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Reseach Article

UML based Approach for System Reliability Assessment

by Bhagat Singh Rajput, Vaishali Chourey
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 131 - Number 2
Year of Publication: 2015
Authors: Bhagat Singh Rajput, Vaishali Chourey
10.5120/ijca2015907252

Bhagat Singh Rajput, Vaishali Chourey . UML based Approach for System Reliability Assessment. International Journal of Computer Applications. 131, 2 ( December 2015), 17-24. DOI=10.5120/ijca2015907252

@article{ 10.5120/ijca2015907252,
author = { Bhagat Singh Rajput, Vaishali Chourey },
title = { UML based Approach for System Reliability Assessment },
journal = { International Journal of Computer Applications },
issue_date = { December 2015 },
volume = { 131 },
number = { 2 },
month = { December },
year = { 2015 },
issn = { 0975-8887 },
pages = { 17-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume131/number2/23421-2015907252/ },
doi = { 10.5120/ijca2015907252 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:26:12.192022+05:30
%A Bhagat Singh Rajput
%A Vaishali Chourey
%T UML based Approach for System Reliability Assessment
%J International Journal of Computer Applications
%@ 0975-8887
%V 131
%N 2
%P 17-24
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Software Engineering is associated with development of software products using well defined principles, techniques and processes. The result of Software Engineering is an effective and reliable product. The software products have chances to fail during implementation and design phases. The design time testing and reliability measurement can enhance the process of development and their component management to work more effectively for long time. Software Testing is evaluation of the software product against system requirements gathered from users and system specification. That mainly comprises of validation and verification. The reliability analysis concerned with analyzing the system and their functions to get the amount of time when the system and their components works reliably. In this paper, Reliability Engineering based case study on software product development is performed. The concept of Software Engineering and the component based product development, use the Unified Modeling Language (UML) diagrams and create Reliability Block Diagram (RBD). RBDs are used to evaluate entire software components and their sub components to find their reliability according to the number of usages and increasing time factor. Therefore, to analyze the software system using RBD, UML to RBD conversion is required. The UML diagram for online shopping is first explored and then its sub use-case checkout is designed. The sub-case is then re-organized according to the functionality that can be similar to component diagram. The component diagram is used further to convert the software system into the RBD diagram. The result of RBD analysis defined in terms of Block failure rate, Block unreliability Vs. Time, Block Reliability vs. Time, System Reliability vs. Time and the System Reliability statistics. The finding of the experiments shows that the system can be improved through the RBD analysis. Additionally the improvements during the design phases can refine the productivity and reliability of the system.

References
  1. Podgurski, Andy, Wassim Masri, Yolanda McCleese, Francis G. Wolff, and Charles Yang. "Estimation of software reliability by stratified sampling." ACM Transactions on Software Engineering and Methodology 8, no. 3, pp. 263-283, 1999.
  2. Mohanta, Sirsendu, Gopika Vinod, A. K. Ghosh, and Rajib Mall. "An approach for early prediction of software reliability." ACM Sigsoft Software Engineering Notes 35, no. 6, pp. 1-9, 2010.
  3. Jalote, Pankaj, Brendan Murphy, and Vibhu Saujanya Sharma. "Post-release reliability growth in software products." ACM Transactions on Software Engineering and Methodology 17, no. 4, pp. 17, 2008.
  4. Peng, Rui, Y. F. Li, W. J. Zhang, and Q. P. Hu. "Testing effort dependent software reliability model for imperfect debugging process considering both detection and correction." Reliability Engineering & System Safety 126, pp. 37-43, 2014.
  5. Dimov, Aleksandar, Senthil Kumar Chandran, and Sasikumar Punnekkat. "How do we collect data for software reliability estimation?" In Proceedings of the 11th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing on International Conference on Computer Systems and Technologies, pp. 155-160. ACM, 2010.
  6. Fujii, Toshiya, Tadashi Dohi, and Takaji Fujiwara. "Towards quantitative software reliability assessment in incremental development processes." In Proceedings of the 33rd International Conference on Software Engineering, pp. 41-50. ACM, 2011.
  7. Pati, Jayadeep, and K. K. Shukla. "A Hybrid Technique for Software Reliability Prediction." In Proceedings of the 8th India Software Engineering Conference, pp. 139-146. ACM, 2015.
  8. Bhuyan, Manmath Kumar, Durga Prasad Mohapatra, and Srinivas Sethi. "A survey of computational intelligence approaches for software reliability prediction." ACM Sigsoft Software Engineering Notes 39, no. 2, pp. 1-10, 2014.
  9. Bird, Christian, Venkatesh-Prasad Ranganath, Thomas Zimmermann, Nachiappan Nagappan, and Andreas Zeller. "Extrinsic influence factors in software reliability: A study of 200,000 windows machines." In Companion Proceedings of the 36th International Conference on Software Engineering, pp. 205-214. ACM, 2014.
  10. Liu, Chang, Yuan Liu, Zhanyong Ren, and Haifeng Li. "Software Reliability Modelling Considering both Testing Effort and Testing Coverage." In 2015 International Symposium on Computers & Informatics. Atlantis Press, 2015.
  11. Buhnova, Barbora, Stanislav Chren, and Lucie Fabriková. "Failure data collection for reliability prediction models: a survey." In Proceedings of the 10th international ACM Sigsoft conference on Quality of software architectures, pp. 83-92. ACM, 2014.
  12. Bernardi, Simona, José Merseguer, and Dorina C. Petriu. "Dependability modeling and analysis of software systems specified with UML." ACM Computing Surveys (CSUR) 45, no. 1, pp. 2, 2012.
  13. Distefano, Salvatore, Antonio Puliafito, and Kishor S. Trivedi. "Dynamic aspects and behaviors of complex systems in performance and reliability assessment." ACM Sigmetrics Performance Evaluation Review 39, no. 4, pp. 71-78, 2012.
  14. Ubal, Rafael, Dana Schaa, Perhaad Mistry, Xiang Gong, Yash Ukidave, Zhongliang Chen, Gunar Schirner, and David Kaeli. "Exploring the heterogeneous design space for both performance and reliability." In Design Automation Conference, 2014 51st ACM/EDAC/IEEE, pp. 1-6. IEEE, 2014.
  15. Sagar, B. B., R. K. Saket, and Col Gurmit Singh. "Exponentiated Weibull distribution approach based inflection S-shaped software reliability growth model." Ain Shams Engineering Journal 2015.
  16. Tyagi, Kirti, and Arun Sharma. "Reliability of component based systems: a critical survey." ACM Sigsoft Software Engineering Notes 36, no. 6, pp. 1-6, 2011.
  17. Singh, Lalit Kumar, Gopika Vinod, and A. K. Tripathi. "Impact of change in component reliabilities on system reliability estimation." ACM Sigsoft Software Engineering Notes 39, no. 3, pp. 1-6, 2014.
  18. Hu, Hai, Chang-Hai Jiang, Kai-Yuan Cai, W. Eric Wong, and Aditya P. Mathur. "Enhancing software reliability estimates using modified adaptive testing." Information and Software Technology 55, no. 2, pp. 288-300, 2013.
  19. Allen M. Johnson Jr., Miroslaw Malek, “Survey of Software Tools for Evaluating Reliability, Availability, and Serviceability”, ACM Computing Surveys, Vol. 20, no. 4, December 1988.
Index Terms

Computer Science
Information Sciences

Keywords

Software Engineering Reliability Engineering System Testing UML RBD Blocksim Case Study.