article

Component Point: A system-level size measure for Component-Based Software Systems

Authors:

Thareendhra Wijayasiriwardhane,

Richard LaiAuthors Info & Claims

Journal of Systems and Software, Volume 83, Issue 12

Pages 2456 - 2470

https://doi.org/10.1016/j.jss.2010.07.008

Published: 01 December 2010 Publication History

Abstract

System-level size measures are particularly important in software project management as tasks such as planning and estimating the cost and schedule of software development can be performed more accurately when a size estimate of the entire system is available. However, due to the black-box nature of components, the traditional software measures are not adequate for Component-Based Software Systems (CBSS). In this paper, we describe a Function Point-like measure, named Component Point (CP), for measuring the system-level size of a CBSS specified in the Unified Modelling Language. Our approach integrates three software measures and extends an existing size measure from the more matured Object-Oriented paradigm to the related and relatively young CBSS discipline. We then apply the proposed measure to a Global Positioning System and demonstrate its viability in sizing a CBSS. An empirical analysis is also provided in order to prove the validity and usefulness of the CP measure.

References

[1]

Standish Group, 2004 Third Quarter Research Report. 2004. Standish Group International, Inc.

[2]

Humphrey, W.S., Managing the Software Process. 1989. Addison-Wesley, Boston, MA.

[3]

Fenton, N.E., Software Metrics: A Rigorous Approach. 1991. Chapman & Hall, London.

[4]

Humphrey, W.S., A Discipline for Software Engineering. 1995. Addison-Wesley, Boston, MA.

[5]

Fenton, N.E. and Pfleeger, S.L., Software Metrics: A Rigorous and Practical Approach. 1998. PWS, Boston, MA.

[6]

Putnam, L.H., A general empirical solution to the macro software sizing and estimating problem. IEEE Transactions on Software Engineering. v4 i4. 345-361.

[7]

Boehm, B.W., Software Engineering Economics. 1981. Prentice Hall PTR, Upper Saddle River, NJ.

[8]

Albrecht, A.J. and Gaffney, J.E., Software function, source lines of code and development effort prediction: a software science validation. IEEE Transactions on Software Engineering. v9 i6. 639-648.

[9]

Boehm, A.W., Clark, B., Horowitz, E., Westland, C., Madachy, R. and Selby, R., Cost models for future software life cycle processes: COCOMO 2.0. Annals of Software Engineering. v1 i1. 57-94.

[10]

Jones, C., Applied Software Measurement: Assuring Productivity and Quality. 1996. 2nd ed. McGraw-Hill, Hightstown, NJ.

[11]

Shepperd, M., Schofield, C. and Kitchenham, B., Effort estimation using analogy. In: Proceedings of the 18th International Conference on Software Engineering, IEEE Computer Society, Berlin, Germany. pp. 170-178.

[12]

Shepperd, M. and Schofield, C., Estimating software project effort using analogies. IEEE Transactions on Software Engineering. v23 i11. 736-743.

[13]

Mendes, E. and Counsell, S., Web development effort estimation using analogy. In: Proceedings of the 2000 Australian Software Engineering Conference, pp. 203-212.

[14]

Wittig, G. and Finnie, G., Estimating software development effort with connectionist models. Information and Software Technology. v39 i7. 469-476.

[15]

Tadayon, N., Neural network approach for software cost estimation. In: Proceedings of the International Conference on information Technology: Coding and Computing (ITCC'05), pp. 815-818.

[16]

Kanmani, S., Kathiravan, J., Kumar, S.S. and Shanmugam, M., Neural network based effort estimation using class points for OO systems. In: Proceedings of the International Conference on Computing: Theory and Applications, pp. 261-266.

Digital Library

[17]

DeMarco, T., An algorithm for sizing software products. ACM SIGMETRICS Performance Evaluation Review. v12 i2. 13-22.

[18]

Murali, C.S. and Sankar, C.S., Issues in estimating real-time data communications software projects. Information and Software Technology. v39 i6. 399-402.

[19]

Boehm, B.W. and Papaccio, P.N., Understanding and controlling software costs. IEEE Transactions on Software Engineering. v14 i10. 1462-1477.

[20]

Blackburn, J.D., Scudder, G.D. and Van Wassenhove, L.N., Improving speed and productivity of software development: a global survey of software developers. IEEE Transactions on Software Engineering. v22 i12. 875-885.

[21]

Banker, R.D., Kauffman, R.J. and Kumar, R., An empirical test of object-based output measurement metrics in a Computer Aided Software Engineering (CASE) environment. Journal of Management Information Systems. v8 i3. 127-150.

[22]

Chan, T., Chung, S.L. and Ho, T.H., An economic model to estimate software rewriting and replacement times. IEEE Transactions on Software Engineering. v22 i8. 580-598.

