I guess things are a spectrum. I've worked on research projects where understanding and developing the algorithm is the research. There isn't really an "input data set" other than a handful of parameters that are really nothing more than scale factors, and the output is how well the algorithm performs. So "setting up the laboratory" by cloning the code and building it is...fine, but a reimplementation of the algorithm with "the same" results (modulo floating point, language features, etc. etc.) aligns much better with reproducibility.