Under CopyrightPoggel, BenediktBenediktPoggelKruse, GeorgGeorgKruseTokuhiro, LenaLenaTokuhiroLorenz, Jeanette MiriamJeanette MiriamLorenz2025-11-242025-11-242025https://publica.fraunhofer.de/handle/publica/499615https://doi.org/10.24406/publica-649910.24406/publica-6499Full stack quantum computing systems require software layers with different levels of abstraction to accommodate industrial end users. On top of hardware control, compilation and transpilation passes, this includes the upmost part of the software stack, the bridge to applications. For emerging technologies such as quantum computing, this is not merely a software engineering challenge but requires defining performance metrics and investigating the best way to plug different parts like classical algorithms, quantum circuits, encoding schemes or decomposition methods together in an application-tailored way. The QuaST Decision Tree is a powerful, flexible and adaptive tool that guides the choice of formulation, algorithm selection, hyperparameter selection and hybrid algorithm execution. Its modular framework allows executing any pre- and postprocessing code and adapting to different scenarios such as specific use cases or providing configuration files for an underlying software stack. Latest features include general QUBO instances, an automatic mode requiring no other user input except the problem instance, the validation of the compatibility of nodes within customized QuaST Decision Tree instances, and a low-code entry point via web app. The next planned feature is a direct connection to the MQSS, enabling the use of the quantum devices located at LRZ.enquantum computingapplied optimizationdesign automationsoftware abstractionposter