A Common-Sense Guide to Data Structures and Algorithms: Level Up Your Core Programming Skills
- 出版商: Pragmatic Bookshelf
- 出版日期: 2017-08-13
- 定價: USD $45.95
- 售價: $1,600
- 貴賓價: 9.5 折 $1,520
- 語言: 英文
- 頁數: 220
- 裝訂: Paperback
- ISBN: 1680502441
- ISBN-13: 9781680502442
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If you last saw algorithms in a university course or at a job interview, you're missing out on what they can do for your code. Learn different sorting and searching techniques, and when to use each. Find out how to use recursion effectively. Discover structures for specialized applications, such as trees and graphs. Use Big O notation to decide which algorithms are best for your production environment. Beginners will learn how to use these techniques from the start, and experienced developers will rediscover approaches they may have forgotten.
Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write code that runs faster and more efficiently, which is particularly important for today's web and mobile apps. This book takes a practical approach to data structures and algorithms, with techniques and real-world scenarios that you can use in your daily production code. Graphics and examples make these computer science concepts understandable and relevant.
Use Big O notation, the primary tool for evaluating algorithms, to measure and articulate the efficiency of your code, and modify your algorithm to make it faster. Find out how your choice of arrays, linked lists, and hash tables can dramatically affect the code you write. Use recursion to solve tricky problems and create algorithms that run exponentially faster than the alternatives. Dig into advanced data structures such as binary trees and graphs to help scale specialized applications such as social networks and mapping software. You'll even encounter a single keyword that can give your code a turbo boost. Jay Wengrow brings to this book the key teaching practices he developed as a web development bootcamp founder and educator.
Use these techniques today to make your code faster and more scalable.