ABSTRACT
Despite the exponential increase in the demand for software and the increase in our dependence on software, many software manufacturers behave in an unpredictable manner. In such an unpredictable software manufacturer organization, it is difficult to determine the optimal release time. An economic model is presented supporting the evaluation and comparison of different release or market entry alternatives. This model requires information with respect to achieved reliability and maintainability. Existing literature reveals many models to estimate reliability and limited models to estimate maintainability. The practicality of most available models is however criticized. A series of case studies confirmed that software manufacturers struggle with determining the reliability and maintainability of their products prior to releasing them. This leads to a combination of non-analytical methods to decide when a software product is 'good enough' for release: intuition prevails where sharing convincing information is required. Next research steps are put forward to investigate ways increasing the economic reasoning about the optimal release time.
- Boehm, B. W., Sullivan, K. J., Software Economics: A Roadmap. ACM Press, 2000.Google Scholar
- Chillarege, R., et al., Orthogonal Defect Classification -- A Concept for In-Process Measurements. IEEE Transactions on Software Engineering, 18, 11, 1992. Google ScholarDigital Library
- Chulani, S., COQUALMO (COnstructive QUALity MOdel): A Software Defect Density Prediction Model. In Project Control for Software Quality, Kusters et al., (Eds.), Shaker Publishing, 1999.Google Scholar
- Cook, C., Visconti, M., New and improved documentation process model. Proceedings of the 14th Pacific Northwest Software Quality Conference, Portland, 1996, 364--380.Google Scholar
- Erdogmus, H., Comparative evaluation of software development strategies based on Net Present Value. Proceedings of the First International Workshop on Economics-driven Software Engineering Research, Toronto (Canada), 1999.Google Scholar
- Fenton, N. E., Pfleeger, S. L., Software Metrics: A Rigorous & Practical Approach. PWS Publishing Company, 1997. Google ScholarDigital Library
- Fenton, N. E., et al., Assessing Dependability of Safety Critical Systems using Diverse Evidence. IEEE Proceedings Software Engineering, 145, 1, 1998, 35--39.Google ScholarCross Ref
- Fenton, N. E., Neil, M., A Critique of Software Defect Prediction Research. IEEE Transactions on Software Engineering, 25, 5, 1999. Google ScholarDigital Library
- Gokhale, S. S., et al., Important Milestones in Software Reliability Modeling. Communications in Reliability, Maintainability and Serviceability, SAE International, 1996.Google Scholar
- IEEE, IEEE Standard Dictionary of Measures to Produce Reliable Software. IEEE Std. 982.1, The Institute of Electrical and Electronics Engineers, 1988.Google Scholar
- IEEE, IEEE Guide for the Use of IEEE Standard Dictionary of Measures to Produce Reliable Software. IEEE Std. 982.1, The Institute of Electrical and Electronics Engineers, 1988.Google Scholar
- ISO, ISO/IEC 9126-1:2001 Software Engineering - Product Quality - Part 1: Quality model. International Organization for Standardization, 2001.Google Scholar
- Kelly, T. P., Arguing Safety. PhD thesis, University of York (UK), 1998.Google Scholar
- Kemerer, C., Software complexity and software maintenance: a survey of empirical research. Annals of Software Engineering I, J. C. Baltzer AG, Science Publishers, 1995, 1--22.Google Scholar
- Kitchenham, B., Pfleeger, S. L., Software Quality: The Elusive Target. IEEE Software, 13, 1, 1996, 12--21. Google ScholarDigital Library
- Li, P. L., et al., Selecting a defect prediction model for maintenance resource planning and software insurance. Proceedings of the Fifth International Workshop on Economics-driven Software Engineering Research, Oregon (USA), 2003.Google Scholar
- Neil, M., Fenton N., Improved Software Defect Prediction. European SEPG Conference, London (UK), 2005.Google Scholar
- Oman, P., Hagemeister, J., Constructing and testing of Polynomials Predicting Software Maintainability. Journal of Systems and Software, 24, 3, March, 1994. Google ScholarDigital Library
- Reliability Analysis Center, Introduction to Software Reliability: A State of the Art Review. Reliability Analysis Center (RAC), 1996.Google Scholar
- Sassenburg, H., Design of a Methodology to Support Software Release Decisions: Do the Numbers really Matter? PhD thesis, University of Groningen (The Netherlands), 2006.Google Scholar
- Xie, M., Software Reliability Modeling. Singapore. World Scientific, 1991.Google Scholar
Index Terms
- Optimal release time: numbers or intuition?
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