LithosAnanake/docs/working/archive/research

Research

This directory contains academic research, publication materials, grant proposals, and scholarly documentation for StarForth.

Contents

• doe-metrics-schema.md - Design of Experiments metrics schema
• literature-review.md - Related work and citations
• research-outline.md - Research roadmap and objectives
• results-for-publication.md - Publication-ready experimental results

Key Research Contributions

1. Physics-Grounded Self-Adaptive Runtime

StarForth demonstrates a novel approach to VM optimization:

• Execution heat model based on thermodynamic metaphor
• Rolling window of truth for deterministic metric seeding
• Inference engine for adaptive parameter tuning

2. Formally Proven Deterministic Behavior

0% algorithmic variance across 90 experimental runs:

• Deterministic heat decay (Loop #3)
• Deterministic window width inference (Loop #5)
• Deterministic pipelining metrics (Loop #4)
• Reproducible across platforms

3. Design of Experiments Methodology

Rigorous experimental approach:

• Factorial DoE for multi-factor analysis
• Statistical validation (ANOVA, Levene's test)
• Heartbeat-driven data collection
• Reproducible protocols

Publications

Peer Review Materials

Comprehensive peer review submission package available in: ../archive/phase-1/Reference/physics_experiment/PEER_REVIEW_SUBMISSION/

Includes:

• Main paper draft
• Formal verification interpretation
• Variance analysis summary
• Supplementary materials

Grant Proposals

• DARPA SSM Proposal: ../DARPA_SSM_Proposal_James.pdf
• Provisional Patent Application: Filed [date]

Publication Process

1. Conduct Experiments

   • Design: ../02-experiments/
   • Execute: Run DoE mode
   • Validate: ../04-quality/validation/

2. Document Findings

   • Results: results-for-publication.md
   • Analysis: DoE analysis scripts
   • Metrics: doe-metrics-schema.md

3. Prepare Submission

   • Draft paper using templates
   • Generate figures and tables
   • Format for target venue

4. Review & Submit

   • Internal review
   • Submit to conference/journal
   • Respond to reviewers

References & Citations

External References

• prog-prove.pdf - Formal verification methodologies
• SYSTEM_NARRATIVE.pdf - System architecture narrative

Related Work

See literature-review.md for comprehensive list of related research in:

• Adaptive virtual machines
• JIT compilation
• Thermodynamic computing models
• Self-optimizing systems

For Researchers

Citing StarForth:

James, R. (2025). StarForth: A Physics-Grounded Self-Adaptive FORTH-79 VM
with Formally Proven Deterministic Behavior. [Venue TBD]

Experimental Reproducibility: All experiments are reproducible:

make fastest
./build/amd64/fastest/starforth --doe

Results should show 0% algorithmic variance.

Contact

For research collaboration or questions:

• Project repository: [GitHub URL after migration]
• Principal investigator: [Contact info]