Risk Ananlysis and Estimation of Scheduling of Software Project – Using Stochastic Approach

Authors

  • Bindra Y Department of Computer Science and Engineering, Ganpati Institute of Technology and Management, Bilaspur, India
  • Garg R Department of Electronics and Communication Engineering, Seth Jai Parakash Polytechnic for Engineering, Damla, India
  • Kaur N Department of Computer Science and Engineering,Ganpati Institute of Technology and Management, Bilaspur, India

DOI:

https://doi.org/10.26438/ijcse/v6i1.332335

Keywords:

Schedule Risk Analysis, Monte Carlo Simulation, Estimation

Abstract

A project is a combination of several interrelated activities which must be performed in a certain order of its completion. To meet tight deadlines in software projects, managers need to understand key reservations about the scheduling techniques and how to use a schedule risk analysis to provide information crucial to a project’s success. This paper describes an application of simulation which simulates the duration of the activities for analyzing schedule risk and providing reliable estimates of time. Monte Carlo Simulation Methods are mostly used for analyzing schedule risk. In this the random numbers are generated to simulate the software project number of times. The primary objective of the simulation is to find out the effect of uncertainties on the schedule of project completion. The designed simulator SRAES for a live website Filmtribe uncovered the critical paths and risky activities in the project and also provided the risk indices of those risky activities. The simulator also calculated the Project Completion Time in less than 1 minute which can take months to calculate analytically. Therefore, it is concluded that Monte Carlo Simulation is an important technique for risk analysis and estimation of scheduling in any type of software projects.

References

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Hira, D. S. 2001. System Simulation, S. Chand & Company Pvt. Ltd, New Delhi.

Subhas C. Misra, Vinod Kumar and Uma kumar (2006), “Different Techniques for Risk Management in Software Engineering: A Review”, ASAC Banff, Alberta.

Sharma, I. et al. 2011. “Schedule Risk Analysis Simulator using Beta Distribution”. International Journal of Computer Science and Engineering (IJCSE), Vol. 3, No. 6, pp.2408-2414.

Deo, N. 2003. System Simulation with Digital Computer, Prentice-Hall of India, New Delhi.

Pressman, R. S. 2006. Software Engineering - A Practitioner’s Approach, fifth edition, McGraw-Hill.

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Published

2025-11-12
CITATION
DOI: 10.26438/ijcse/v6i1.332335
Published: 2025-11-12

How to Cite

[1]
Y. Bindra, R. Garg, and N. Kaur, “Risk Ananlysis and Estimation of Scheduling of Software Project – Using Stochastic Approach”, Int. J. Comp. Sci. Eng., vol. 6, no. 1, pp. 332–335, Nov. 2025.

Issue

Vol. 6 No. 1 (2018): IJCSE January Ediion

Section

Research Article

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