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Early Stage Software Reliability Modeling using Requirements and Object-Oriented Design Metrics: Fuzzy Logic Perspective

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Syed Wajahat A. Rizvi, Raees Ahmad Khan, Vivek Kumar Singh

Syed Wajahat A Rizvi, Raees Ahmad Khan and Vivek Kumar Singh. Early Stage Software Reliability Modeling using Requirements and Object-Oriented Design Metrics: Fuzzy Logic Perspective. International Journal of Computer Applications 162(2):44-59, March 2017. BibTeX

	author = {Syed Wajahat A. Rizvi and Raees Ahmad Khan and Vivek Kumar Singh},
	title = {Early Stage Software Reliability Modeling using Requirements and Object-Oriented Design Metrics: Fuzzy Logic Perspective},
	journal = {International Journal of Computer Applications},
	issue_date = {March 2017},
	volume = {162},
	number = {2},
	month = {Mar},
	year = {2017},
	issn = {0975-8887},
	pages = {44-59},
	numpages = {16},
	url = {},
	doi = {10.5120/ijca2017913290},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


In the current scenario as the influence of information technology has been rising day by day, the industry is facing the pressure of developing software with higher level of reliability. Generally it is an accepted fact that the roots of unreliability lies in ill defined requirements and design documents. With this spirit, researcher has proposed and implemented a reliability prediction model through fuzzy inference system that utilizes early stage product based measures from requirements and object-oriented design stages. The study starts with the review findings those have been used as foundation for proposing a reliability quantification framework. Subsequently this framework has implemented in the form of reliability prediction model that predicts reliability at the requirements as well as design level through its output variable. The model has been validated as well as quantitatively compared with two existing reliability models. The obtained results are quite encouraging and supports that the proposed framework and reliability prediction model are better. Consideration of requirements phase along with the object-oriented design provides this paper an edge over other similar studies those are based on only design phase. Because ignoring requirements deficiencies and only concentrating on design constructs will not help in developing reliable software.


