Many organizations utilize some form of automation in the test assembly process; either fully algorithmic or heuristically constructed. However, one issue with heuristic models is that when the test assembly problem changes the entire model may need to be re-conceptualized and recoded. In contrast, mixed-integer programming (MIP) is a mathematical representation of the test assembly problem that looks for the statistically optimal solution. Because MIP is a mathematical representation, changes to the test assembly problem typically involve only minor changes to the programming. This review focuses on comparing two free and open-source R packages for mixed integer linear programming: inlinelpSolveAPI and inlineompr. Programming style (with code provided), ease of use, run time, and other considerations will be examined. Solvers from other open-source platforms (e.g. Python, Julia) will also be discussed. Code and sample data are also provided.