In less than two decades, destruction and abuse caused by computer viruses and worms have grown from an anomaly to an everyday occurrence. In recent years, the Computer Emergency Response Team (CERT) has recorded a steady increase in software defects and vulnerabilities, similar to those exploited by the Slammer and Code Red worms. In response to such a threat, the academic community has started a set of research projects seeking to understand worm behavior through creation of highly theoretical and generalized models. Staniford et. al. created a model to explain the propagation behaviors of such worms in computer network environments. Their model makes use of the Kermack-McKendrick biological model of propagation as applied to digital systems. Liljenstam et. al. add a spatial perspective to this model, varying the infection rate by the scanning worms' source and destination groups. These models have been shown to describe generic Internet-scale behavior. However, they are lacking from a localized (campus-scale) network perspective. We make the claim that certain real-world constraints, such as bandwidth and heterogeneity of hosts, affect the propagation of worms and thus should not be ignored when creating models for analysis. In setting up a testing environment for this hypothesis, we have identified areas that need further work in the computer worm research community. These include availability of real-world data, a generalized and behaviorally complete worm model, and packet-based simulations. The major contributions of this thesis involve a parameterized, algorithmic worm model, an openly available worm simulation package (based on SSFNet and SSF.App.Worm), analysis of test results showing justification to our claim, and suggested future directions.