1. A method of sequentially transforming an original data sequence comprising a plurality of symbols and associated with a known context model into an irreducible context-dependant grammar from which the original data can be fully recovered, wherein the irreducible context-dependent grammar is represented by a set of production rules which are formed using a set of pairs of variables and contexts representing non-overlapping repeated patterns and contexts in the data sequence, the method applicable to any countable context model and comprising the steps of: (a) parsing a substring from the sequence, wherein the substring is the longest prefix of a string of previously unparsed symbols of the sequence that can be represented, under the context of the current time instant, by a variable within the set of variables of a previous irreducible context-dependent grammar other than the initial variable in the initial pair of the set of pairs of variables and contexts if such a prefix exists, and otherwise a first symbol of the string of the previously unparsed symbols in the sequence; (b) generating an admissible context-dependent grammar based on the substring, the current context, and the previous irreducible context-dependent grammar; (c) applying at least one set of reduction rules to the admissible context-dependent grammar to generate a new irreducible context-dependent grammar; (d) repeating steps (a) through (c) until all of the symbols of the sequence are represented by the final irreducible context-dependent grammar.