Add documentation for innovative JSON repair ideas #2
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This commit introduces several new markdown files in the root directory, expanding on innovative concepts for the JsonRemedy library, largely inspired by the existing `docs/design/1.md`. The new files are: - `INNOVATIONS_IN_JSON_REPAIR.md`: Summarizes foundational concepts like the probabilistic repair model, cost system, beam search, enhanced contextual awareness, and declarative rule sets. - `PROBABILISTIC_REPAIR_MODEL.md`: Elaborates on the mechanics of the cost system (how costs are defined and influenced) and the beam search engine (workflow, beam width trade-offs, interaction with layers). - `ADVANCED_HEURISTICS.md`: Explores ideas for more sophisticated heuristics, methods for enriching the `JsonContext` (e.g., N-gram token history, structural depth, key duplication tracking), and examples of advanced rules for the declarative rule set. - `ADAPTIVE_REPAIR.md`: Discusses potential future-state capabilities like dynamic cost adjustments, learning common non-standard patterns from specific sources, adaptive beam width, and using statistical heuristics from data corpora. These documents aim to iterate on and build out the vision for a world-class, intelligent JSON repair library in Elixir.
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This commit introduces several new markdown files in the root directory, expanding on innovative concepts for the JsonRemedy library, largely inspired by the existing
docs/design/1.md.The new files are:
INNOVATIONS_IN_JSON_REPAIR.md: Summarizes foundational concepts like the probabilistic repair model, cost system, beam search, enhanced contextual awareness, and declarative rule sets.PROBABILISTIC_REPAIR_MODEL.md: Elaborates on the mechanics of the cost system (how costs are defined and influenced) and the beam search engine (workflow, beam width trade-offs, interaction with layers).ADVANCED_HEURISTICS.md: Explores ideas for more sophisticated heuristics, methods for enriching theJsonContext(e.g., N-gram token history, structural depth, key duplication tracking), and examples of advanced rules for the declarative rule set.ADAPTIVE_REPAIR.md: Discusses potential future-state capabilities like dynamic cost adjustments, learning common non-standard patterns from specific sources, adaptive beam width, and using statistical heuristics from data corpora.These documents aim to iterate on and build out the vision for a world-class, intelligent JSON repair library in Elixir.