Quantum computers have the potential to solve certain problems faster or with more precision than classical computers. Therefore, quantum computing saw a rise in popularity and consequently much research is performed to achieve quantum advantage. However, today’s quantum computers are not capable of executing most of these algorithms with reasonable instance sizes. To benefit from current hardware, algorithms are split into a classical part and a quantum part, such that recent quantum computers can execute it. This abstract idea of splitting is formulated in the Quantum- Classic Split pattern. This thesis examines these hybrid algorithms with a focus on Variational Quantum Algorithms and their split-points. Different implementations of the Variational Quantum Eigensolver and Quantum Approximation Optimization Algorithm are tested with several components. Many classical components are reusable. If the split-points are set well, Classical optimizers, classical pre-processing and classical post-processing can be tested and implemented by classical software engineers. The benefit of splitting algorithms are, that the implementation can be distributed between software engineers and quantum experts and the classical parts can be reusable. The guidelines on how to set split-points are structured similar to patterns as pattern-candidates.