Abstract — Applying visual analytics to large software systems can help users comprehend the wealth of information produced by source repository mining. One concept of interest is the co-evolution of test code with source code, or how source and test files develop together over time. For example, understanding how the testing pace compares to the development pace can help test managers gauge the effectiveness of their testing strategy. A useful concept that has yet to be effectively incorporated into a co-evolution visualization is co-change. Co-change is a quantity that identifies correlations between software artifacts, and we propose using this to organize our visualization in order to enrich the analysis of co-evolution. In this paper, ...