Fundamental Data Structures In JavaScript
Data structures in JavaScript
Here is a website I created to practice data structures!
Resources (article contentbelow):
Videos
- Here is a website I created to practice data structures!
- Abdul Bari: YouTubeChannel for Algorithms
- Data Structures and algorithms
- Data Structures and algorithms Course
- Khan Academy
- Data structures by mycodeschool
- MIT 6.006: Intro to Algorithms(2011)
- Data Structures and Algorithms by Codewithharry
Books
- Introduction to Algorithms
- Competitive Programming 3
- Competitive Programmers Hand Book
- Data Structures and Algorithms Made Easy
- Learning Algorithms
Coding Practice
- LeetCode
- InterviewBit
- Codility
- HackerRank
- Project Euler
- Spoj
- Google Code Jam practice problems
- HackerEarth
- Top Coder
- CodeChef
- Codewars
- CodeSignal
- CodeKata
- Firecode
Courses
Guides
- The best-case complexity: when the data looks the best
- The worst-case complexity: when the data looks the worst
- The average-case complexity: when the data looks average
space
The space complexity represents the memory consumption of a data structure. As for most of the things in life, you can't have it all, so it is with the data structures. You will generally need to trade some time for space or the other way around.
time
The time complexity for a data structure is in general more diverse than its space complexity.
Several operations
In contrary to algorithms, when you look at the time complexity for data structures you need to express it for several operations that you can do with data structures. It can be adding elements, deleting elements, accessing an element or even searching for an element.
Dependent ondata
Something that data structure and algorithms have in common when talking about time complexity is that they are both dealing with data. When you deal with data you become dependent on them and as a result the time complexity is also dependent of the data that you received. To solve this problem we talk about 3 different time complexity.
Big Onotation
The complexity is usually expressed with the Big O notation. The wikipedia page about this subject is pretty complex but you can find here a good summary of the different complexity for the most famous data structures and sorting algorithms.
The Array data structure
Definition
An Array data structure, or simply an Array, is a data structure consisting of a collection of elements (values or variables), each identified by at least one array index or key. The simplest type of data structure is a linear array, also called one-dimensional array. From Wikipedia
Arrays are among the oldest and most important data structures and are used by every program. They are also used to implement many other data structures.
Complexity Average Access Search Insertion Deletion
O(1) O(n) O(1) O(n)
class ArrayADT {
constructor() {
this.array = [];
}
add(data) {
this.array.push(data);
}
remove(data) {
this.array = this.array.filter((current) = current !== data);
}
search(data) {
const foundIndex = this.array.indexOf(data);
if (foundIndex === -1) {
return foundIndex;
}
return
null;
}
getAtIndex(index) {
return this.array[index];
}
length() {
return this.array.length;
}
print() {
console.log(this.array.join(" "));
}
}
const array = new
ArrayADT();
console.log("const array = new ArrayADT();: ", array);
console.log("-------------------------------");
console.log("array.add(1):
", array.add(1));
array.add(3);
array.add(4);
console.log(
"array.add(2);: ",
array.add(2),
"array.add(3);",
array.add(3),
"array.add(4); ",
array.add(4)
);
console.log("-------------------------------");
array.print();
console.log("-------------------------------");
console.log("search 3
gives index 2:", array.search(3));
console.log("-------------------------------");
console.log("getAtIndex
2 gives 3:", array.getAtIndex(2));
console.log("-------------------------------");
console.log("length is
4:", array.length());
console.log("-------------------------------");
array.remove(3);
array.print();
console.log("-------------------------------");
array.add(5);
array.add(5);
array.print();
console.log("-------------------------------");
array.remove(5);
array.print();
console.log(
"-------------------------------" );
/*
~ final : (master) node 01-array.js
const array = new ArrayADT();: ArrayADT { array: [] }
-------------------------------
array.add(1): undefined
array.add(2);: undefined array.add(3); undefined array.add(4); undefined
-------------------------------
1 3 4 2 3 4
-------------------------------
search 3 gives index 2: null
-------------------------------
getAtIndex 2 gives 3: 4
-------------------------------
length is 4: 6
-------------------------------
1 4 2 4
-------------------------------
1 4 2 4 5 5
-------------------------------
1 4 2 4
-------------------------------
~ final : (master)
*/
indexvalue0 … this is the first
value,
stored at zero position
1. The index of an array runs in
sequence
2. This could be useful for storing
data
that are required to be ordered, such as rankings or queues
3. In JavaScript, array's value
could be
mixed; meaning value of each index could be of different data, be it String,
