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The project analyzes the performance of pattern-matching algorithms on pseudo-randomly generated texts of 500,000 characters. Tests were conducted using alphabets of sizes 2 and 70, with pattern le…
Application using LLM models to explain pattern matching algorithms and their performance metrics. This project integrates the RAG (Retrieval-Augmented Generation) technique and vector embeddings t…