OSS Effort Expense Optimization Based on Wiener Process Model and GA
- 1 Tokyo City University, Tokyo, Japan
- 2 Tokyo City University, Tokyo, Japan
- 3 Tottori University, Tottori, Japan
Abstract
Various open source software are managed by using several bug tracking systems. In particular, the open source software extends to the cloud service and edge computing. Recently, OSF Edge Computing Group is launched by OpenStack. There are big data behind the internet services such as cloud and edge computing. Then, it is important to consider the impact of big data in order to assess the reliability of open source software. Various optimal software release problems have been proposed by specific researchers. In the typical optimal software release problems, the cost parameters are defined as the known parameter. However, it is difficult to decide the cost parameter because of the uncertainty. The purpose of our research is to estimate the effort parameters included in our models. In this paper, we propose an estimation method of effort parameter by using the genetic algorithm. Then, we show the estimation method in section 3. Moreover, we analyze actual data to show numerical examples for the estimation method of effort parameter. As the research results, we found that the OSS managers would be able to comprehend the human resources required before the OSS project in advance by using our method.
- Ibrahim, I.M., et al. (2018) A Robust Generic Multi-Authority Attributes Management System for Cloud Storage Services. IEEE Transactions on Cloud Computing, 30 August 2018, 1. https://doi.org/10.1109/TCC.2018.2867871
- Ahmad, A.A., et al. (2019) Scalability Analysis Comparisons of Cloud-Based Software Services. Journal of Cloud Computing: Advances, Systems and Applications, 8, Article No. 10.
- Taleb, T., Samdanis, K., Mada, B., Flinck, H., Dutta S. and Sabella, D. (2017) On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Cloud Architecture and Orchestration. IEEE Communications Surveys & Tutorials, 19, 1657-1681. https://doi.org/10.1109/COMST.2017.2705720
- Kapur, P.K., Pham, H., Gupta, A. and Jha, P.C. (2011) Software Reliability Assessment with OR Applications. Springer-Verlag, London. https://doi.org/10.1007/978-0-85729-204-9
- Yamada, S. and Tamura, Y. (2016) OSS Reliability Measurement and Assessment. Springer International Publishing, Switzerland. https://doi.org/10.1007/978-3-319-31818-9
- Norris, J. (2004) Mission-Critical Development with Open Source Software. IEEE Software Magazine, 21, 42-49. https://doi.org/10.1109/MS.2004.1259211
- Singh, V.B., Sharma, M. and Pham, H. (2017) Entropy Based Software Reliability Analysis of Multi-Version Open Source Software. IEEE Transactions on Software Engineering, 44, 1207-1223. https://doi.org/10.1109/TSE.2017.2766070
- Yamada, S. and Osaki, S. (1985) Cost-Reliability Optimal Software Release Policies for software Systems. IEEE Transactions on Reliability, 34, 422-424. https://doi.org/10.1109/TR.1985.5222222
- Khatri, S.K., John S.A. and Majumdar, R. (2016) Quantifying Software Reliability Using Testing Effort. Proceedings of International Conference on Information Technology (InCITe)—The Next Generation IT Summit on the Theme—Internet of Things: Connect Your Worlds, Noida, 6-7 October 2016, 23-26. https://doi.org/10.1109/INCITE.2016.7857582
- Lance, F. and Swapna, S.G. (2008) Software Reliability Models Incorporating Testing Effort. OPSEARCH, 45, 351-368. https://doi.org/10.1007/BF03398825
- Kapur, P.K., Gupta, A. and Jha, P. (2007) Reliability Analysis of Project and Product Type Software in Operational Phase Incorporating the Effect of Fault Removal Efficiency. International Journal of Reliability, Quality and Safety Engineering, 14, 219-240. https://doi.org/10.1142/S021853930700260X