[23]

Verner, J. and Tate, G., A software size model. IEEE Transactions on Software Engineering. v18 i4. 265-278.

[24]

Cockcroft, S.K.S., Estimating CASE development size from outline specifications. Information and Software Technology. v38 i6. 391-399.

[25]

Hakuta, M., Tone, F. and Ohminami, M., A software size estimation model and its evaluation. Journal of Systems and Software. v37 i3. 253-263.

[26]

MacDonell, S.G., Software source code sizing using fuzzy logic modeling. Information and Software Technology. v45 i7. 389-404.

[27]

IFPUG, Function Point Counting Practices Manual, Release 4.1. 1999. International Function Point Users Group, Westerville, OH.

[28]

Dreger, J.B., Function Point Analysis. 1989. Prentice Hall PTR, Upper Saddle River, NJ.

[29]

Kemerer, C.F. and Porter, B.S., Improving the reliability of function point measurement: an empirical study. IEEE Transactions on Software Engineering. v18 i11. 1011-1024.

[30]

Longstreet, D.H., How are function points useful?. American Programmer. v8 i12. 25-32.

[31]

Symons, C.R., Function point analysis: difficulties and improvements. IEEE Transactions on Software Engineering. v14 i1. 2-11.

[32]

Banker, R.D., Kauffman, R.J., Wright, C. and Zweig, D., Automating output size and reuse metrics in a repository-based Computer-Aided Software Engineering (CASE) Environment. IEEE Transactions on Software Engineering. v20 i3. 169-187.

[33]

Costagliola, G., Ferrucci, F., Tortora, G. and Vitiello, G., Class point: an approach for the size estimation of object-oriented systems. IEEE Transactions on Software Engineering. v31 i1. 52-74.

[34]

Jones, C., Programming Productivity. 1985. McGraw-Hill, New York.

[35]

Abran, A., Maya, M., Desharnais, J.M. and St-Pierre, D., Adapting function points to real-time software. American Programmer. v10 i11. 32-43.

[36]

Whitmire, S.A., 3D function points: applications for object-oriented software. In: Proceedings of the Applications in Software Measurements Conference,

[37]

Minkiewicz, A.F., Measuring object oriented software with predictive object points. In: Proceedings of the Applications in Software Measurements Conference (ASM '97),

[38]

Antoniol, G., Lokan, C., Caldiera, G. and Fiutem, R., Function point-like measure for object-oriented software. Empirical Software Engineering. v4 i3. 263-287.

[39]

Reifer, D.J., Web-development: estimating quick-to-market software. IEEE Software. v17 i6. 57-64.

[40]

Cleary, D., Web-based development and functional size measurement. In: Proceedings of the IFPUG Annual Conference,

[41]

Cost Xpert Group, Estimating Internet Development. 2002. Cost Xpert Group, Inc.

[42]

Cechich, A., Piattini, M. and Vallecillo, A., . 2003. Assessing Component-Based Systems, in Component-Based Software Quality, 2003.Springer, Berlin/Heidelberg.

[43]

Ravichandran, T. and Rothenberger, M.A., Software reuse strategies and component markets. Communications of the ACM. v46 i8. 109-114.

[44]

Vitharana, P., Zahedi, F.M. and Jain, H., Design, retrieval and assembly in component-based software development. Communications of the ACM. v46 i11. 97-102.

[45]

Mahmood, S., Lai, R. and Kim, Y.S., Survey of component-based software development. IET Software. v1 i2. 57-66.

[46]

Sedigh-Ali, S., Ghafoor, A. and Paul, R.A., Software engineering metrics for COTS-based systems. IEEE Computer. v34 i5. 44-50.

[47]

Gill, N.S. and Grover, P.S., Component-based measurement: few useful guidelines. ACM SIGSOFT Software Engineering Notes. v28 i6. 1-6.

[48]

Sedigh-Ali, S., Ghafoor, A. and Paul, R.A., A metrics-guided framework for cost and quality management of component-based software. In: Cechich, A., Piattini, M., Vallecillo, A. (Eds.), Component-Based Software Quality, vol. 2693. Springer. pp. 374-402.

[49]

Mahmood, S. and Lai, R., A complexity measure for UML component-based system specification. Software - Practice & Experience. v38 i2. 117-134.

[50]

Cheesman, J., Daniels, J. and Components:, U.M.L., A Simple Process for Specifying Component Based Software. 2001. Addison-Wesley, Boston, MA.

[51]

Wijayasiriwardhane, T. and Lai, R., A method for measuring the size of a component-based system specification. In: Proceedings of the 8th International Conference on Quality Software (QSIC 2008), IEEE Computer Society Press, Oxford, United Kingdom. pp. 329-337.

