Assessment and Prediction of Software Reliability in Mobile Applications
- 1 Department of Computer Science, Southern Methodist University, Dallas, TX, USA
- 2 Department of Computer Science, Southern Methodist University, Dallas, TX, USA
Abstract
Software reliability is an important quality attribute, and software reliability models are frequently used to measure and predict software maturity. The nature of mobile environments differs from that of PC and server environments due to many factors, such as the network, energy, battery, and compatibility. Evaluating and predicting mobile application reliability are real challenges because of the diversity of the mobile environments in which the applications are used, and the lack of publicly available defect data. In addition, bug reports are optionally submitted by end-users. In this paper, we propose assessing and predicting the reliability of a mobile application using known software reliability growth models (SRGMs). Four software reliability models are used to evaluate the reliability of an open-source mobile application through analyzing bug reports. Our experiment proves it is possible to use SRGMs with defect data acquired from bug reports to assess and predict the software reliability in mobile applications. The results of our work enable software developers and testers to assess and predict the reliability of mobile software applications.
- Shanmugam, L. and Florence, L. (2012) An Overview of Software Reliability Models. International Journal of Advanced Research in Computer Science and Software Engineering, 2, 10.
- Muss, J.D., Iannino, A. and Okumoto, K. (1987) Software Reliability: Measurement, Prediction, Application. McGraw-Hill, Inc., Pennsylvania Plaza, New York City.
- Musa, J.D., Iannino, A. and Okumoto, K. (1990) Software Reliability. Advances in Computers, 30, 85-170. https://doi.org/10.1016/S0065-2458(08)60299-5
- Barack, O. and Huang, L. (2019) Adaptation of Orthogonal Defect Classification for Mobile Applications. Proceedings of the 28th International Conference on Software Engineering and Data Engineering, 64, 119-128.
- Vithani, T. and Kumar, A. (2014) Modeling the Mobile Application Development Lifecycle. Proceedings of the International Multi Conference of Engineers and Computer Scientists, Vol. 1, Hong Kong, 12-14 March 2014.
- Lyu, M.R., et al. (1996) Handbook of Software Reliability Engineering. Vol. 222, IEEE Computer Society Press, Washington DC.
- Tian, J., Rudraraju, S. and Li, Z. (2004) Evaluating Web Software Reliability Based on Workload and Failure Data Extracted from Server Logs. IEEE Transactions on Software Engineering, 30, 754-769. https://doi.org/10.1109/TSE.2004.87
- Huang, C.-Y., Kuo, S.-Y. and Lyu, M.R. (2007) An Assessment of Testing-Effort Dependent Software Reliability Growth Models. IEEE Transactions on Reliability, 56, 198-211. https://doi.org/10.1109/TR.2007.895301
- Alannsary, M.O. and Tian, J. (2016) Measurement and Prediction of SaaS Reliability in the Cloud. 2016 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C), Vienna, Austria, 1-3 August 2016, 123-130. https://doi.org/10.1109/QRS-C.2016.20
- Bokhary, A. (2017) Measuring Cloud Service Reliability by Weighted Defects over the Number of Clients as a Proxy for Usage. Proceedings of the 32nd International Conference on Computers and Their Applications (CATA), Honolulu, HI, 20-22 March 2017, 63-70.
- Perera, U.D. (2006) Reliability Index—A Method to Predict Failure Rate and Monitor Maturity of Mobile Phones. RAMS’06. Annual Reliability and Maintainability Symposium, Newport Beach, CA, 23-26 January 2006, 234-238.
- Almering, V., van Genuchten, M., Cloudt, G. and Sonnemans, P.J.M. (2007) Using Software Reliability Growth Models in Practice. IEEE Software, 24, 82-88. https://doi.org/10.1109/MS.2007.182