Published In

Software Process: Improvement and Practice

Document Type

Post-Print

Publication Date

2004

Subjects

System analysis -- Simulation methods, Experimental design -- Computer simulation

Abstract

Hybrid simulation models combine the high-level project issues of System Dynamics models along with the detailed process representation of discrete event simulation models. Hybrid models not only capture the best of both of these simulation paradigms, but they also are able to address new issues that are important in managing complex real-world development projects that neither the System Dynamics nor Discrete Event simulation paradigms are able to address alone.

In order to reap the full benefits from a simulation model, a structured approach for analyzing model results is necessary. The recommended approach is a combination of the Design of Experiments (DOE) technique and sensitivity analysis performed in a specific manner. DOE is a statistical technique that provides a more objective measure of how the impact of a given change to the model (such as a process change) might be dependent upon the values of other model parameters (such as the project environment, worker motivation, schedule pressure and so forth). Consideration of the interaction effects coupled with sensitivity analysis is essential for insightful interpretation of model results and effective decision-making.

This paper applies DOE and broad range sensitivity analysis to a Hybrid System Dynamics and discrete event simulation model of a software development process. DOE is used to analyze the interaction effects, such as the degree to which the impact of the process change depends on worker motivation, schedule pressure and other project environmental variables. The sensitivity of the model to parameter changes over a broad range of plausible values is used to analyze the nonlinear aspects of the model. The end result is a deeper insight into the conditions under which the process change will succeed and improved recommendations for process change design and implementation.

Keywords: Software Process Modeling, Software Process Simulation, Hybrid Simulation, Design of Experiments, Sensitivity Analysis

Rights

This is the post-print version. The published version, Copyright © 2004 John Wiley & Sons, Ltd., is available here: https://doi.org/10.1002/spip.200

DOI

10.1002/spip.200

Persistent Identifier

https://archives.pdx.edu/ds/psu/42823

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