Abstract Lossless conversion and compatibility of codes across programming languages and operating systems represent a long-standing fundamental challenge in the fields of computer programming languages and compiling principles. Existing technologies are always confined to the unidirectional adaptation paradigm at the syntactic level, relying on manual rule mapping or surface-level syntactic translation, which fails to achieve lossless transmission of core business logic across domains and bidirectional closed-loop verification. There is also a lack of universal, principle-based underlying support at the theoretical level. Based on the core underlying ideas of the author's original Chinese basic invention patent A Bidirectional Cross-Domain Adaptation Method and System Based on AI Compatibility Layer, this paper proposes a complete set of basic theories for universal bidirectional cross-domain adaptation, and constructs a brand-new theoretical system with the AI compatibility layer as the core hub and logical feature normalization and dynamic feature mapping as the dual core mechanisms. It addresses for the first time the underlying common problems in the cross-language and cross-operating system code conversion field: "difficult to break syntactic barriers, easy logic distortion, and no closed-loop verification". It completely abandons the inherent mindset of traditional syntactic adaptation, realizing pure logical bidirectional mapping and self-optimization between the source domain and target domain without syntactic barriers or platform differences. This paper focuses entirely on principle-level theoretical construction, without involving specific engineering parameters, code implementation, or model training details. Through formal definitions, paradigm comparison, and theoretical completeness analysis, it demonstrates the 0-1 originality and academic value of this theory. This study breaks the underlying paradigm constraints of existing cross-domain conversion, filling the global basic theoretical gap in universal cross-language and cross-operating system logical adaptation in the computer field. It is not only applicable to code conversion scenarios but also extendable to bidirectional cross-domain interaction scenarios in all fields, providing core theoretical support for subsequent research and underlying innovation in programming languages, artificial intelligence transfer learning, software engineering and other directions. Update 1 | Right Confirmation & Publication | Core Logic (Beijing Time 03:31, March 23, 2026) The core reason for releasing this paper as a preprint is academic right confirmation, as I intend to submit it to a top international journal. In fact, this paper is the second academic work associated with my core invention patent. The first one, "Language-Mediated-Free AI Generation and Bidirectional Human-Machine Interaction Based on Brain-Computer Interfaces: A Feasibility Hypothesis and Research Outlook" (doi: 10.5281/zenodo.18338568), was published by me as early as December 23, 2025. Both papers share the same patent core logic, differing only in their research focus: this one is more mature, with a clear focus on the computer science domain.While my patent is a fundamental invention that may seem esoteric at first glance, I believe you will fully understand this paper once you read its abstract. As you will see from the abstract, the breakthrough of this paper lies in unlocking full interoperability between any programming languages. Instead of directly translating syntax, it extracts the core business logic and then reconstructs it into the target language. Logic itself is universal—since the birth of programming languages, they have all been designed to translate abstract logic into language-specific syntax. I have simply reversed this process: first, reverse-engineer code back to its underlying pure logic, then reconstruct that logic into a new target language. By using AI as the compatibility layer, this entire process can be automated elegantly by the AI itself, skipping the laborious stage of manually building language libraries and stepping directly into the future. Are you excited? Because this means that, based on my theory and patent, we can build a universal programming language converter powered by an AI compatibility layer. In the future, proprietary languages developed by major tech companies will lose their purpose as technical barriers, allowing programming languages to return to their original intent: enhancing the expression of logic and efficiency. This makes true "Internet of Everything" possible—when programming languages themselves become interoperable, how far can the fully connected future be? Haha, I know you must be looking forward to such a future, just as I am. I have always strived to change the world and shape the future through fundamental theory. This is the power and charm of knowledge, and I believe that as a reader and scholar, you share this vision too.
Relike Zhou (Sun,) studied this question.