Abstract
Software quality processes can be assessed with the Orthogonal Defect Classification COnstructive QUALity MOdel (ODC COQUALMO) that predicts defects introduced and removed, classified by ODC types. Using parametric cost and defect removal inputs, static and dynamic versions of the model help one determine the impacts of quality strategies on defect profiles, cost and risk. The dynamic version provides insight into time trends and is suitable for continuous usage on a project. The models are calibrated with empirical data on defect distributions, introduction and removal rates; and supplemented with Delphi results for detailed ODC defect detection efficiencies. This work has supported the development of software risk advisory tools for NASA flight projects. We have demonstrated the integration of ODC COQUALMO with automated risk minimization methods to design higher value quality processes, in shorter time and with fewer resources, to meet stringent quality goals on projects.
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References
Chulani, S., Boehm, B.: Modeling software defect introduction and removal: COQUALMO (COnstructive QUALity MOdel), University of Southern California Center for Software Engineering, USC-CSE Technical Report 99-510 (1999)
Boehm, B., Abts, C., Brown, A., Chulani, S., Clark, B., Horowitz, E., Madachy, R., Reifer, D., Steece, B.: Software Cost Estimation with COCOMO II. Prentice-Hall, Englewood Cliffs (2000)
Biffl, S., Aurum, A., Boehm, B., Erdogmus, H., Grünbacher, P. (eds.): Value-Based Software Engineering. Springer, Heidelberg (2005)
Boehm, B.: Software Engineering Economics. Prentice-Hall, Englewood Cliffs (1981)
Chillarege, R., Bhandari, I., Chaar, J., Halliday, M., Moebus, D., Ray, B., Wong, M.: Orthogonal Defect Classification - A Concept for In-Process Measurements. IEEE Transactions on Software Engineering 18(11), 943–956 (1992)
Lutz, R., Mikulski, I.: Final Report: Adapting ODC for Empirical Analysis of Pre-Launch Anomalies, version 1.2, NASA Jet Propulsion Laboratories, JPL Caltech report (2003)
Madachy, R.: Risk Model Calibration Report, USC Center for Systems and Software Engineering, Report to NASA AMES (2006)
Madachy, R.: JPL Delphi Survey for V&V Defect Detection Efficiencies, USC Center for Systems and Software Engineering, Report to NASA (2006)
Madachy, R.: Calibration of ODC COQUALMO to Predict V&V Effectiveness, USC Center for Systems and Software Engineering, Report to NASA AMES (2007)
Madachy, R.: Software Process Dynamics. IEEE-Wiley, Hoboken (2008)
Menzies, T., Richardson, J.: XOMO: Understanding Development Options for Autonomy. In: 20th International Forum on COCOMO and Software cost Modeling, USC (2005)
Port, D., Kazman, R., Polo, B., Nakao, H., Katahira, M.: Practicing What is Preached: 80-20 Rules for Strategic IV&V Assessment, Center for Strategic Software Engineering, Technical Report, CSSE-TR20051025, University of Hawaii at Manoa (2005)
Feather, M., Cornford, S.: Quantitative Risk-based Requirements Reasoning. Requirements Engineering 8(4), 242–265 (2005)
Feather, M., Cornford, S., Hicks, K., Johnson, R.: Applications of Tool Support for Risk-informed Requirements Reasoning. Computer Systems Science and Engineering 20(1), 5–17 (2005)
Madachy, R., Boehm, B., Richardson, J., Feather, M., Menzies, T.: Value-Based Design of Software V&V Processes for NASA Flight Projects. In: AIAA Space 2007 Conference (2007)
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Madachy, R., Boehm, B. (2008). Assessing Quality Processes with ODC COQUALMO. In: Wang, Q., Pfahl, D., Raffo, D.M. (eds) Making Globally Distributed Software Development a Success Story. ICSP 2008. Lecture Notes in Computer Science, vol 5007. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79588-9_18
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DOI: https://doi.org/10.1007/978-3-540-79588-9_18
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