press, Upper Saddle River (2004)
Denne, M., Cleland-Huang, J.: The incremental funding method: data-driven software development. IEEE Softw. 21(3), 39–47 (2004)
Winkler, R.L.: An Introduction to Bayesian Inference and Decision, 2nd edn. Probabilistic Publishing, Gainesville (2003)
Letier, E., Stefan, D., Barr, E.T.: Uncertainty, risk, and information value in software requirements and architecture. In: Proceedings of 36th International Conference on Software Engineering (2014)
Harman, M., Jones, B.F.: Search-based software engineering. Inf. Softw. Technol. 43(14), 833–839 (2001)
Moore, M., Kaman, R., Klein, M., Asundi, J.: Quantifying the value of architecture design decisions: lessons from the field. In: Proceedings of 25th International Conference on Software Engineering (2003)
Cantor, M.: Calculating and improving ROI in software and system programs. Commun. ACM 54(9) (2011) (Ruhe, G., Greer, D. Quantitative studies in software release planning under risk and resource constraints. In: Proceedings of ISESE (2003))
Logue, K., McDaid, K.: Agile release planning: dealing with uncertainty in development time and business value. In: Proceedings of ECBS (2008)
Alencar, A.J., et al.: A statistical approach for the maximization of the financial benefits yielded by a large set of MMFs and AEs. Comput. Inform. 32(6), 1147–1169 (2013)
Barbosa, B.P., Schmitz, E.A., Alencar, A.J.: Generating software-project investment policies in an uncertain environment. In: Proceedings SIEDS (2008)
da Cunha Mattos, E.M., et al.: Applying game theory to the incremental funding method in software projects. J. Softw. 9(6), 1435–1443 (2014)
O’Hagan, A., Buck, C., Daneshkhah, A., Eiser, J., Garthwaite, P., Jenkinson, D., Oakley, J., Rakow, T.: Uncertain Judgments: Eliciting Experts’ Probabilities. Wiley, Hoboken (2006)
Heaven, W., Letier, E.: Simulating and optimising design decisions in quantitative goal models. In: Proceedings of 9th International Conference on Requirements (2011)
Mahvish, K., Gorschek, T., Wilson, M.: The software value map—an exhaustive collection of value aspects for the development of software intensive products. J. Softw. Evol. Process 25(7), 711–741 (2013)
Veerappa, V., Letier, E.: Understanding clusters of optimal solutions in multi-objective decision problems. In: Proceedings 19th International Conference on Requirements (2011)
Acknowledgment
Olawole Oni’s research is funded by the Tertiary Education Trust Fund (TETFund) in Nigeria.
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Oni, O., Letier, E. (2016). Optimizing the Incremental Delivery of Software Features Under Uncertainty. In: Daneva, M., Pastor, O. (eds) Requirements Engineering: Foundation for Software Quality. REFSQ 2016. Lecture Notes in Computer Science(), vol 9619. Springer, Cham. https://doi.org/10.1007/978-3-319-30282-9_3
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DOI: https://doi.org/10.1007/978-3-319-30282-9_3
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