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. Recently, Augmented Regular Expressions (AREs) havebeen proposed as a formalism to describe, recognize and learn a nontrivialclass of context-sensitive languages (CSLs) [1, 2]. AREs augmentthe expressive power of Regular Expressions (REs) by including aset of constraints, that involve the number of instances in a stringof the operands of the star operations of an RE. Although it isdemonstrated that not all the CSLs can be described by AREs, the classof representable objects includes...

Efficient recognition of a class of context-sensitive languages described by Augmented Regular Expressions