Combining Process Feedback with Discrete Event Simulation Models to Support Software Project Management

Abstract

Process feedback is an essential ingredient in process change planning and software project management. In this paper, we discuss on-going work with an industrial partner to integrate feedback from the software development process with a discrete event simulation model to improve process performance predictions. A flexible metrics repository provides feedback that is used to generate updated simulation model parameters at predefined project milestones. Model predictions using updated parameters and current project data are compared to Outcome Based Control Limits (OBCLs) defined for the project. These predictions enable the program manager to take corrective action as necessary with the simulation model providing feedback and insight on potential performance impacts of the proposed corrective actions. This creates a feedback loop with the process enhancing model predictions supporting project management decisions.

A discrete event simulation model in the case of managing a software project

“…It is, hence, very important for an organization willing to improve its processes and receive help in that direction from techniques such as simulation modeling, to systematically record and statistically analyze data from various projects' executions [3,16,18,20]. This way, the experience gained from the development of the various projects, can be transformed, given the appropriate maturing time, into valuable knowledge, rather than a recollection of statistical attempts.…”

A flexible software process model

“…The main paradigms currently applied to simulation modelling are system dynamics [1,51,99,105,119,138,162], discrete event simulation, state based [67,137], and rule based [46,143,153]. More recently, researchers have combined paradigms in an attempt to overcome limitations inherent in individual paradigms [45,93,107,106,136].…”

“…Other modellers emply a discrete mechanism to capture such change. For example, Raffo and Harrison manage such variables by means of some persistent storage that captures changing values as the project progresses [136]. Martin and Raffo present a model in which values for continuous elements are obtained by calculating model equations at regular time intervals [106].…”