FMCooler: Simulated annealing for feature model configuration selection

FMCooler is a tool for the automatic optimization in the selection of a configuration from a feature model based on the Simulated Annealing metaheuristic.It is a python-based tool built on top of flamapy, qubovert and dwave-neal.The formulation abstractions and details are exposed, as well as examples of usage to understand the easy handling of the module.We discuss experimentation results to argue that is a valid candidate to be included in the toolset to address this problem given its competitive results and scalability.We also include a discussion on future extensions as the reuse of the abstractions for experimenting with quantum computation.Tool and video: https://github.com/jdanielescanez/fmcooler