We report on the state of the field of algorithm visualization, both quantitatively and qualitatively. Computer science educators seem to find algorithm and data structure visualizations attractive for their classrooms. Educational research shows that some are effective while many are not. Clearly, then, visualizations are difficult to create and use right. There is little in the way of a supporting community, and many visualizations are downright poor. Topic distribution is heavily skewed towards simple concepts with advanced topics receiving little to no attention. We have cataloged nearly 400 visualizations available on the Internet. We have a wiki-based catalog which includes availability, platform, strengths and weaknesses, responsible personnel and institutions, and other data about each visualization. We have developed extraction and analysis tools to gather statistics about the corpus of visualizations. Based on analysis of this collection, we point out areas where improvements may be realized and suggest techniques for implementing such improvements. We pay particular attention to the free and open source software movement as a model which the visualization community may do well to emulate, from both a software engineering perspective and a community-building standpoint. / Master of Science