Bhagvan Kommadi - Learn Data Structures and Algorithms with Golang

Eduard Bondarenko is a software developer living in Kiev, Ukraine. He started programming using Basic on a ZX Spectrum many, many years ago. Later, he worked in the web development domain. He has used Ruby on Rails for over 8 years. Having used Ruby for a long time, he discovered Clojure in early 2009, and liked the simplicity of the language. Besides Ruby and Clojure, he is interested in Go and ReasonML development.

, Data Structures and Algorithms, focuses on the definition of abstract data types, classifying data structures into linear, non-linear, homogeneous, heterogeneous, and dynamic types. Abstract data types, such as container, list, set, map, graph, stack, and queue, are presented in this chapter. This chapter also covers the performance analysis of data structures, as well as the correct choice of data structures and structural design patterns.

, Getting Started with Go for Data Structures and Algorithms, covers Go-specific data structures, such as arrays, slices, two-dimensional slices, maps, structs, and channels. Variadic functions, deferred function calls, and panic and recover operations are introduced. Slicing operations, such as enlarging using append and copy, assigning parts, appending a slice, and appending part of a slice, are also presented in this chapter.

, Linear Data Structures, covers linear data structures such as lists, sets, tuples, stacks, and heaps. The operations related to these types, including insertion, deletion, updating, reversing, and merging are shown with various code samples. In this chapter, we present the complexity analysis of various data structure operations that display accessing, search, insertion, and deletion times.

, Non-Linear Data Structures, covers non-linear data structures, such as trees, tables, containers, and hash functions. Tree types, including binary tree, binary search tree, T-tree, treap, symbol table, B- tree, and B+ tree, are explained with code examples and complexity analysis. Hash function data structures are presented, along with examples in cryptography for a variety of scenarios, such as open addressing, linear probing, universal hashing, and double hashing.

, Homogeneous Data Structures, covers homogeneous data structures such as two-dimensional and multi-dimensional arrays. Array shapes, types, literals, printing, construction, indexing, modification, transformation, and views are presented together with code examples and performance analysis. Matrix representation, multiplication, addition, subtraction, inversion, and transpose scenarios are shown to demonstrate the usage of multi-dimensional arrays.

, Heterogeneous Data Structures, covers heterogeneous data structures, such as linked lists, ordered, and unordered lists. We present the singly linked list, doubly linked list, and circular linked list, along with code samples and efficiency analysis. Ordered and unordered lists from HTML 3.0 are shown to demonstrate the usage of lists and storage management.