Data Structures and Algorithms with JavaScript

Once JavaScript moved beyond the browser and entered server-side programming through platforms such as Node.js, developers likewise needed classic data structures—linked lists, stacks, queues, graphs—as well as algorithms for sorting and searching. This book addresses exactly that question: in a JavaScript environment where arrays are objects, global variables are everywhere, and objects are built on prototype chains, how can traditional data structures and algorithms actually be implemented, and how can one make trade-offs among readability, code size, and execution efficiency? The book begins with JavaScript's programming environment and object model, first sorting through arrays' various accessor, mutator, and iterator methods to lay a foundation for the custom structures that follow. It then implements, in turn, lists, stacks, queues, linked lists (including doubly linked and circular lists), dictionaries, hashing (including separate chaining and linear probing for collision handling), sets, binary trees and binary search trees, and graphs for modeling network relationships, with graph algorithms including depth-first search, breadth-first search, shortest paths, and topological sorting. The final part turns to algorithms: first comparing basic sorts such as bubble, selection, and insertion sort with a timing platform, then introducing Shell sort, merge sort, and quicksort; the searching section covers sequential search, self-organizing data, and binary search; the last chapter discusses dynamic programming and greedy algorithms, using the Fibonacci sequence, longest common substring, knapsack problem, and coin-change problem as examples. Each chapter includes exercises, and the sample code can be run and modified directly.