  1. Dalal, S. R., Lyu, M. R., and Mallows, C. L. 2014. Software Reliability. John Wiley & Sons.
  2. Pandey, A. K., and Goyal, N. K. 2013. Early Software Reliability Prediction. Springer, India.
  3. Okutan, and Yildiz, O.T. 2014. Software Defect Prediction using Bayesian Networks. Empirical Software Engineering, 19(1), 154-181.
  4. Ogheneovo, E. E. 2014. Software Dysfunction: Why Do Software Fail?. Journal of Computer and Communications, 2, 25-35.
  5. Yadav, D. K., Charurvedi, S. K., and Mishra, R. B. 2012. Early Software Defects Prediction using Fuzzy Logic. International Journal of Performability Engineering, 8(4), 399-408.
  6. Yadav, H. B., and Yadav, D. K. 2014. Early Software Reliability Analysis using Reliability Relevant Software Metrics. International Journal of System Assurance Engineering and Management, pp.1-12.
  7. Bowles, J.B., and Pelaez, C.E. 1995. Application of fuzzy logic to reliability engineering. Proceedings of IEEE, 83(3), 435–449.
  8. Rizvi, S.W.A. and Khan, R.A. 2013. Improving Software Requirements through Formal Methods. International Journal of Information and Computation Technology, 3(11), 1217-1223.
  9. Ying, M., Shunzhi, Z., Ke, Q., and Guangchun, L. 2014. Combining the requirement information for software defect estimation in design time. Information Processing Letters, 114(9), 469–474.
  10. Catal, C. 2011. Software Fault Prediction:A Literature Review and Current Trends. Expert System with Applications, 38(4), 4626-4636.
  11. Catal, C., and Diri, B. 2009. A Systematic Review of Software Fault Predictions Studies. Expert System with Applications, 36(4), 7346-7354.
  12. Radjenovic, D., Hericko, M., Torkar, R., and Zivkovic, A. 2013. Software Fault Prediction Metrics: A Systematic Literature Review. Information and Software Technology, 55(8), 1397-1418.
  13. Mizuno, O. and Hata, H. 2009. Yet another Metric for Predicting Fault-Prone Modules. Advances in Software Engineering Communications in Computer and Information Science, Springer, 59, 296-304.
  14. He, Z., Shu, F., Yang,Y., Li, M., and Wang, Q. 2012. An Investigation on the Feasibility of Cross-Project Defect Prediction. Journal of Automated Software Engineering, 19(2), 167-199.
  15. Maa, Y., Zhua, S., Qin, K. and Luo, G. 2014. Combining the Requirement Information for Software Defect Estimation in Design Time. Information Processing Letters, 114(9), 469-474.
  16. Rizvi, S. W. A., and Khan, R. A. 2010. Maintainability Estimation Model for Object-Oriented Software in Design Phase (MEMOOD). Journal of Computing, 2(4), 26-32.
  17. Rizvi, S.W.A., Singh, V.K. and Khan, R.A. 2016. Software Reliability Prediction using Fuzzy Inference System: Early Stage Perspective, International Journal of Computer Applications, 145(10), 16-23.
  18. Rizvi, S. W. A., Singh, V. K., and Khan, R. A. 2016. The State of the Art in Software Reliability Prediction: Software Metrics and Fuzzy Logic Perspective. Advances in Intelligent Systems and Computing, Springer, 433, 629-637.
  19. Jaiswal, G.P. and Giri, R. N. 2015. A Fuzzy Inference Model for Reliability Estimation of Component Based Software System. International Journal of Computer Science and Technology, 3(3), 177-182.
  20. Kumar, A. and Dhanda, N. 2015. Reliability Estimation of Object-oriented Software: Design Phase Perspective. International Journal of Advanced Research in Computer and Communication Engineering, 4(3), 573-577.
  21. Yadav, A., and Khan, R. A. 2012a. Reliability Quantification of an Object-Oriented Design: Complexity Perspective. Proceedings of the Second International Conference on Computer Science, Engineering and Applications (ICCSEA 2012), May 25-27, 2012, New Delhi, Advances in Intelligent and Soft Computing, Springer, 166, 577-585.
  22. Kong, W. 2009. Towards a Formal and Scalable Approach for Quantifying Software Reliability at Early Development Stages. Ph.D. Thesis University of Maryland.
  23. Hooshmand, A. and Isazadeh, A. 2008. Software Reliability Assessment Based on a Formal Requirements Specification, Proceedings of the Conference on Human System Interactions, Publisher IEEE Krakow, Poland, 311-316.
  24. Rizvi, S.W.A., Singh, V. K., and Khan, R. A. 2016. Fuzzy Logic based Software Reliability Quantification Framework: Early Stage Perspective (FLSRQF), Elsevier Procedia-Computer Science, 89, 359-368.
