viii PREFACE material in the book),as would courses in real analysis,numerical methods, or elementary number theory.We draw on all of these areas,but summarize the necessary material here,with reference to standard texts for people who want more information. Programming experience equivalent to one or two semesters'study at the college level,including elementary data structures,is assumed.We do not dwell on programming and implementation issues,but algorithms and data structures are the central object of our studies.Again,our treatment is complete in the sense that we summarize basic information,with reference to standard texts and primary sources. Related books.Related texts include The Art of Computer Programming by Knuth;Algorithms,Fourth Edition,by Sedgewick and Wayne;Introduction to Algorithms by Cormen,Leiserson,Rivest,and Stein;and our own Analytic Combinatorics.This book could be considered supplementary to each of these. In spirit,this book is closest to the pioneering books by Knuth.Our fo- cus is on mathematical techniques of analysis,though,whereas Knuth's books are broad and encyclopedic in scope,with properties of algorithms playing a primary role and methods of analysis a secondary role.This book can serve as basic preparation for the advanced results covered and referred to in Knuth's books.We also cover approaches and results in the analysis of algorithms that have been developed since publication of Knuth's books. We also strive to keep the focus on covering algorithms of fundamen- tal importance and interest,such as those described in Sedgewick's Algorithms (now in its fourth edition,coauthored by K.Wayne).That book surveys classic algorithms for sorting and searching,and for processing graphs and strings. Our emphasis is on mathematics needed to support scientific studies that can serve as the basis of predicting performance of such algorithms and for com- paring different algorithms on the basis of performance. Cormen,Leiserson,Rivest,and Stein's Introduction to Algorithms has emerged as the standard textbook that provides access to the research litera- ture on algorithm design.The book (and related literature)focuses on design and the theory of algorithms,usually on the basis of worst-case performance bounds.In this book,we complement this approach by focusing on the aral- ysis of algorithms,especially on techniques that can be used as the basis for scientific studies (as opposed to theoretical studies).Chapter 1 is devoted entirely to developing this context. www.it-ebooks.infoviii P Ş ő Œ ō ŏ ő material in the book), as would courses in real analysis, numerical methods, or elementary number theory. We draw on all of these areas, but summarize the necessary material here, with reference to standard texts for people who want more information. Programming experience equivalent to one or two semesters’ study at the college level, including elementary data structures, is assumed. We do not dwell on programming and implementation issues, but algorithms and data structures are the central object of our studies. Again, our treatment is complete in the sense that we summarize basic information, with reference to standard texts and primary sources. Related books. Related texts include Ļe Art of Computer Programming by Knuth; Algorithms, Fourth Edition, by Sedgewick and Wayne; Introduction to Algorithms by Cormen, Leiserson, Rivest, and Stein; and our own Analytic Combinatorics. Ļis book could be considered supplementary to each of these. In spirit, this book is closest to the pioneering books by Knuth. Our fo￾cus is on mathematical techniques of analysis, though, whereas Knuth’s books are broad and encyclopedic in scope, with properties of algorithms playing a primary role and methods of analysis a secondary role. Ļis book can serve as basic preparation for the advanced results covered and referred to in Knuth’s books. We also cover approaches and results in the analysis of algorithms that have been developed since publication of Knuth’s books. We also strive to keep the focus on covering algorithms of fundamen￾tal importance and interest, such as those described in Sedgewick’s Algorithms (now in its fourth edition, coauthored by K.Wayne). Ļat book surveys classic algorithms for sorting and searching, and for processing graphs and strings. Our emphasis is on mathematics needed to support scientiŀc studies that can serve as the basis of predicting performance of such algorithms and for com￾paring different algorithms on the basis of performance. Cormen, Leiserson, Rivest, and Stein’s Introduction to Algorithms has emerged as the standard textbook that provides access to the research litera￾ture on algorithm design. Ļe book (and related literature) focuses on design and the theory of algorithms, usually on the basis of worst-case performance bounds. In this book, we complement this approach by focusing on the anal￾ysis of algorithms, especially on techniques that can be used as the basis for scientiŀc studies (as opposed to theoretical studies). Chapter 1 is devoted entirely to developing this context. www.it-ebooks.info