Research Article Open Access

Simulator for Optimization of Software Project Cost and Schedule

P. K. Suri and B. Bhushan

Abstract

Each phase of the software design consumes some resources and hence has cost associated with it. In most of the cases cost will vary to some extent with the amount of time consumed by the design of each phase .The total cost of project, which is aggregate of the activities costs will also depends upon the project duration, can be cut down to some extent. The aim is always to strike a balance between the cost and time and to obtain an optimum software project schedule. An optimum minimum cost project schedule implies lowest possible cost and the associated time for the software project management. In this research an attempt has been made to solve the cost and schedule problem of software project using PERT network showing the details of the activities to be carried out for a software project development/management with the help of crashing, reducing software project duration at a minimum cost by locating a minimal cut in the duration of an activity of the original project design network. This minimal cut is then utilized to identify the project phases which should experience a duration modification in order to achieve the total software duration reduction. Crashing PERT networks can save a significant amount of money in crashing and overrun costs of a company. Even if there are no direct costs in the form of penalties for late completion of projects, there is likely to be intangible costs because of reputation damage.

Journal of Computer Science
Volume 4 No. 12, 2008, 1030-1035

DOI: https://doi.org/10.3844/jcssp.2008.1030.1035

Submitted On: 22 April 2008 Published On: 31 December 2008

How to Cite: Suri, P. K. & Bhushan, B. (2008). Simulator for Optimization of Software Project Cost and Schedule. Journal of Computer Science, 4(12), 1030-1035. https://doi.org/10.3844/jcssp.2008.1030.1035

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Keywords

  • Software
  • PERT
  • crashing
  • beta distribution
  • scheduling
  • activity cost
  • cost slope