  25. Dromey, R.G. 1995. A Model for Software Product Quality. IEEE Transactions on Software Engineering, 21(2), 146-162.
  26. McCall, J.A., Richards, P.K., Walters, G.F. 1977. Factors in software quality, RADC (Rome: Rome Air Development Center), TR-77-369.
  27. Dromey, R.G. 1996. Concerning the Chimera. IEEE Software. 1, 33-43.
  28. Boehm, B.W. 1987. Improving Software Productivity. IEEE Computer, 20(9), 43-57.
  29. ISO, 2001. ISO/IEC 9126-1: Software Engineering- Product Quality –Part I: Quality Model. Geneva, Switzerland.
  30. He, P., Li, B., Liu, X., Chen, J., and Ma, Y. 2015. An Empirical Study on Software Defect Prediction with a Simplified Metric Set. Information and Software Technology, 59, 170-190.
  31. Li, M., and Smidts, C. 2003. A ranking of software engineering measures based on expert opinion. IEEE Transaction on Software Engineering, 29(9), 811–824.
  32. Martin, N., Fenton, N., and Nielson, L. 2000. Building large-scale Bayesian networks. The Knowledge Engineering review, 15(3), 257–284.
  33. Rizvi, S. W. A., and Khan, R. A. 2009. A Critical Review on Software Maintainability Models. Proceedings of the Conference on Cutting Edge Computer and Electronics Technologies, 144-148.
  34. Bansiya, J., and Devis, C. 1997. Automated Metrics for Object-Oriented Development. Dr. Dobb’s Journal, 272(12), 42-48.
  35. Bansiya, J., and Devis, C. 2002. A Hierarchical Model for Object-Oriented Design Quality Assessment. IEEE Transactions on Software Engineering, 28(1), 4-17.
  36. Birkmeier, D. Q. 2010. On the State of the Art of Coupling and Cohesion Measures for Service-Oriented System Design metrics. Proceedings of Conference on Information Systems (AMCIS), 1-10.
  37. Breesam, K. M. 2007. Metrics for Object-Oriented Design Focusing on Class Inheritance Metrics. 2nd International Conference on Dependability of Computer Systems, June 14-16, 2007, IEEE Computer Society, 231-237.
  38. Dallal, J. A. 2010. Mathematical Validation of Object-Oriented Class Cohesion Metrics. International Journal of Computers, 4(2), 45-52.
  39. Gray, C. L. 2008. A Coupling Complexity Metric Suit for Predicting Software Quality. Thesis submitted to Polytechnic State University, California, 1-71.
  40. Yadav A. and Khan R.A. 2012b. Development of Encapsulated Class Complexity Metric, International Conference on Computer, Communication, Control and Information Technology (CCCIT-2012), Procedia Technology, pp. 754-760.
  41. Yadav, A., and Khan, R. A. 2011. Class Cohesion Complexity Metric (C3M). Proceedings of International Conference on Computer and Communication Technology (ICCCT-2011), 363-366.
  42. Yong, C., and Qingxin, Z. 2008. Improved Metrics for Encapsulation Based on Information Hiding. 9th International Conference for Young Computer Scientists, IEEE computer society, 742-724.
  43. Yadav, A. and Khan, R.A. 2009b. Measuring Design Complexity–An Inherited Method Perspective. ACM Software Engineering Notes, 34(4), 1-5.
  44. Ross, T. J. 2010. Fuzzy Logic with Engineering Applications. 3rd Edition, John Wiley and sons.
  45. Yadav, O.P., Singh, N., Chinnam, R.B. and Goel, P.S. 2003. A fuzzy logic based approach to reliability improvement during product development. Reliability Engineering and System Safety, 80(1), 63–74.
  46. Zadeh, L.A. 1989. Knowledge representation in fuzzy logic. IEEE Transactions on Knowledge and Data Engineering, 1(1), 89–100.
  47. Zhang, X. and Pham, H. 2000. An analysis of factors affecting software reliability. Journal of Systems and Software, 50(1), 43–56.
  48. Mamdani, E. H. 1977. Applications of fuzzy logic to approximate reasoning using linguistic synthesis. IEEE Transaction on Computers, 26(12), 1182–1191.
  49. Walkerden, F., and Jeffery, R. 1999. Analogy, Regression and Other Methods for Estimating Effort and Software Quality Attributes. Proceeding of European Conference Optimizing Software Development and Maintenance, 37-46.
  50. Conte, S. D., Dunsmore, H. F., and Shen, V. Y. 1986. Software Engineering Metrics and Models. ISBN: 0805321624, Benjamin Cummings Publishing Co., Inc., Redwood city, CA, USA.
  51. Kitchenham, B.A., Pickard, L.M., MacDonell, S.G. and Shepperd, M.J. 2001. What Accuracy Statistics Really Measure. IEEE Software, 148(3), 81–85.


Software Requirements, Software Reliability, Fuzzy Logic, Early Reliability Prediction, Object-oriented Design, Software Reliability Model.