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Preprint . 2026
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
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Sadhana Programming Language v1.0 — A Meaning-First, Order-Free, Time-Latent Programming Language

Authors: Parihar, Manish Kumar;

Sadhana Programming Language v1.0 — A Meaning-First, Order-Free, Time-Latent Programming Language

Abstract

Sadhana (Sanskrit: साधना) is an experimental meaning-first programming language and AGI alignment research framework. It compiles declarative entity-relation specifications into executable code across seven target backends: HTML/CSS, Python, SQL, Rust, Go, Java, and C++. Primary contributions include: (1) the Canonical Meaning Kernel (CMK), an invariant five-part semantic fingerprint; (2) the Bija reversible semantic encoding system inspired by Sanskrit grammar; and (3) the Sandhi Engine for mandatory meaning composition. The language is grounded in Panini's Ashtadhyayi (5th c. BCE) and Sankhya philosophy. The compiler is a single 3,587-line pure Python file with zero external dependencies. This record includes the full compiler (sadhana.py), demonstration files, and the accompanying academic paper (PDF). License: MIT. Repository: https://github.com/nickzq7/Sadhana-Programming-LanguageDeveloper "" Idea - Manish Kumar PariharResearch - Manish Kumar PariharAssembler - Manish Kumar PariharReasoning - Manish Kumar PariharQuality Check - Manish Kumar PariharStudy - Manish Kumar PariharFramework Design - Manish Kumar PariharCoder - Prompt Engineering(75%) + Online Reference (10%) + Manish Kumar Parihar (15%) ""

Keywords

AGI alignment, Sanskrit, Panini, meaning-first, Bija, semantic computing, programming language, code generation, CMK, order-independence, compiler, Guna, Python

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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