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A Comparison of Function Point Counting Techniques
May 1993 (vol. 19 no. 5)
pp. 529-532

Effective management of the software development process requires that management be able to estimate total development effort and cost. One of the fundamental problems associated with effort and cost estimation is the a priori estimation of software size. Function point analysis has emerged over the last decade as a popular tool for this task. Criticisms of the method that relate to the way in which function counts are calculated and the impact of the processing complexity adjustment on the function point count have arisen. SPQR/20 function points among others are claimed to overcome some of these criticisms. The SPQR/20 function point method is compared to traditional function point analysis as a measure of software size in an empirical study of MIS environments. In a study of 64 projects in one organization it was found that both methods would appear equally satisfactory. However consistent use of one method should occur since the individual counts differ considerably.

[1] A. J. Albrecht, "Measuring application development productivity," inProc. Joint SHARE/GUIDE/IBM Application Development Symp., Oct. 1979, pp. 83-92.
[2] A. J. Albrecht,AD/M Estimating and Productivity Measurement Guidelines, IBM Corp. Information Systems, 1984.
[3] A. J. Albrecht and J. E. Gaffney, "Software function, source lines of code and development effort prediction: A software science validation,"IEEE Trans. Software Eng., vol. SE-9, no. 6, pp. 639-648, Nov. 1983.
[4] B. W. Boehm,Software Engineering Economics. Englewood Cliffs, NJ: Prentice-Hall, 1981.
[5] S.D. Conte, H.E. Dunsmore, and V.Y. Shen,Software Engineering: Metrics and Models, Benjamin/Cummings, Menlo Park, Calif., 1986.
[6] Development Centre Productivity Guide, IBM, Middlesex, England, 1984.
[7] D. R. Jeffery, "The relationship between team size, experience and attitudes and software development productivity," inProc. IEEE COMPSAC 87, Tokyo, Japan, Oct., 1987, pp. 2-8.
[8] D.R. Jeffery and G. Low, "Calibrating estimation tools for software development,"Software Eng. J., pp. 215-221, July 1990.
[9] T. C. Jones, "A short history of function points and feature points," Software Productivity Reserch Inc., 1988.
[10] C. H. Hull and N. H. Nie,SPSS Update 7-9, New York: McGraw-Hill, 1981, p. 224.
[11] C.F. Kemerer, "An empirical validation of software cost estimation models,"Commun. ACM, vol. 30, no. 5, pp. 416-429, May 1987.
[12] G. Keppell,Design and Analysis: A Researchers Handbook. Englewood Cliffs. NJ: Prentice-Hall, 1982. pp. 96-99.
[13] G. C. Low and D. R. Jeffery, "Function points in the estimation and evaluation of the software process,"IEEE Trans. Software Eng., vol. 16, no. 1, pp. 64-71, Jan. 1990.
[14] G. C. Low and D. R. Jeffery, "Productivity issues in the use of current back-end CASE tools," inProc. 3rd Int. Workshop CASE, CASE 89, IEEE and BCS, London, England, July 1989, pp. 12-38.
[15] C. R. Symons, "Function point analysis: Difficulties and improvements,"IEEE Trans. Software Eng., vol. 14, no. 1, pp. 2-11, 1988.
[16] J. Verner, G. Tate, B. Jackson, and R. Hayward, "Technology dependence in function point analysis: A case study and critical review," Dep. Comput. Sci., Massey Univ. Sept., 1988.

Index Terms:
function point counting techniques; software development process; a priori estimation; software size; processing complexity adjustment; SPQR/20 function points; DP management; project management; software engineering
Citation:
D.R. Jeffery, G.C. Low, M. Barnes, "A Comparison of Function Point Counting Techniques," IEEE Transactions on Software Engineering, vol. 19, no. 5, pp. 529-532, May 1993, doi:10.1109/32.232016
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