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Reseach Article

An Algorithmic Approach to Predict Fault Propagation and Defects in Dependent Modules based on Coupling

by Kireet Joshi, Ramesh Chandra Belwal, Shailendra Mishra
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 68 - Number 12
Year of Publication: 2013
Authors: Kireet Joshi, Ramesh Chandra Belwal, Shailendra Mishra
10.5120/11635-7112

Kireet Joshi, Ramesh Chandra Belwal, Shailendra Mishra . An Algorithmic Approach to Predict Fault Propagation and Defects in Dependent Modules based on Coupling. International Journal of Computer Applications. 68, 12 ( April 2013), 40-46. DOI=10.5120/11635-7112

@article{ 10.5120/11635-7112,
author = { Kireet Joshi, Ramesh Chandra Belwal, Shailendra Mishra },
title = { An Algorithmic Approach to Predict Fault Propagation and Defects in Dependent Modules based on Coupling },
journal = { International Journal of Computer Applications },
issue_date = { April 2013 },
volume = { 68 },
number = { 12 },
month = { April },
year = { 2013 },
issn = { 0975-8887 },
pages = { 40-46 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume68/number12/11635-7112/ },
doi = { 10.5120/11635-7112 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:27:42.053001+05:30
%A Kireet Joshi
%A Ramesh Chandra Belwal
%A Shailendra Mishra
%T An Algorithmic Approach to Predict Fault Propagation and Defects in Dependent Modules based on Coupling
%J International Journal of Computer Applications
%@ 0975-8887
%V 68
%N 12
%P 40-46
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

There is an enormous amount of research going on to minimize the effect of coupling between the software modules and to reduce the defects present in them. In this paper, an algorithmic approach is proposed that gives a probability, such that the highly dependent modules in system must be analyzed by the development team for fault proneness and defects. The higher the coupling, interdependency between the modules is increased and it is alarming issue in software engineering tasks. There is an enormous amount of research done on direct and indirect coupling, but this paper approaches on the effect of coupling to predict defects and how they are propagating between the modules. Every software product is tested for defects and bugs before it is given to acceptance testing to users. The paper focuses on testing the defect propagation percentage of every module in a dependent system (dependent modules). The greater the percentage of defect propagation factor between two dependent module, implies that the coupling between them is higher and the probability of the module to be fault prone increases. Taking this into consideration, the testing team saves the time by considering more on the modules for which the percentage defect propagation factor is higher. It ensures time, cost and efficiency which are the main factors of a software industry.

References
  1. Fang Deng, James A. Jones," Weighted System Dependence Graph", 2012 IEEE Fifth International Conference on Software Testing, Verification and Validation"
  2. . Tan, Xi Sch. of Comput. Sci. , Fudan Univ. , Shanghai, China Peng, Xin, Pan, Sen, Zhao, Wenyon," Assessing Software Quality by Program Clustering and Defect Prediction", Reverse Engineering (WCRE), 2011 18th Working Conference, pp. 244 – 248, Oct. 2011, ISSN : 1095-1350
  3. Vinay Singh and Vandana Bhattacherjee," Detection of Indirect Coupling Using Chaining Method and Its Impact on Software Quality", International Journal of Research and Reviews in Information Sciences (IJRRVol. 1, No. 4, December 2011, ISSN: 2046-6439
  4. . Gonzalez-Sanchez, Alberto Software Technol. Dept. , Delft Univ. of Technol. , Delft, Netherlands Abreu, Rui, Gross, Hans-Gerhard, Van Gemund, Arjan J C," Prioritizing tests for fault localization through ambiguity group reduction", Automated Software Engineering (ASE), 2011 26th IEEE/ACM International Conference, pp. 83 – 92, 6-10 Nov. 2011, ISSN : 1938-4300
  5. . Jalbert, Kevin Software Quality Res. Group, Univ. of Ontario Inst. of Technol. , Oshawa, ON, Canada Bradbury, Jeremy S. ," Using clone detection to identify bugs in concurrent software", Software Maintenance (ICSM), 2010 IEEE International Conference, pp. 1 – 5, 12-18 Sept. 2010, ISSN : 1063-6773
  6. . Nugroho, Ariadi LIACS, Leiden Univ. , Leiden, Netherlands Chaudron, Michel R V,Arisholm, Erik," Assessing UML design metrics for predicting fault-prone classes in a Java system:, Mining Software Repositories (MSR), 2010 7th IEEE Working Conference, pp. 21 – 30, 2-3 May 2010, Print ISBN: 978-1-4244-6802-7
  7. W. E. Wong, V. Debroy and B. Choi, "A Family of Code Coverage-based Heuristics for Effective Fault Localization," Journal of Systems and Software, 83(2):188-208, February, 2010
  8. . Chen, Yuan Changchun Inst. of Opt. , Fine Mech. & Phys. , Chinese Acad. of Sci. , Changchun, China Shen, Xiang-heng, Du, Peng,Ge, Bing,"Research on software defect prediction based on data mining", Vol. 1,Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference,563 – 567, pp. 26-28 Feb. 2010, E-ISBN : 978-1-4244-5586-7
  9. . Liu Yanbin Ordnance Eng. Coll. , Shijiazhuang, China,Zhu Xiaodong,Sun Zhiming,Wang Yigang,Ye Fei," Dual-Slices Algorithm for Software Fault Localization", Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference, pp. 1 – 4, 11-13 Dec. 2009, Print ISBN: 978-1-4244-4507-3
  10. P. -N. Tan, M. Steinbach, and V. Kumar, Introduction to Data Mining. Boston, MA, USA: Addison-Wesley Longman Publishing Co. , Inc. , 2005
  11. F. Tip, "A survey of program slicing techniques, "Journal of Programming Languages,3(3):121–189, 1995
  12. M. Weiser, "Program slicing," IEEE Transactions on Software Engineering, SE-10(4):352-357, July 1984
  13. J. -D. Choi, B. P. Miller, and R. H. B. Netzer, "Techniques for debugging parallel programs with ?owback analysis," ACM Trans. Program. Lang. Syst. , vol. 13, pp. 491–530, October 1991.
  14. S. Bates and S. Horwitz, "Incremental program testing using program dependence graphs," in Symposium on Principles of Programming Languages. New York, NY, USA: ACM, 1993, pp. 384–396.
  15. S. Horwitz, T. Reps, and D. Binkley, "Interprocedural slicing using dependence graphs," ACM Trans. Program. Lang. Syst. , vol. 12, pp. 26–60, January 1990
  16. K. J. Ottenstein and L. M. Ottenstein, "The program dependence graph in a software development environment," SIGPLAN Not. , vol. 19, no. 5,pp. 177–184, 1984.
  17. Briand,L. C. , Daly,J. W. , & Wust,J. K. ,"A Unified framework for coupling measurement in object oriented system". IEEE Transact Software Engineering, (25(1): pp. 91-121, January/February 1999
  18. Yourdon. & Constantine, L. L," Structured Design: Fundamental of a discipline of computer program and system design prentice hall", 1979
  19. R. Abreu, P. Zoeteweij, and A. J. C. van Gemund, "On the accuracy ofspectrum-based fault localization," in Testing: Academic and Industrial Conference Practice and Research Techniques, 2007, pp. 89–98.
Index Terms

Computer Science
Information Sciences

Keywords

Coupling Fault detection Fault Prediction using Coupling Module Dependency Testing Strategies Fault Localization Defects Debugging