Название: Go Data Structures and AlgorithmsАвтор: Christopher Fox
Издательство: bookboon.com
Год: 2018
Страниц: 374
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.2 MB
A concise introduction to data structures and algorithms in Go. Data structures are presented in a container hierarchy that includes stacks and queues as non-traversable dispensers, and lists, sets, and maps as traversable collections. Algorithm analysis is introduced and applied to linear and binary search, bubble sort, selection sort, insertion sort, merge sort and quicksort. The book also covers heaps and heapsort, unbalanced binary search trees, AVL trees, 2-3 trees, hashing, graph representations, and graph algorithms based on depth-and breadth-first search.
Typical algorithms and data structures textbooks are seven or eight hundred pages long, include chapters about software engineering and the programming language used in the book, and include appendices with yet more information about the programming language. Often they include lengthy case studies with tens of pages of specifications and code. Frequently they are hardcover books printed in two colors; sometimes they have sidebars with various sorts of supplementary material. All of these characteristics make these textbooks very expensive (and very heavy), but in my experience, relatively few students take advantage of the bulk of this material and few appreciate these books’ many features: much of the time and money lavished on these texts is wasted on their readers.
Students seem to prefer dealing with only essential material compressed into the fewest number of pages. Perhaps this is attributable to habits formed by life on the Internet, or perhaps it is due to extreme pragmatism. But whatever the reason, it seems very difficult to persuade most computer science students to engage with long texts, large examples, and extra material, no matter how well it is presented and illustrated. This text is a response to this tendency.
This text covers the usual topics in an introductory survey of algorithms and data structures, but it does so in under 200 pages. There are relatively few examples and no large case studies. Code is presented in Go (more about this in a moment), but the book does not teach Go and it does not include reference material about the language. There are no sidebars and the book is in black and white. The book does include features of pedagogical value: every chapter has review questions with answers, and a set of exercises. There is also a glossary at the end. The book (and versions of it using other programming languages) has been used successfully for several years to teach introductory algorithms and data structures at James Madison University. Many students have commented appreciatively regarding its brevity, clarity, and low cost.
Ideally, a language for algorithms and data structures would be easy to learn (so as to leave time for learning algorithms and data structures), support data abstraction well, provide a good development environment, and engage students. Go is a fairly small language that can be learned quite easily, especially if the portions of the language about concurrency are left out. Go is not object-oriented, which makes it smaller and simpler, but it has a rich, modern type system with exactly the features needed to support data abstraction. Go is statically typed and its compiler gives good error messages, which helps novice programmers. Go is a relatively new language from Google, and many students are interested in learning it. Overall, Go is an excellent choice for teaching algorithms and data structures.
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