data structures and algorithms pdf

The implementation of the dictionary// 字典类function Dictionary () { this.add = add; this.dataStore = new Array(); this.find = find; this.remove = remove; this.showAll = showAll; this.count = count; this.clear = clear;}function add (key, value) { this.dataStore[key] = value;}function find (key) { return this.dataStore[key];}function remove (key) { delete this.dataStore[key];}function showAll () { let datakeys = Array.prototype.slice.call(Object.keys(this.dataStore)

node1.next = node3; node3.previous = node1; node3.next = node2; node2.previous = node3; node2.next = node4; node4.previous = node2; }};DList.prototype.advance = function (n, item) { let currNode = this.find(item); while (n--) { this.goPrevious(currNode); }};// 示例let names = new DList();names.insert('Mazey', 'head');names.insert('Cherrie', 'Mazey');names.insert('John', 'Cherrie');names.insert('Luna', 'John');names.insert('Ada', 'Luna'

efficiency: In a merge sort, the maximum value of this secondary storage space is not more than N, so the spatial complexity of the merge algorithm is θ (n) in order to combine the sub-sequences to use additional storage space.Time efficiency: The merging algorithm is a typical divide-and-conquer algorithm with a time complexity of 0 (n log n).　3. Algorithm examplesMergesort.javaPackage Com.test.sort.merge;public class MergeSort {/** * @param args */public static void main (string[] args) {//TO

" definition of algorithmic time complexity"At the time of the algorithm analysis, the total number of executions of the statement T (N) is a function of the problem size n, which then analyzes the change of T (n) with N and determines the order of magnitude of T (N). The time complexity of the algorithm, which is the time measurement of the algorithm, is recorded as: T (n) = O (f (n)). It indicates that with the increase of the problem size n, the growth rate of the algorithm execution time is

]; while (end>start) { while (end>startarrys[key)//If there is nothing smaller than the key value, compare next until there is a smaller swap position than the key value, And then compare it back to the past End--; if (arrys[end]) { arrys[end]; arrys[arrys[start]; arrys[tmp; } while (end>startarrys[start]) Start+ +; if (arrys[key) {

Bucket sortBarrel sequencing has been used since the 1956, and the basic idea of the algorithm is proposed by E.J.ISSAC and R.c.singleton.This algorithm is like having 11 barrels, numbered from 0~10. Each occurrence of a number, in the corresponding number of buckets put aA little flag, and then just count the few small flags in each bucket OK. For example, there are 1 small flags in bucket 2nd, indicating2 appeared once, and in the 3rd barrels there were 1 small flags, indicating that 3 appeare

can put in *, in Put +, that is abc*+.A * (b+c) turn suffix:Read a, read *, later found (can not be placed *, (B+C * Priority High, read, followed by), can be changed to bc+, and a * together, that is abc+*.This is a queue, but the structure to use is the stack, because it comes in. The arithmetic here does not have to be pressed into the stack, directly output.a+b-c Turn suffix:Direct output A, read +, stack empty press into the stack, then output B, stack non-empty, pop +, read to-,+ priority

and J to point to the leftmost and rightmost of the sequence, respectively. At first, the variable I points to the leftmost part of the sequence, which is the number 6, and J points to the far right of the sequence, pointing to the number 8, as shown inFirst J moves from right to left, so long as it finds a number smaller than 6, it stops, and J is in the 5 position. I then start from left to right, as long as I find a number greater than 6 to stop, so it to the position of 7This is where the t

Using system;using system.collections.generic;using system.linq;using system.text;using System.Threading.Tasks; Namespace selectsort{class Program {static void Main (string[] args) {int[] Arry = {1, 4, 5,6,2,9,0,8,3,10}; Selectesort (Arry, Arry. Length); for (int i = 0; i Because of the two for loops, the time complexity is O (n^2), which is a simple but very slow sort.Selection and sequencing of algorithms and

Note: This blog is my understanding of the data structure, many local understanding may not be appropriate, but also ask the reader to learn dialecticallyUnderstanding data structures from the macro levelMany times we have been working hard, but don't know why ...After a year of work, re-think of the university's data

: Network Disk DownloadContent Introduction······In the book on algorithms, some are very rigorous, but not comprehensive enough, others involve a lot of subject matter, but lack of rigor. This book will be rigorous and comprehensive integration, in-depth discussion of various algorithms, and focus on the design and analysis of these algorithms can be accepted at

First, insert sortWhat is insert sort: insert sort is to insert a value into an ordered data by size, and after inserting the value, the data is still in order.Time complexity for inserting sorting: The large O method is O (n^2). But more quickly than bubble sort and select sortTo insert a sort plot:　　　　　　　　Specific Java code: Public classInsertsort {int[] Array =NULL; @Test Public voidTestinsertsort () {ar

Some of the books on algorithms are very rigorous, but not comprehensive, others involve a lot of subject matter, but lack rigor. The introduction of the Algorithm (the 3rd edition of the original book)/Computer science series combines rigor and comprehensiveness into an in-depth discussion of various algorithms and focuses on the design and analysis of these algorithms