Abstract
In the computational space, reproducibility has become a concern for many as results need verification and reproducibility which are foundational parts of the scientific process. Technologies such as Jupyter Notebook have become increasingly common as an attempt to increase the nature of creating both reproducible results as well as reproducible code and sharing those results rapidly. The framework of notebooks isn't perfect however as notebooks can be shared without being entirely reproducible due to various constraints within the current Jupyter Notebook infrastructure as well as bad practices enabled by the technology. This thesis explores the potential shortfalls and pitfalls of reproducibility in this environment and also aims to address the concerns that come from Jupyter Notebooks. Resolving how these issues can be mitigated through better coding practices as well as creating additional tools that capture some of the existing issues within this environment.