  Quantum computing can enable a variety of breakthroughs in research and
industry in the future. Although some quantum algorithms already exist that
show a theoretical speedup compared to the best known classical algorithms, the
implementation and execution of these algorithms come with several challenges.
The input data determines, e.g., the required number of qubits and gates of a
quantum algorithm. An algorithm implementation also depends on the used
Software Development Kit which restricts the set of usable quantum computers.
Because of the limited capabilities of current quantum computers, choosing an
appropriate one to execute a certain implementation for a given input is a
difficult challenge that requires immense mathematical knowledge about the
implemented quantum algorithm as well as technical knowledge about the used
Software Development Kits. Thus, we present a roadmap for the automated
analysis and selection of implementations of a certain quantum algorithm and
appropriate quantum computers that can execute the selected implementation with
the given input data.
