This is a book on a topic that has witnessed a surge of interest over the last decade, owing in part to several novel applications, most notably in data compression and computational molecular biology. It describes methods employed in average case analysis of algorithms
, combining both analytical and probabilistic tools.
Tools are illustrated through problems on words
with applications to molecular biology, data compression, security, and pattern matching.
This book includes chapters on algorithms and data structures on words, probabilistic and analytical models, inclusion-exclusion principles, first and second moment methods, subadditive ergodic theorem and large deviations, elements of information theory, generating functions, complex asymptotic methods, Mellin transform and its applications, and analytic poissonization and depoissonization.
:) "Overall, this is a very good graduate-level textbook and a valuable (and almost self-contained) source of information for everyone interested in the analysis of algorithms."