What is the SSCA Linked Library?
The SSCA Linked Library is a dynamic, self-building symbol table created and modified during the life/operation of the SSCA stack. It is part of Layer 9 (Dynamic Ontology Learning) and enables progressive compression on semi-static or large files (logs, telemetry streams, metadata repositories).
Unlike static dictionaries, the Linked Library:
- Runs a first compression pass through Layers 1–8
- Records recurring character strings, tokens, or subgraphs with high frequency
- Counts occurrences in a linked data structure (hash map or trie)
- If a string exceeds a practical threshold (e.g., >50 occurrences or >5% of data), flags it for symbol reduction
- Returns to the file (or flagged sections) in a second pass to replace repeats with short symbols/references
- Yields 5–15% additional compression (up to 22% on custom repeats) with low overhead
This makes SSCA a "learning compressor" — it adapts to your data over time, getting more efficient on repeated patterns without manual intervention.
How the Linked Library Works – Visual Flow
First Pass: Compress through Layers 1–8
│
├─► Build Linked Library (hash map/trie)
│ │
│ └─ Record every recurring string/token/subgraph
│ │
│ └─ Count occurrences (frequency tracking)
│
│
├─► Threshold Check
│ │
│ ├─ If count > threshold (e.g., 50 occurrences or >5% data volume)
│ │ │
│ │ └─ Flag for symbol reduction
│ │
│ └─ Else → Keep as-is (no change)
│
│
└─► Second Pass: Return & Re-compress
│
└─ Scan flagged sections only (using pointers/indices)
│
└─ Replace repeats with short symbols/references
│
└─ Update graph (Layer 2) and packer (Layer 4)
│
└─ Output: Final .ssca file (5–22% tighter)
Lightweight & safe: Only re-processes flagged sections. Lossless — symbols map back perfectly.