Researchers have introduced Flashback, a novel reversible string decomposition method that operates by peeling maximal leading and trailing character runs from an input. This process records each pair as a bilateral token, with both decomposition and reconstruction achieving O(n) time and space complexity. A key finding is the run-pairing theorem, which establishes Flashback's equivalence to pairing runs from the string's ends inward, yielding a token count of 1+[r/2] for strings with r maximal runs. AI
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IMPACT Introduces a novel string decomposition technique with potential applications in data compression and sequence analysis.
RANK_REASON Academic paper detailing a new string decomposition algorithm.