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We developed an approach that uses our innate visual pattern recognition skills as part of the debugging process. Inspired by Huang's (1996) use of color to visualize energy distributions while untangling knots, we represented the particles graphically and color-coded them by energy value. Thus far, we've applied this approach to three domains: particle systems, cluster hardware configurations, and physics codes using finite element models. This debugging paradigm differs from software or program visualization in that we don't visualize software elements such as procedures, message passing between processors, or graph-based representations of data structures. In most application domains developers that use algorithm visualization tools must make decisions about what kind of visualization would best represent their code, and they must, in effect, code this visualization in addition to their application. For many developers, the time investment is too great compared to their perceived benefit, so they return to a traditional debugging approach. We believe that restricting the application domain increases the ease of use of visual debuggers. However, we go one step further by creating a, visual tool tailored to a particular application domain that can use either captured data or simulation outputs and requires no coding effort on the part of the user.