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Methodology for Validating Software Metrics
May 1992 (vol. 18 no. 5)
pp. 410-422

A comprehensive metrics validation methodology is proposed that has six validity criteria, which support the quality functions assessment, control, and prediction, where quality functions are activities conducted by software organizations for the purpose of achieving project quality goals. Six criteria are defined and illustrated: association, consistency, discriminative power, tracking, predictability, and repeatability. The author shows that nonparametric statistical methods such as contingency tables play an important role inevaluating metrics against the validity criteria. Examples emphasizing the discriminative power validity criterion are presented. A metrics validation process is defined that integrates quality factors, metrics, and quality functions.

[1] A. J. Albrecht and J. E. Gaffney, Jr., "Software function, source lines of code, and development error prediction: a software science validation,"IEEE Trans. Software Eng., vol. SE-9, pp. 639-648, Nov. 1983.
[2] A. L. Bakeret al., "A philosophy for software measurement,"J. Syst. Software, vol. 12, no. 3, pp. 277-281, July 1990.
[3] V. R. Basili, R. W. Selby, Jr., and T.-Y. Phillips, "Metric analysis and data validation across Fortran proiects,"IEEE Trans. Software Eng., vol. SE-9, pp. 652-663, Nov. 1983.
[4] V. R. Basili, and D. H. Hutchens, "An empirical study of a syntactic complexity family,"IEEE Trans. Software Eng., vol. SE-9, pp. 664-672, Nov. 1983.
[5] V.R. Basili and H.D. Rombach, "The Tame Project: Towards Improvement-Oriented Software Environments,"IEEE Trans. Software Eng., Vol. SE-14, No. 6, June 1988, pp. 758-773.
[6] M. E. Bush and N. E. Fenton, "Software measurement: a conceptual framework,"J. Syst. Software, vol. 12, no. 3, pp. 223-231, July 1990.
[7] D. N. Card, G. T. Page, and F. E. McGarry, "Criteria for software modularization," inProc. 8th Int. Conf. on Software Eng., Aug. 1985, pp. 372-377.
[8] W. J. Conover,Practical Nonparametric Statistics. New York: Wiley, 1971.
[9] Conte, S.D. et al. 1986.Software Engineering Metrics and Models. Menlo Park, Calif., Benjamin/Cummings.
[10] L. Felician and G. Zalateu, "Validating Halstead's theory for Pascal programs,"IEEE Trans. Software Eng., vol. 15, pp. 1630-1632, Dec. 1989.
[11] N. E. Fenton and A. Melton, "Deriving structurally based software metrics,"J. Syst. Software, vol. 12, no. 3, pp. 177-187, July 1990.
[12] J. D. Gibbons,Nonparametric Statistical Inference. New York: McGraw-Hill, 1971.
[13] IEEE Standard for a Software Quality Metrics Methodology(draft), no. P-1061/D21, Apr. 1, 1990.
[14] IEEE Standard Glossary of Software Engineering Terminology, ANSI/ IEEE Std. 729-1983.
[15] IEEE Glossary of Software Engineering Terminology(draft), no. P729/610.12/D8, Mar. 30, 1990.
[16] A. A. Porter and R. W. Selby, "Empirically guided software development using metric-based classification trees,"IEEE Software, vol. 7, no. 2, pp. 46-54, Mar. 1990.
[17] E. J. Weyuker, "Evaluating software complexity measures,"IEEE Trans. Software Eng., vol. 14, pp. 1357-1365, Sept. 1988.

Index Terms:
software metrics; comprehensive metrics validation methodology; validity criteria; quality functions; software organizations; project quality goals; discriminative power; tracking; predictability; repeatability; nonparametric statistical methods; contingency tables; discriminative power validity criterion; metrics validation process; program verification; quality control; software metrics; software reliability
N.F. Schneidewind, "Methodology for Validating Software Metrics," IEEE Transactions on Software Engineering, vol. 18, no. 5, pp. 410-422, May 1992, doi:10.1109/32.135774
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