Data structures and algorithms are presented at the college level
in a highly accessible format that presents material with one-page
displays in a way that will appeal to both teachers and students.
The thirteen chapters cover: Models of Computation, Lists,
Induction and Recursion, Trees, Algorithm Design, Hashing, Heaps,
Balanced Trees, Sets Over a Small Universe, Graphs, Strings,
Discrete Fourier Transform, Parallel Computation.
Key features:
* Complicated concepts are expressed clearly in a single page
with minimal notation and without the "clutter" of the syntax of a
particular programming language; algorithms are presented with
self-explanatory "pseudo-code."
* Chapters 1-4 focus on elementary concepts, the exposition
unfolding at a slower pace. Sample exercises with solutions are
provided. Sections that may be skipped for an introductory course
are starred. Requires only some basic mathematics background and
some computer programming experience.
* Chapters 5-13 progress at a faster pace. The material is
suitable for undergraduates or first-year graduates who need only
review Chapters 1-4.
* Chapters 1-4. This book may be used for a one-semester
introductory course (based on Chapters 1-4 and portions of the
chapters on algorithm design, hashing, and graph algorithms) and
for a one-semester advanced course that starts at Chapter 5. A
yearlong course may be based on the entire book.
* Sorting, often perceived as rather technical, is not treated
as a separate chapter, but is used in many examples (including
bubble sort, merge sort, tree sort, heap sort, quick sort, and
several parallel algorithms). Also, lower bounds on sorting by
comparisons are included with thepresentation of heaps in the
context of lower bounds for comparison-based structures.
* Chapter 13 on parallel models of computation is something of a
mini-book itself, and a good way to end a course. Although it is
not clear what parallel architectures will prevail in the future,
the idea is to further teach fundamental concepts in the design of
algorithms by exploring classic models of parallel computation,
including the PRAM, generic PRAM simulation, HC/CCC/Butterfly, the
mesh, and parallel hardware area-time tradeoffs (with many
examples).
Apart from classroom use, this book serves as a good reference
on the subject of data structures and algorithms. Its
page-at-a-time format makes it easy to review material that the
reader has studied in the past.
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