The book's comprehensive, self-contained coverage will give readers the knowledge they need to stay up to date on new research as well as help them understand the difficulties facing the field. Advanced results are covered in the authors' monograph Analytic Combinatorics and Donald Knuth's The Art of Computer Programming books.

Despite increased interest, practitioners, academics, and students have rarely had direct access to basic information on techniques and models for mathematically assessing algorithms. By thoroughly addressing fundamental methods and outcomes in the subject, this book collects and delivers that information.

The authors combined discrete mathematics, basic real analysis, combinatorics, algorithms, and data structures, drawing on both classical mathematics and computer science. They place a strong emphasis on the mathematics required to support scientific research that may be used to forecast algorithm performance and compare various algorithms based on performance.

Recurrences, generating functions, asymptotics, and analytic combinatorics are among the methods discussed in the first half of the book. Permutations, trees, strings, attempts, and mappings are some of the structures that are covered in the second half of the book. Throughout, numerous examples are used to illustrate how applications to the analysis of algorithms, which are essential to the development of our contemporary computational infrastructure, might be used.