Noisy Intermediate-Scale Quantum (NISQ) computers are potentially capable of solving Non-deterministic Polynomial-time hard problems that remain computationally intractable for classical computers. However, the potential of NISQ computers cannot be fully exploited due to physical limitations: state-of-the-art quantum hardware backends suffer from high error rates and short decoherence times. As a consequence, the probability of a successful computation is inversely proportional to the depth and gate count of the quantum circuit; such metrics, when sufficiently high, do not allow the system to complete the computation within the coherence time. Compilation and Optimization techniques become necessary to overcome these physical constraints and to achieve a better success probability.