Digital Library

[52]

DeMarco, T., Controlling Software Projects: Management, Measurement and Estimation. 1986. Prentice Hall, Upper Saddle River, NJ.

[53]

Ejiogu, L.O., Software Engineering with Formal Metrics. 1991. QED Information Sciences, Wellesley, MA.

[54]

Albrecht, A.J., Measuring application development productivity. In: Proceedings of the Joint SHARE/GUIDE/IBM Application Development Symposium, pp. 83-92.

[55]

Abran, A. and Robillard, P.N., Function and points: a study of their measurement processes and scale transformations. Journal of Systems and Software. v25 i2. 171-184.

[56]

Poels, G., Why function points do not work in search of new software measurement strategies. Guide Share Europe Journal. v1 i2. 9-26.

[57]

Abrahão, S., Poels, G. and Pastor, O., A functional size measurement method for object-oriented conceptual schemas: design and evaluation issues. Software and Systems Modelling. v5 i1. 48-71.

[58]

Matson, J.E., Barret, B.E. and Mellichamp, J.M., Software development cost estimation using function points. IEEE Transactions on Software Engineering. v20 i4. 275-287.

[59]

Boehm, B.W., Abts, C., Brown, A.W., Chulani, S., Clark, B.K., Horowitz, E., Madachy, R., Reifer, D.J. and Steece, B., Software Cost Estimation with COCOMO II. 2000. Prentice Hall, Upper Saddle River, NJ.

[60]

¿ivkovič, A., Rozman, I. and Heričko, M., Automated software size estimation based on function points using UML models. Information and Software Technology. v47 i13. 881-890.

[61]

Kralj, T., Rozman, I., Heričko, M. and ¿ivkovič, A., Improved standard FPA method-resolving problems with upper boundaries in the rating complexity process. Journal of Systems and Software. v77 i2. 81-90.

[62]

ISO, ISO/IEC 20926:2003, Information Technology-Software Engineering: IFPUG 4.1 Unadjusted Functional Size Measurement Method. 2003.

[63]

Symons, C.R., Come back Function Point analysis (modernised)-all is forgiven!. In: Proceedings of 4th European Conference on Software Measurement and ICT Control,

[64]

Halstead, M.H., Elements of Software Science. 1977. Elsevier Science, New York.

[65]

Kanmani, S., Kathiravan, J., Kumar, S.S. and Shanmugam, M., Class point based effort estimation of OO systems using fuzzy subtractive clustering and artificial neural networks. In: Proceedings of the First Conference on India Software Engineering Conference (ISEC'08), ACM Press, Hyderabad, India. pp. 141-142.

[66]

Symons, C., Software Sizing and Estimating: Mark II FPA, Baffin's Lane. 1991. John Wiley, United Kingdom.

[67]

UKSMA, MKII Function Point Analysis Counting Practices Manual, Version 1.3.1. 1998. United Kingdom Software Metrics Association, Edenbridge, Kent, United Kingdom.

[68]

Abran, A., Desharnais, J.M., Oligny, S., St-Pierre, D. and Symons, C., COSMIC-FFP Measurement Manual, Version 2.0. 1999. Software Engineering Management Research Laboratory, University of Quebec, Montreal, Canada.

[69]

Seker, R. and Tanik, M.M., An information-theoretical framework for modeling component-based systems. IEEE Transactions on Systems, Man and Cybernetics. v34 i4. 475-484.

[70]

Han, J., A comprehensive interface definition framework for software components. In: Proceedings of the Fifth Asia Pacific Software Engineering Conference, IEEE Computer Society, Taipei, Taiwan. pp. 110-117.

[71]

Szyperski, C., Component Software: Beyond Object-Oriented Programming. 2002. 2nd ed. Addison-Wesley, Boston, MA.

[72]

Goulão, M.A. and Abreu, F.B.E., From objects to components: a quantitative experiment. In: Proceedings of 6th European Conference on Object-Oriented Programming (ECOOP) Workshop on Quantitative Approaches in Object-Oriented Software Engineering (QAOOSE 2002),

[73]

Szyperski, C., Universe of composition. 2002. Architecture and Design, 2002.Dr Dobbs Portal.

[74]

Salman, N., Extending object oriented metrics to components. In: Proceedings of the 6th Biennial World Conference on Integrated Design and Process Technology,

[75]

Mahmood, S., Lai, R., Kim, Y.S., Kim, J.H., Park, S.C. and Oh, H.S., A survey of component based system quality assurance and assessment. Information & Software Technology. v47 i10. 693-707.

[76]

Williams, J., The business case for components. In: Heineman, G.T., Councill, W.T. (Eds.), Component-Based Software Engineering: Putting the Pieces Together, Addison-Wesley, Boston, MA. pp. 79-97.

