DMC (Deterministic Markov Chain)

DMCA is a symbolic semantic memory system designed to complement and extend traditional vector databases. It serves as the foundation for FixCom's intelligent, AI-assisted release note generator

DMCA is to power the backend of FixCom, a tool that automates Git commit summarization, changelog generation, and release note authoring using small quantized models.

FixCom already:

• Parses commits into hunks
• Summarizes each hunk independently using tiny LLMs (less context rot)
• Aggregates hunks into commit-level summaries
• Tags hunks using Ctags, and stores keywords in a vector DB
• Segments release notes by gathering hunks related to a given keyword
• However, this system is limited: the vector DB lacks semantic understanding, relationship modeling, and context merging.

DMCA addresses the limitations of static keyword search by constructing a symbolic Markov graph, where:

• Nodes represent source-level entities (e.g., functions, classes, variables) and semantic concepts (e.g., "thread-safe", "render pipeline").
• Edges represent probabilistic transitions between symbols based on co-occurrence, file proximity, call relations, or summarizer keywords.
• Commits are modeled as subgraphs, giving them semantic “footprints.”
• Features (like threading changes, renderer refactors, etc.) are inferred as connected regions of the graph.

This allows DMCA to:

• Discover semantically related commits automatically
• Merge related concepts and track refactors over time
• Build structured, modular release notes per feature
• Provide full explainability without large LLMs

 Git Repo
│
▼
[ FixCom Hunks ]
│
+-----┴------+-----------------------------+
| | |
Small Model ➜ Summary Extract CTags
| |
Commit Summary ◄───────────── Tag/Concept Mapping
| |
+-------------→ [ DMCA Graph ] ←----------+
│
▼
Graph Regions + Commit Subgraphs
│
▼
[ DMCA Output ]
│
▼
FixCom Generates Release Notes