Compared to What?: An Introduction to the Anaylsis of Algorithms,New

Compared to What?: An Introduction to the Anaylsis of Algorithms,New

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compared to what? covers all the basics of algorithm analysis but it does not just supply algorithms to memorize it lets you guide your students through the process of breaking down and solving aigolithmic problems. The invaluable analytic skills developed through this innovative approach will appiv to anj, programming assignmentno matter the size of the problem or the language and macnine used. The book does not assume a high degree of familiarity with discrete mathematicsin fact, all mathematical concepts crucial to algorithm analysis are explained in the appendices. Each chapter centers on a basic problem and works through a variety of available . options for its solution rather than declaring a single best answer. Within the chapters, carefully orchestrated. 'Pauses'helpful questions and strategy suggestionspoint students to workable solutions and to increasinglv more advanced variations and applications. Endofchapter 'Codas' restate each chapter's major themes and guide the transition into the next set of problems. Compared to What? will help students analyze problems, determine what needs to be optimized, and pinpoint inefficiencies and inaccuracies in their programs. Its friendlv but challenging style, inventive examples 'and analogies, descriptions of stateoftheart applications, and pragmatic focus will help you teach students to create algorithmic solutionsnot merely memorize them.

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To facilitate a smooth return process, a Return Authorization (RA) Number is required for all returns. Returns without a valid RA number will be declined and may incur additional fees. You can request an RA number within 15 days of the original delivery date. For more details, please refer to our Return & Refund Policy page.

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Warranty

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If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.

This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).

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Frequently Asked Questions

  • Q: What topics are covered in 'Compared to What?: An Introduction to the Analysis of Algorithms'? A: The book covers the basics of algorithm analysis, including problem-solving techniques, optimization strategies, and various algorithms. It explains mathematical concepts crucial to algorithm analysis in the appendices.
  • Q: Is prior knowledge of discrete mathematics required to understand this book? A: No, the book does not assume a high degree of familiarity with discrete mathematics. Key mathematical concepts are explained in the appendices, making it accessible for beginners.
  • Q: How is the book structured to facilitate learning? A: Each chapter focuses on a basic problem and presents multiple solution options. Pauses with helpful questions guide students toward workable solutions, and end-of-chapter 'Codas' summarize major themes and transition into new problems.
  • Q: What is the condition of the book being sold? A: The book is listed as a 'Used Book in Good Condition,' indicating it may have some wear but is overall in acceptable shape for reading and studying.
  • Q: Who is the author of this book? A: The author of 'Compared to What?' is Gregory J.E. Rawlins.
  • Q: What is the page count of the book? A: The book contains 536 pages.
  • Q: When was this book published? A: The book was published on November 15, 1991.
  • Q: What type of binding does the book have? A: The book is available in hardcover binding, providing durability and a professional appearance.
  • Q: Can this book help with programming assignments? A: Yes, the book helps students analyze problems and develop algorithmic solutions, making it valuable for programming assignments of any size or language.
  • Q: What is the main goal of 'Compared to What?'? A: The main goal of the book is to teach students to analyze problems, optimize solutions, and identify inefficiencies in their programming, rather than just memorizing algorithms.