As part of a reproducibility initiative from the Student Cluster Competition 2016, specific results and trends presented in “A parallel connectivity algorithm for de Bruijn graphs in metagenomic applications” were similarly produced and verified. The general lack of reproducibility within the scientific community is a known issue, but few have the time, resources, or incentives to fully address it. Motivation for reproducibility resides in the need to independently validate previous research claims and test the difficulty or ease with which these claims may be reasserted. This fundamental tenant becomes ever more important, particularly due the prohibitive simulation cost and data complexity currently associated with metagenomics. The algorithms in the aforementioned article provide a scalable, distributed memory solution to the problem of assembling and labeling connected components in graphs associated with metagenomic samples. We aim to verify four of the components demonstrated by this article; namely, the deterministic countability of connected components in the data sets used, the computation to communication ratio of different work-balanced parallel algorithm implementations, the results obtained from said algorithm implementations, and the scaling behavior of the algorithms as the number of MPI processes are increased.