Abstract
Bugs are inevitable in any software development life cycle. Most bugs are detected and removed in the testing phase. In software, we can classify bugs into two categories: (1) bugs of different severity, from a user's perspective,(how much damage the bug does) and (2) bugs of different complexity(how much is the debugging time lag between detection and correction). Prior knowledge of bug distribution of different complexity can help project managers in allocating testing resources and tools. Various researchers have proposed models for determining the proportion of bugs present in software of different complexity but none of these models have been applied to object oriented software. In this paper, we have proposed a model that will determine the proportion of different bug complexity. The paper also suggests the suitability of the proposed model for a particular data set. We have taken two data sets based on object oriented methodology namely SQL for Python and SQuirreL SQL Client software developed under open source environment.
- Meyer, Bertrand (1988): Object-oriented Software Construction. Prentice-Hall, New York, NY, 1988, p. 59--62. Google Scholar
Digital Library
- Binder RV: Testing object oriented software: A survey. Journal of software testing, Verification and Reliability 31996;6(3/4):125--252Google Scholar
- IEEE 729-1983: Glossary of Software Engineering Terminology, September 23, 1982.Google Scholar
- Gacek Cristina and Arief Budi (2004):The Many meanings of Open Source, IEEE Software, Vol. 21, issue Google Scholar
Digital Library
- Ruben van Wendel de Joode and Mark de Bruijne(2006): The organization of open source communities: Towards a Framework to Analyze the relationship between openness and reliability, Proceedings of 39th Hawaii International Conference on System Sciences, 2006, pp.1--6. Google Scholar
Digital Library
- Mary Paul Li, Shaw, Herbsleb Jim, Bonnie Ray, Santhanam P., Empirical Evaluation of Defect Projection Models for Widely-deployed Production Software systems, in the proceedings of the 12th International Symposium on the production of Software Engineering (FSE-12), pp.263--272. Google Scholar
Digital Library
- Tamura Y. and Yamada S., Optimization analysis for Reliability Assessment based on stochastic differential equation modeling for Open Source Software, International Journal of Systems Science, Vol. 40, No.4 , 2009, pp. 429--438. Google Scholar
Digital Library
- Zhou Ying and Davis Joseph (2005):Open Source Software Reliability Model: An empirical approach, Proceedings of the 5th WOSSE, 2005, pp. 1--6. Google Scholar
Digital Library
- Singh V.B. and P.K Kapur.(2009): Measuring Reliability Growth of Open Source Software, Accepted for poster presentation in IBM-Indian Research Laboratory Collaborative Academia Research Exchange held during October 26, 2009 at IBM India Research Lab, ISID Campus, Institutional Area, Vasant Kunj , New Delhi, India.Google Scholar
- Kapur P.K, Min Xie and Younes Said (1994): Reliability Growth Model for Object Oriented Software System, Software Testing, Reliability and Quality Assurance, Dec. 21-22 1994, pp. 148--153Google Scholar
- Kapur P.K., Younes S. and Agarwala S. (1995) "Generalized Erlang Software Reliability Growth Model with n types of bugs", ASOR Bulletin, 14, pp. 5--11.Google Scholar
- Kapur P.K., Bardhan A.K., and Kumar S. (2000) : On Categorization of Errors in a Software, Int. Journal of Kapur Management and System, 16(1), pp. 37--38Google Scholar
- P.K., Bardhan A.K.; Shatnawi O.; (2002) Why Software Reliability Growth Modelling Should Define Errors of Different Severity. Journal of the Indian Statistical Association, Vol. 40, 2, 119--142.Google Scholar
- Kapur P.K., Younes S and Grover P.S.; (1995), Software Reliability Growth Model with Errors of Different Severity, Computer Science and Informatics (India) 25(3):51--65.Google Scholar
- Kapur P.K. Kumar Archana ,Yadav Kalpana and Khatri Sunil(2007) :Software Reliability Growth Modelling for Errors of Different Severity using Change Point, International Journal of Quality, Reliability and Safety engineering Vol.14, No.4, pp. 311--326.Google Scholar
- P.K Kapur. Kumar Archana Singh V.B. and Nailana F.K.(2007):On Modeling Software Reliability Growth Phenomanon for Errors of Different Severity, In the Proceedings of National Conference on Computing for Nation Development, Bhartiya Vidyapith's Institute of Computer Applications and Management, New Delhi, pp.279--284, held during 23rd--24th February.Google Scholar
- P.K., Kapur Kumar Archana, Mittal Rubina and Gupta Anu (2005):Flexible Software Reliability Growth Model Defining Errors of Different Severity, Reliability, Safety and Hazard, pp. 190--197 Narosa Publishing New Delhi.Google Scholar
- Singh V.B., Singh O. P., Kumar.Ravi,Kapur P.K.(2010) A Generalized Software Reliability Model for Open Source Software published in proceedings of 2nd International Conference on Reliability Safety and Hazard, organized by Bhabha Atomic Research Center, Mumbai held during December, 14-16, 2010, published by IEEE Explore, pp.479--484Google Scholar
- Singh V.B., Khatri Sujata and Kapur P.K.(2010): A Reliability Growth Model for Object Oriented Software Developed Under Concurrent Distributed Development Environment, published in proceedings of 2nd International Conference on Reliability Safety And Hazard, organized by Bhabha Atomic Research Center, Mumbai held during December, 14- 16, 2010, pp. 479--484,Published by IEEE Explore.Google Scholar
- Kapur P.K., Garg R.B. and Kumar S. (1999) "Contributions to Hardware and Software Reliability", World Scientific, Singapore.Google Scholar
- K. Pillai and V.S.S. Nair, A Model for Software Development effort and Cost Estimation, IEEE Transactions on Software Engineering; vol. 23(8), 1997, pp. 485--497. Google Scholar
Digital Library
- Goel, AL and Okumoto K. (1979) :Time dependent error detection rate model for software reliability and other performance Measures, IEEE Transactions on Reliability Vol. R-28 (3) pp.206--211.Google Scholar
- S. Yamada, M. Ohba and S. Osaki, S-shaped Software Reliability Growth Models and their Applications, IEEE Transactions on Reliability R-33, 1984, pp. 169--175.Google Scholar
Cross Ref
- Singh V.B., Kapur P.K. and Abhishek Tandon "Measuring Reliability Growth of Software by Considering Fault Dependency, Debugging Time Lag Functions and Irregular Fluctuation" published in May issue Vol. 25, No. 3 ACMGoogle Scholar
Index Terms
Measuring bug complexity in object oriented software system
Recommendations
A Data Mining Model to Predict Software Bug Complexity Using Bug Estimation and Clustering
ITC '10: Proceedings of the 2010 International Conference on Recent Trends in Information, Telecommunication and ComputingSoftware defect(bug) repositories are great source of knowledge. Data mining can be applied on these repositories to explore useful interesting patterns. Complexity of a bug helps the development team to plan future software build and releases. In this ...
Effective Bug Triage Based on Historical Bug-Fix Information
ISSRE '14: Proceedings of the 2014 IEEE 25th International Symposium on Software Reliability EngineeringFor complex and popular software, project teams could receive a large number of bug reports. It is often tedious and costly to manually assign these bug reports to developers who have the expertise to fix the bugs. Many bug triage techniques have been ...
Bug characteristics in open source software
To design effective tools for detecting and recovering from software failures requires a deep understanding of software bug characteristics. We study software bug characteristics by sampling 2,060 real world bugs in three large, representative open-...






Comments