Title: Uncertainties evaluation and analysis using quantitative technique for a software project

Authors: Harvinder Singh; Adarsh Kumar; Kiran Kumar Ravulakollu; Manoj Kumar; Thompson Stephan

Addresses: Department of Virtualization, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India ' Department of Systemics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India ' Department of Informatics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India ' Department of Systemics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India ' Department of Computer Science and Engineering, Faculty of Engineering and Technology, M.S. Ramaiah University of Applied Sciences, Bangalore, Karnataka, India

Abstract: Opportunities cannot be converted into achievements without assessing risk. Software developers and project managers presume that activities would proceed smoothly and according to plan in software project development. However, in reality, this is not always true due to the existence of unseen risks that influence the development process and thereby performance. Hence, there is a need for more realistic risk evaluation criteria that can address the project managers need. This paper proposes a project risk evaluation technique (PRET) to determine the attractiveness of a software project. The proposed technique used normal distribution (D_N) approach for risk understanding and thereby use the activity network to assess them. Using the graph theory method, with nodes as phases of the development process and edges as the duration of phases and the whole network as a software project, the algorithm systematically represented to extend various influential aspects of risk analysis. Hence, using quantitative analysis, the proposed algorithm is evaluated against negative exponential distribution (D_NE) and is found to have a slight degree of uncertainty associated with risk and attractiveness. This signifies that there is still a scope of improvement for stabilising the proposed technique with minimal improvements in the project factors.

Keywords: risk analysis; software risk management; PRET algorithm; normal distribution; negative exponential distribution.

DOI: 10.1504/IJAHUC.2021.119088

International Journal of Ad Hoc and Ubiquitous Computing, 2021 Vol.38 No.1/2/3, pp.70 - 81

Received: 26 Sep 2020
Accepted: 07 Jan 2021
Published online: 22 Nov 2021 *

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