Since a few decades, research is going through the so-called replication crisis. It is known that different software versions or CPU architectures will impact the performance and results of an algorithm. This awareness has a positive impact on the research as more and more published papers pay more attention at the reproducibility aspect by giving more details about the proposed algorithms and experiment parameters. Yet, implementation choices are often left out of the publishing process and using the exact same machine and parameters as the original authors is usually impossible. With this work, we give some information on how the modeling language JuMP passes the constraints to the solvers and we present a new julia tool called SortModel which allows for changing the order of the constraints in the JuMP model. Using SortModel, we show the performance variability induced by constraint ordering and provide a simple way to experiment with.