Break-Resilient Codes

This project is a research artifact tied to a specific paper in the field of information theory. While the mathematical contribution (establishing lower bounds and near-optimal constructions for break-resilient codes) is academically significant, the software project itself lacks any indicators of a defensive moat. With 0 stars and minimal activity over 900+ days, it functions as a reference implementation rather than a library. Its primary utility is in niche applications like DNA data storage or specialized distributed systems where physical fragmentation of data carriers is a risk. Frontier labs (OpenAI, Anthropic) have zero interest in this low-level combinatorial coding theory, making the frontier risk low. The 'moat' here is the domain expertise required to implement the math, but the code itself is easily reproducible by any researcher in the space. It is unlikely to be displaced by GenAI, but also unlikely to see commercial adoption without a significant pivot into a production-ready library (e.g., as a module for something like the Python 'galois' library).