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Validation of object oriented metrics using open source software system: an empirical study

Published: 27 January 2012 Publication History

Abstract

In today's environment the relevance of Free Open Source Software Systems is understood and appreciated both in academia and research. The debate about the pros and cons of the open source vis-à-vis proprietary software has been raging from ages ever since Richard Stallman founded the Free Software Foundation in 1985. With the changing trends in the domain of Object Oriented Systems there is a need to measure the fault predictability of software metrics on open source software systems. In this paper we present the results of empirical study which was conducted using open source software, JHotDraw 7.5.1. We computed the object oriented metrics, proposed by Chidamber and Kemmerer, and performed bug- class mapping for the software under study. We also studied the relationship between the revisions made to open source software and its software metrics measure.

References

[1]
V. R. Basili, L. Briand, and W. L. Melo, "A validation of object-oriented design metrics as quality indicators," IEEE Transactions on Software Engineering, vol. 22, pp. 751--761, 1996.
[2]
R. Subramanyam, M.S. Krishnan, "Empirical Analysis of CK Metrics for Object-Oriented Design Complexity: Implications for Software Defects," IEEE Transaction on Software Engineering, vol. 29, no. 4, pp. 297--310, 2003.
[3]
S.R. Chidamber, D.P. Darcy, C.F. Kemerer, " Managerial Use of Metrics for Object Oriented Software: An Exploratory Analysis," IEEE Transacion on Software Engineering, vol. 24 no. 8, pp. 629--639, 1998.
[4]
L.C. Briand, W.L. Melo, J. Wüst, "Assessing the Applicability of Fault-Proneness Models Across Object-Oriented Software Projects," IEEE Transaction on Software Engineering, vol. 28 no. 7, pp. 706--720, 2002.
[5]
H.M. Olague, L.H. Etzkorn,S. Gholston, S. Quattlebaum, "Empirical Validation of Three Software Metrics Suites to Predict Fault-Proneness of Object-Oriented Classes Developed Using Highly Iterative or Agile Software Development Processes," IEEE Transaction on Software Engineering, vol. 33 no. 6, pp. 402--419, 2007.
[6]
S. R. Chidamber and C. F. Kemerer, "A metrics suite for object oriented design," IEEE Trans. Software Eng., vol. 20, no. 6, pp. 476--493, 1994.
[7]
T. Gyimóthy, R. Ferenc, I. Siket, "Empirical Validation of Object-Oriented Metrics on Open Source Software for Fault Prediction," IEEE Transaction on Software Engineering, vol. 31 no. 10, pp. 897--910, 2005.
[8]
T. Zimmermann, R. Premraj, A. Zellar, "Predicting Defects for Eclipse," In: 3rd International Workshop on Predictor Models in Software Engineering, PROMISE'07. 2007.
[9]
N.E. Fenton, M. Neil, "Software Metrics: Successes, failures and new directions," Journal of System and Software, vol. 47, issue 2-3, pp. 149--157, 1999.
[10]
M. Marian, L. Moonen, A. van Deursen, "A Classification of Crosscutting Concern," In: 21st IEEE International Conference on Software Maintenance, ICSM'05, pp. 673--676, 2005.
[11]
G. Canfora, L. Cerulo, M. Di Penta, "On the use of Line Co-change for Idenifying Crosscutting Concern Code," In: 22nd IEEE International Conference on Software Maintenance, ICSM'06, pp. 213--222, 2006.
[12]
JhotDraw 7, http://www.randelshofer.ch/oop/JhotDraw/Documentation/index.html
[13]
Open source software, www.sourceforge.net
[14]
Ckjm-1.9, http://www.spinellis.gr/sw/ckjm/doc/index.html
[15]
Metrics 1.3.6, http://metrics.sourceforge.net/

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    Published In

    cover image ACM SIGSOFT Software Engineering Notes
    ACM SIGSOFT Software Engineering Notes  Volume 37, Issue 1
    January 2012
    115 pages
    ISSN:0163-5948
    DOI:10.1145/2088883
    Issue’s Table of Contents

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 27 January 2012
    Published in SIGSOFT Volume 37, Issue 1

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    Author Tags

    1. bug mapping
    2. empirical study
    3. object oriented metrics
    4. open source software system
    5. revision

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