Description
Most professional programmers that I've encountered are not well prepared to tacklealgorithmdesignproblems.Thisisapity, becausethetechniquesofalgorithm design form one of the core practical technologies of computer science. Designing correct, e?cient, and implementable algorithms for real-world problems requires access to two distinct bodies of knowledge: - Techniques - Good algorithm designers understand several fundamental - gorithm design techniques, including data structures, dynamic programming, depth-?rst search, backtracking, and heuristics. Perhaps the single most - portantdesigntechniqueismodeling, theartofabstractingamessyreal-world application into a clean problem suitable for algorithmic attack. - Resources - Good algorithm designers stand on the shoulders of giants. Ratherthanlaboringfromscratchtoproduceanewalgorithmforeverytask, they can ?gure out what is known about a particular problem. Rather than re-implementing popular algorithms from scratch, they seek existing imp- mentations to serve as a starting point. They are familiar with many classic algorithmic problems, which provide su?cient source material to model most any application. This book is intended as a manual on algorithm design, providing access to combinatorial algorithm technology for both students and computer professionals.
Author: Steven S. Skiena
Publisher: Springer
Published: 10/06/2020
Pages: 793
Binding Type: Hardcover
Weight: 3.25lbs
Size: 9.21h x 6.93w x 1.50d
ISBN13: 9783030542559
ISBN10: 3030542556
BISAC Categories:
- Computers | Programming | Algorithms
- Computers | Computer Science
- Computers | Data Science | General
Author: Steven S. Skiena
Publisher: Springer
Published: 10/06/2020
Pages: 793
Binding Type: Hardcover
Weight: 3.25lbs
Size: 9.21h x 6.93w x 1.50d
ISBN13: 9783030542559
ISBN10: 3030542556
BISAC Categories:
- Computers | Programming | Algorithms
- Computers | Computer Science
- Computers | Data Science | General
About the Author
Dr. Steven S. Skiena is Distinguished Teaching Professor of Computer Science at Stony Brook University, with research interests in data science, natural language processing, and algorithms. He was awarded the IEEE Computer Science and Engineering Undergraduate Teaching Award "for outstanding contributions to undergraduate education ...and for influential textbooks and software."