3-6-9 n-slot

Abstract

Abstract This dataset and software repository presents the formal implementation and theoretical framework of the Slot-Based Technical Taxonomy Model (N-Slot Engine). Evolving from a baseline 3-slot architecture (Header + Core + Modifier), this framework introduces deterministic 6-slot and 9-slot positional grammar schemas designed for zero-allocation boundary isolation across complex, un-indexed text corpora and dense industrial telemetry streams. The core computational engine is written in compiled Rust, leveraging static string slicing (&'a str) and regex-driven deterministic finite automata (DFA) state machines to achieve microsecond execution speeds with zero heap memory allocation during parsing loops. Taxonomy Architecture & Slot Decompositions The model treats incoming tokens or byte arrays as structured, positional ledgers rather than unstructured strings: 3-Slot Base Model: [Slot 1: Header/Scope] + [Slot 2: Subject Core] + [Slot 3: Modifier/Terminal] Application: Rapid corpus indexing, preliminary token segmentation, and lightweight token classification. 6-Slot Standard Model: [Slot 1: Scope] + [Slot 2: Operator] + [Slot 3: Core Stem] + [Slot 4: Infix/State] + [Slot 5: Suffix] + [Slot 6: Trailer] Application: Granular character/glyph boundary isolation (MS 408 folios), morphological affix mapping, and standard industrial CAN bus frame decoding. 9-Slot High-Resolution Model: [Slot 1: Macro Scope] + [Slot 2: Header] + [Slot 3: Opcode] + [Slot 4: Root Payload] + [Slot 5: Primary Infix] + [Slot 6: Modifier] + [Slot 7: Primary Suffix] + [Slot 8: Meta Suffix] + [Slot 9: Delimiter] Application: Ultra-high-resolution positional grammar parsing, pre-filtering for edge vector database indexing (Qdrant/Milvus), and complex SCADA/IoT event logging. Dual-Domain Applications Computational Cryptanalysis & Historical Manuscripts (MS 408 / Voynich): Provides a reproducible, open-access taxonomy framework to test positional character stability, glyph-cluster dependencies, and prefix/infix/suffix distributions across 35,000+ non-standardized manuscript tokens without relying on modern natural language assumptions. Edge Telemetry & Embedded Computing: Functions as an embedded, zero-cost abstraction engine that parses, compresses, and indexes raw byte streams directly on edge hardware (ARM64/Android/Linux) prior to cloud transmission, reducing bandwidth overhead and compute latency. Technical Specifications & Contents Implementation Language: Rust (Edition 2021) Dependencies: Pure-Rust SSL (rustls-tls), serde, regex, csv Included Assets: Compiled Rust engine source code (src/main.rs), configuration manifests (Cargo.toml), benchmark execution scripts, and output CSV datasets containing multi-slot token breakdowns.