[77]

Narasimhan, V.L. and Hendradjaya, B., Some theoretical considerations for a suite of metrics for the integration of software components. Information Sciences. v177 i3. 844-864.

[78]

Jeffery, D.R., Low, G.C. and Barnes, M., A comparison of function point counting techniques. IEEE Transactions on Software Engineering. v19 i5. 529-532.

[79]

Kemerer, C.F., An empirical validation of software cost estimation models. Communications of the ACM. v30 i5. 416-429.

[80]

Kitchenham, B.A. and Kansala, K., Inter-item correlations among function points. In: Proceedings of the 15th international conference on Software Engineering, IEEE Computer Society, Baltimore, MD. pp. 477-480.

[81]

Lokan, C.J., An empirical analysis of function point adjustment factors. Information & Software Technology. v42 i9. 649-659.

[82]

Santillo, L., ESE: enhanced software estimation. 2002. International Function Point Users Group.

[83]

Diev, S., Software estimation in the maintenance context. ACM SIGSOFT Software Engineering Notes. v31 i2. 1-8.

[84]

Abts, C., 2004. Extending the COCOMO II Software Cost Model to Estimate Effort and Schedule for Software Systems Using Commercial-Off-The-Shelf (COTS) Software Components: the COCOTS Model, vol. PhD. University of Southern California, Los Angeles, CA.

[85]

Tessier, P., Gérard, S., Mraidha, C., Terrier, F. and Geib, J., A component-based methodology for embedded system prototyping. In: Proceedings of the 14th International Workshop on Rapid Systems Prototyping (RSP'03), pp. 9-15.

[86]

Salman, N. and Doğru, A., Design effort estimation using complexity metrics. Integrated Design & Process Science. v8 i3. 83-88.

[87]

Briand, L.C., El Emam, K. and Wieczorek, I., Explaining the cost of European space and military projects. In: Proceedings of the 21st International Conference on Software Engineering (ICSE '99), ACM Press, Los Angeles, CA, United States. pp. 303-312.

[88]

Briand, L.C. and Wüst, J., Modelling development effort in object-oriented systems using design properties. IEEE Transactions on Software Engineering. v27 i11. 963-986.

[89]

Berry, W.D. and Feldman, S., Multiple Regression in Practice, Sage University Paper Series on Quantitative Applications in the Social Sciences. Series 7-050. 1985. Sage, Newbury Park, CA.

[90]

Fox, J., Regression Diagnostics, Sage University Paper Series on Quantitative Applications in the Social Sciences. Series 7-079. 1991. Sage, Newbury Park, CA.

[91]

Vesterinen, P., Issues in calibrating effort estimation models. ACM SIGSOFT Software Engineering Notes. v24 i3. 63-65.

[92]

Briand, L.C. and Wieczorek, I., Resource estimation in software engineering. In: Marciniak, J.J. (Ed.), Encyclopaedia of Software Engineering, John Wiley, New York. pp. 1160-1196.

Cited By

Melo Alves MDrummond L(2017)A multivariate and quantitative model for predicting cross-application interference in virtual environmentsJournal of Systems and Software10.1016/j.jss.2017.04.001128:C(150-163)Online publication date: 1-Jun-2017
https://dl.acm.org/doi/10.1016/j.jss.2017.04.001

Recommendations

A Method for Measuring the Size of a Component-Based System Specification
QSIC '08: Proceedings of the 2008 The Eighth International Conference on Quality Software

The system-level size measures are particularly important in software project management as tasks such as planning and estimating the cost and schedule of software development can be performed more effectively when a size estimate of the entire system ...
A Compositional Claim-based Component Certification Procedure
EUROMICRO '04: Proceedings of the 30th EUROMICRO Conference

Component-based software construction is of much interest in software engineering due to its promise of black-box composition and independent deployment. Because of this black-box nature, users of components must be concerned with their trustworthiness, ...
A mapping study to investigate component-based software system metrics

A component-based software system (CBSS) is a software system that is developed by integrating components that have been deployed independently. In the last few years, many researchers have proposed metrics to evaluate CBSS attributes. However, the ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Journal of Systems and Software

Journal of Systems and Software Volume 83, Issue 12

December, 2010

300 pages

ISSN:0164-1212

Issue’s Table of Contents

Copyright © Elsevier Inc. © 2010.

Publisher

Elsevier Science Inc.

United States

Publication History

Published: 01 December 2010

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 21 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Melo Alves MDrummond L(2017)A multivariate and quantitative model for predicting cross-application interference in virtual environmentsJournal of Systems and Software10.1016/j.jss.2017.04.001128:C(150-163)Online publication date: 1-Jun-2017
https://dl.acm.org/doi/10.1016/j.jss.2017.04.001

View Options

View options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Issue’s Table of Contents