Probabilistic estimation of software project duration

TL;DR

This paper introduces a probabilistic framework using Monte Carlo simulation to model and propagate uncertainty in software project duration estimates, aiding project managers in decision-making.

Contribution

It presents a flexible, uncertainty-aware estimation framework that incorporates historical data to improve project duration predictions throughout the lifecycle.

Findings

Initial results with simulated data demonstrate the framework's potential.

The approach enables informed decision-making under uncertainty.

Mechanisms for learning from past projects are integrated.

Abstract

This paper presents a framework for the representation of uncertainty in the estimates for software design projects for use throughout the entire project lifecycle. The framework is flexible in order to accommodate uncertainty in the project and utilises Monte Carlo simulation to compute the propagation of uncertainty in effort estimates towards the total project uncertainty and therefore gives a project manager the means to make informed decisions throughout the project life. The framework also provides a mechanism for accumulating project knowledge through the use of a historical database, allowing effort estimates to be informed by, or indeed based upon, the outcome of previous projects. Initial results using simulated data are presented and avenues for further work are discussed.