Ordinary differential equations are a ubiquitous tool for modeling real-world phenomena. To ensure the best quality of a model, one tends to focus on the ability to discover model parameters from experiment. Property of structural parameter identifiability can help solving this problem. I will show examples of parameter identifiability types, talk about some existing solutions and their Julia Language implementations, and discuss what I am working on during this year's Summer of Code.