[PROPL'24] Fluid: towards transparent, self-explanatory research outputs

Joe Bond, Cristina David, Minh Nguyen, Roly Perera

This talk will introduce a “transparent” programming language called Fluid which incorporates a bidirectional dynamic dependency analysis into its runtime. Fluid keeps track of dependencies as outputs, such as charts or tables, are computed from data, and automatically enriches rendered outputs with interactions allowing a reader to interactively explore their relationship to inputs.