  Research on fractal networks is a dynamically growing field of network
science. A central issue is to analyze fractality with the so-called
box-covering method. As this problem is known to be NP-hard, a plethora of
approximating algorithms have been proposed throughout the years. This study
aims to establish a unified framework for comparing approximating box-covering
algorithms by collecting, implementing, and evaluating these methods in various
aspects including running time and approximation ability. This work might also
serve as a reference for both researchers and practitioners, allowing fast
selection from a rich collection of box-covering algorithms with a publicly
available codebase.
