String-rewriting systems
Handbook of formal languages, vol. 1
Efficient Algorithms for Lempel-Zip Encoding (Extended Abstract)
SWAT '96 Proceedings of the 5th Scandinavian Workshop on Algorithm Theory
Complexity of Language Recognition Problems for Compressed Words
Jewels are Forever, Contributions on Theoretical Computer Science in Honor of Arto Salomaa
Testing Equivalence of Morphisms on Context-Free Languages
ESA '94 Proceedings of the Second Annual European Symposium on Algorithms
Word Problems and Membership Problems on Compressed Words
SIAM Journal on Computing
Querying and embedding compressed texts
MFCS'06 Proceedings of the 31st international conference on Mathematical Foundations of Computer Science
Efficient computation in groups via compression
CSR'07 Proceedings of the Second international conference on Computer Science: theory and applications
Processing compressed texts: a tractability border
CPM'07 Proceedings of the 18th annual conference on Combinatorial Pattern Matching
Faster fully compressed pattern matching by recompression
ICALP'12 Proceedings of the 39th international colloquium conference on Automata, Languages, and Programming - Volume Part I
One-Variable word equations in linear time
ICALP'13 Proceedings of the 40th international conference on Automata, Languages, and Programming - Volume Part II
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The algorithmic problem of whether a compressed string is accepted by a (nondeterministic) finite state automaton with compressed transition labels is investigated. For string compression, straight-line programs (SLPs), i.e., contextfree grammars that generate exactly one string, are used. Two algorithms for this problem are presented. The first one works in polynomial time, if all transition labels are nonperiodic strings (or more generally, the word length divided by the period is bounded polynomially in the input size). This answers a question of Plandowski and Rytter. The second (nondeterministic) algorithm is an NP-algorithm under the assumption that for each transition label the period is bounded polynomially in the input size. This generalizes the NP upper bound for the case of a unary alphabet, shown by Plandowski and Rytter.