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Software Project Management under Uncertainties
Analysis of Software Project using Event Chains Methodology
Step 3: Performing Simulation and Analysis
To generate a schedule with uncertainties, Monte Carlo simulations should be performed using a baseline project schedule and an event list. The number of simulations can be defined based on the lowest probability of the occurrence of events. The simulation can be stopped when the results of simulations converge: that is, when the main calculation outputs (duration, finish time, project cost, etc.) within a given number of simulations remain close to each other. Unfortunately, because of the discrete nature of the event chains, simulations will converge relatively slowly. In reality, the number of simulations can be between a few hundred to a few thousand. However, using modern computer hardware, Monte Carlo simulations for realistic software development projects can be executed within seconds. Actual simulation time depends on computer performance, number of simulations, number of tasks, and number of events.
The results of a calculation can be presented in the form of a Gantt chart together with baseline project schedule (see Fig. 3).
Fig. 3. Results of calculation and baseline project schedule
In this example, events significantly increased the duration of all tasks and the whole project. Results of the simulation are shown on Fig 4. as a table and a frequency chart. The chance that project duration is below a certain number is a measure of the project risk.
Fig. 4. Simulation results: frequency chart for duration and results in table format
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