# Towards a Digital Transformation Hyper-Framework:
## 3 Materials and Methods
### The Foundation of Hypothesis 1 (H1)--Integrated Tailorable Life Cycle Models
#### 3.1.2 The Role of Software Engineering (SwEng)
Consequently, a TCP/IP meta-specification is better suited for validation and monitoring purposes (due to the direct compliance with the real-time operating context). The digital communication domain faces a fast development of methods, principles, techniques, and technologies challenging the sustainability of contemporary DgT approaches. The most challenging is the transition from contemporary (3G/4G) to 5G/6G and beyond technologies [60; 61], the broader incorporation of Blockchain [62], the impact of the artificial intelligence [63], and the predicted transition from classical to semantic digital communications [64; 65]. Computer infrastructure (CI) is the SoIS that physically hosts the related digital ecosystem and represents the most inner responsibility layer of DgT endeavors. A dominant fast development of technologies and the proliferation of novel computing principles (primarily quantum computing) represent the additional challenging aspects of a continuous DgT operation independent of infrastructure reconfiguration. Similarly to the CS, CI determines a cost/performance relation of particular DgT activities. A CI incorporates a broad scope of networked computer assets ranging from the IoT edge and cloud [66] support, globally distributed ledgers [67], computer clusters [68], gateway-isolated private computer networks [69], public computer networks [70], to personal and pervasive computer devices [71]. Currently, a computer network topology is a synonym for CI topology, making a computer network a generic CI but with the extracted CS domain. The mind map scope model of CI topology scope is represented in Figure 7[72] and frames the potential ranges of DgT. The course of OpEng originates from the technical infrastructure's similarity with a human's vegetative neural system. When it functions, nobody even cares or is conscious of its existence. Proper functioning is intrinsically assumed, while continuous service delivery appears as a spontaneous natural phenomenon from the stakeholder's angle. When the technical infrastructure fails, it appears from the darkness blame  
Figure 7: CI topology scope model (adapted from [72]). The role of Operations Engineering in the specification of integrated tailorable life cycle models reflects the impact of executive infrastructure that transparently supports a virtually unlimited digital ecosystem in the uninterruptable delivery of the embedded system's services. According to the conceptual framework model proposed in [42] (Figure 4), Operations Engineering maps to the Execution helix. In conclusion, the first hypothesis advocates a need for an interoperable multi-stage, Digital Twin-based, hyper-framework hosting the extendible library of collaborative/cooperative life cycle meta-models that integrate Systems Engineering (SysEng), Software Engineering (SwEng), and Operation Engineering (OpEng) activities. Based on a generic artificial intelligence and the information resources harvested from the persistent data layer, individual meta-models transform into particular DgT context instances.