A Quantity Model for Controlling and Measuring Software Quality Based on the Expert Decision-Making Algorithm

Che-Wei CHANG, Der-Juinn HORNG, Hung-Lung LIN

.

DOI: 10.4236/iim.2009.12013                

Abstract

Researchers have been active in the field of software engineering measurement over more than 30 years. The software quality product is becoming increasingly important in the computerized society. Target setting in software quality function and usability deployment are essential since they are directly related to development of high quality products with high customer satisfaction. Software quality can be measured as the degree to which a particular software program complies with consumer demand regarding function and characteristics. Target setting is usually subjective in practice, which is unscientific. Therefore, this study proposes a quantity model for controlling and measuring software quality via the expert decision-making algorithm-based method for constructing an evaluation method can provide software in relation to users and purchasers, thus enabling administrators or decision makers to identify the most appropriate software quality. Importantly, the proposed model can provide s users and purchasers a reference material, making it highly applicable for academic and government purposes.

Keywords

software quality characteristics, software quality model, multiple criteria decision making (MCDM), analytic hierarchy process (AHP)

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	H. Aras, S. Erdogmus, and E. Koc, “Multi-criteria selection for a wind observation station location using analytic hierarchy process,” Renewable Energy, Vol. 29, 2004, pp. 1383–1392.
[2]	V. Belton and T. J. Stewart, “Multiple criteria decision analysis: An integrated approach,” Kluwer Academic Publishers, Boston, 2002.
[3]	G. P. Cesar, M. Tom, and H. S. Brian, “A Metamodel for assessable software development methodologies,” Software Quality Journal, Vol. 13, No. 2, pp. 195–214, 2005.
[4]	C. W. Chang, C. R. Wu, and H. L. Lin, “Evaluating the digital video recorder systems using analytic hierarchy and analytic network processes,” Information Sciences, Vol. 177, No. 16, pp. 3383–3396, 2007.
[5]	C. W. Chang, C. R. Wu, and H. L. Lin, (2007b), “Integrating fuzzy theory and hierarchy concepts to evaluate software quality,” Software Quality Journal, Published online, Vol. 11, No. 27, 2007.
[6]	C. W. Chang, C. R. Wu, and H. L. Lin, “Group decision-making in a multiple criteria environment—A case using the AHPGR model to assess digital video recorder systems,” Journal of Testing and Evaluation, Vol. 36, No. 2, pp. 583–589, 2008.
[7]	P. F. Hsu and B.-Y. Chen, “Developing and implementing a selection model for bedding chain retail store franchisee using Delphi and fuzzy AHP,” Quality and Quantity, Vol. 41, No. 2, pp. 275–290, 2007.
[8]	ISO/IEC9126-1, “Software engineering-product quality- Part1: Quality model,” 2001.
[9]	G. Issac, C. Rajendran, and R. N. Anantharaman, “An instrument for the measurement of customer perceptions of quality management in the software industry: An empirical study in India,” Software Quality Journal, Vol. 14, No. 4, pp. 291–308, 2005.
[10]	L. S. Jose and H. Ines, “An AHP-based methodology to rank critical success factors of executive information systems,” Computer Standards and Interfaces, Vol. 28, pp. 1–12, 2005.
[11]	R. Kazman, L. Bass, M. Klein, T. Lattanze, and L. Northrop, “A Basis for Analyzing Software Architecture Analysis Methods,” Software Quality Journal, Vol. 13, No. 4, pp. 329–355, 2005.
[12]	T. M. Khoshgoftaar, A. Herzberg, and N. Seliya, “Resource oriented selection of rule-based classification models: An empirical case study,” Software Quality Journal, Vol. 14, No. 4, pp. 309–338, 2006.
[13]	T. M. Khoshgoftaar, N. Seliya, and N. Sundaresh, “An empirical study of predicting software faults with case- based reasoning,” Software Quality Journal, Vol. 14, No. 2, pp. 85–111, 2006.
[14]	L. Z. Lin, and T. H. Hsu, “The qualitative and quantitative models for performance measurement systems: The agile service development,” Quality & Quantity, Vol. 42, No. 4, pp. 445–476, 2008.
[15]	F. Liu, K. Noguchi, A. Dhungana, A. V. V. N. S. N. Srirangam, and P. Inuganti, “A quantitative approach for setting technical targets based on impact analysis in software quality function deployment,” Software Quality Journal, Vol. 14, No. 2, pp. 113–134, 2005.
[16]	M. Mollaghasemi and J. Pet-Edwards, “Making multiple- objective decisions,” Los Alamitos, IEEE Computer Society Press, CA, 1997.
[17]	T. Rafla, P. N. Robillard, and M. C. Desmarais, (2007), “A method to elicit architecturally sensitive usability requirements: Its integration into a software development process,” Software Quality Journal, Vol. 15, No. 2, pp. 117–133.
[18]	T. L. Saaty, (1980), “The analytic hierarchy process,” McGraw Hill, New York, NY.
[19]	E. Tolgaa, M. L. Demircana, and C. Kahraman, “Operating system selection using fuzzy replacement analysis and analytic hierarchy process,” International Journal of Production Economics, Vol. 97, pp. 89–117, 2005.
[20]	C. R. Wu, C. W. Chang, and H. L. Lin, “FAHP sensitivity analysis for measurement nonprofit organizational performance,” Quality & Quantity, Vol. 42, No. 3, pp. 283–302, 2008.