A Practical Approach to Software Cost Estimation Using Stochastic Modelling

Authors

  • Swati Saxena Department of Mathematics Sagar Institue of Science & Technology, Bhopal
  • Shiv Kumar Singh Department of Mathematics Sagar Institue of Science & Technology, Bhopal
  • Nargish Gupta Department of Computer Science & Engineering Sagar Institue of Science & Technology, Bhopal
  • Meena Malik Department of Computer Science & Engineering Chandigarh University, Mohali.
  • Ankur Goyal Department of CSE, Symbiosis Institute of Technology, Symbiosis International Deemed University, Pune

Keywords:

Software Cost Estimation, Fuzzy Logic, Linear Regression Analysis, JIRA

Abstract

Software cost estimation plays a very critical role in Software Project Management. If the cost of the software has not been estimated properly, it can have a drastic impact on the project execution and delivery. Traditional models for software cost estimation fail to model correctly, the cost components associated with the project. There is enormous research literature related to software cost estimation but only a handful of them relate to cost measures that include both software development and software support. This is mainly because, in recent years, there has been a remarkable change in the way the software is now developed and supported. Needless to say, the software exists everywhere from elementary education to nuclear reactors and from civil engineering to genetic engineering. As such, one cannot bind it into the same set of measures related to development and delivery. In this research, we focus on customers like hotels, airways, banking, etc., particularly massive ERP systems, for development and customization support. Such software once purchased, requires one or more support teams to ensure its availability for the client. The infrastructure teams usually maintain server support whereas the application maintenance teams provide customization and functionality support. In this research, we have developed a model that considers the fixed cost and the recurring costs associated with the software. The fixed cost is related to the cost of development whereas the recurring cost involves the cost associated with the cost of cloud/on-premise deployment and the cost associated with support teams. The contribution of this research is twofold. We have proposed a model that considers the largest set of parameters of cost-related estimation, aligned with both development and support, which is highly mapped to ERP-like software. To the best of our knowledge and belief, no existing research considers all these parameters. To make the analysis applicable to a number of case studies, we have fuzzified the parameters to make them align with linguistic hedges. The possible deviations in the cost computation are estimated using linear regression ML models. We have considered the supports and customization part in accordance with modern bug-tracking tools like JIRA. The analysis is done for the case of an educational ERP with LMS and compared the result with those available as open-source in the UCI repository.

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Published

23.02.2024

How to Cite

Saxena, S. ., Singh, S. K. ., Gupta, N. ., Malik, M. ., & Goyal, A. . (2024). A Practical Approach to Software Cost Estimation Using Stochastic Modelling. International Journal of Intelligent Systems and Applications in Engineering, 12(17s), 478–488. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4907

Issue

Vol. 12 No. 17s (2024)

Section

Research Article

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