This body of work develops a unified relational ontology of form that reinterprets metaphysics, physics, biology, and AI as different expressions of the same underlying problem: how stable forms emerge, persist, and transform within a world constituted not by independent objects, but by relations. Beginning with the formal foundations of relational ontology, the work argues that determination is not imposed upon a pre-existing reality but progressively achieved through hierarchies of relational constraints. This metaphysical framework is then developed across increasingly concrete domains. In physics, it offers an alternative to object-based metaphysics by interpreting physical reality as an ongoing process of relational determination. In biology, it reconceives living systems as dynamically self-maintaining relational organizations whose identity is preserved through continuous return rather than static structure. In the study of large language models, it distinguishes formal continuation from interpretation, showing how recursive relational processes can generate formally integrated conceptual structures while remaining fundamentally distinct from human acts of interpretation. Across these domains, a common theoretical principle emerges: identity is not the persistence of substance but the achievement of relational continuity. Physics, biology, and AI therefore become different manifestations of a single metaphysical logic in which possibility is progressively formed, organization is maintained through recursive constraint, and interpretative meaning requires participatory return rather than formal representation alone. Taken as a whole, this work offers a contingent philosophical framework through which metaphysics can provide a common language for bringing the physical sciences, the life sciences, and the formal sciences into relation. It is an attempt to recover theoria as an inquiry into becoming rather than being, replacing an ontology of independent objects with an ontology of relational determination. The framework does not claim to exhaust the actuality to which its formal structures refer; rather, by bringing different domains into relation, it seeks to make visible both their underlying continuities and the wider metaphysical and interpretative questions that remain open beyond its own determinations
The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.
Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al.· IEEE Transactions on Softwar...· 178 citations· ⚡14
Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.
M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al.· e-Informatica Software Engin...· 157 citations· ⚡17
This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.
Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al.· Empirical Software Engineeri...· 127 citations· ⚡15
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al.· Journal of Systems and Softw...· 111 citations· ⚡8
The ongoing work building a Raspberry Pi cluster consisting of 300 nodes is presented, with potential use cases being an inexpensive and green test bed for cloud computing research and a robust and mobile data center for operating in adverse environments.
P. Abrahamsson, S. Helmer, Nattakarn Phaphoom et al.· IEEE International Conferenc...· 110 citations· ⚡7
The results indicate that software developers are a slightly happy population, but the need for limiting the unhappiness of developers remains, and 219 factors representing causes of unhappiness while developing software are identified.
D. Graziotin, Fabian Fagerholm, Xiaofeng Wang et al.· International Conference on...· 84 citations· ⚡6
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