Number or even Objects
// 1. Creating Arrays
let firstArray = ["a","b","c"];
let secondArray = ["d","e","f"];
// 2. Access an Array Item
console.log(firstArray[0]); // Results: "a"
// 3. Loop over an Array
firstArray.forEach(function(item, index, array){
console.log(item, index);
});
// Results:
// a 0
// b 1
// c 2
// 4. Add new item to END of
array
secondArray.push('g');
console.log(secondArray);
// Results: ["d","e","f", "g"]
// 5. Remove item from END
of array
secondArray.pop();
console.log(secondArray);
// Results: ["d","e","f"]
// 6. Remove item from FRONT
of array
secondArray.shift();
console.log(secondArray);
// Results: ["e","f"]
// 7. Add item to FRONT of
array
secondArray.unshift("d");
console.log(secondArray);
// Results: ["d","e","f"]
// 8. Find INDEX of an item
in array
let position = secondArray.indexOf('f');
// Results: 2
// 9. Remove Item by Index
Position
secondArray.splice(position, 1);
console.log(secondArray);
// Note, the second argument, in this case "1",
// represent the number of array elements to be removed
// Results: ["d","e"]
// 10. Copy an Array
let shallowCopy = secondArray.slice();
console.log(secondArray);
console.log(shallowCopy);
// Results: ShallowCopy === ["d","e"]
// 11. JavaScript properties
that BEGIN with a digit MUST be accessed using bracket notation
renderer.3d.setTexture(model, 'character.png'); // a syntax error
renderer['3d'].setTexture(model, 'character.png'); // works properly
// 12. Combine two Arrays
let thirdArray = firstArray.concat(secondArray);
console.log(thirdArray);
// ["a","b","c", "d", "e"];
// 13. Combine all Array
elements into a string
console.log(thirdArray.join()); // Results: a,b,c,d,e
console.log(thirdArray.join('')); // Results: abcde
console.log(thirdArray.join('-')); // Results: a-b-c-d-e
// 14. Reversing an Array
(in place, i.e. destructive)
console.log(thirdArray.reverse()); // ["e", "d",
"c", "b", "a"]
// 15. sort
let unsortedArray = ["Alphabet", "Zoo",
"Products", "Computer Science", "Computer"];
console.log(unsortedArray.sort());
// Results: ["Alphabet", "Computer", "Computer
Science", "Products", "Zoo" ]
2. Objects
Think of objects as a logical
grouping of a
bunch of properties.
Properties could be some variable
that it's
storing or some methods that it's using.
I also visualize an object as a
table.
The main difference is that
object's
"index"
need not be numbers and is not necessarily sequenced.
// 16. Creating an Object
let newObj = {
name: "I'm an object",
values: [1,10,11,20],
others: '',
"1property": 'example of property name starting with digit'
};
// 17. Figure out what
keys/properties are in an object
console.log(Object.keys(newObj));
// Results: [ 'name', 'values', 'others', '1property' ]
// 18. Show all values
stored in the object
console.log(Object.values(newObj));
// Results:
// [ 'I\'m an object',
// [ 1, 10, 11, 20 ],
// '',
// 'example of property name starting with digit' ]
// 19. Show all key and
values of the object
for (let [key, value] of Object.entries(newObj)) {
console.log(`${key}: ${value}`);
}
// Results:
// name: I'm an object
// values: 1,10,11,20
// others:
// 1property: example of property name starting with digit
// 20. Accessing Object's
Properties
// Two different ways to access properties, both produce same results
console.log(newObj.name);
console.log(newObj["name"]);
// But if the property name
starts with a digit,
// we CANNOT use dot notation
console.log(newObj["1property"]);
// 21. Adding a Method to an
Object
newObj.helloWorld = function(){
console.log("Hello World from inside an object!");
}
// 22. Invoking an Object's
Method
newObj.helloWorld();
The Hash Table
Definition
A Hash Table (Hash
Map) is a data structure used to implement an associative array, a structure
that can map keys to values. A Hash Table uses a hash function to compute an
index into an array of buckets or slots, from which the desired value can be
found. From Wikipedia
Hash Tables are considered the more
efficient data structure for lookup and for this reason, they are widely used.
Complexity
Average
Access Search Insertion Deletion
- O(1) O(1) O(1)
The code
Note, here I am storing another object for
every hash in my Hash Table.
class HashTable {
constructor( size ) {
this.values = {};
this.numberOfValues = 0;
this.size = size;
}
add( key, value ) {
let hash = this.calculateHash( key );
if ( !this.values.hasOwnProperty( hash ) ) {
this.values[ hash ] = {};
}
if ( !this.values[ hash ].hasOwnProperty( key ) ) {
this.numberOfValues++;
}
this.values[ hash ][ key ] = value;
}
remove( key ) {
let hash = this.calculateHash( key );
if (
this.values.hasOwnProperty( hash )
&&
this.values[ hash ].hasOwnProperty( key )
) {
delete this.values[ hash ][ key ];
this.numberOfValues--;
}
}
calculateHash( key ) {
return key.toString().length % this.size;
}
search( key ) {
let hash = this.calculateHash( key );
if (
this.values.hasOwnProperty( hash )
&&
this.values[ hash ].hasOwnProperty( key )
) {
return this.values[ hash ][ key ];
} else {
return null;
}
}
length() {
return this.numberOfValues;
}
print() {
let string = "";
for ( let value in this.values ) {
for ( let key in this.values[ value ] ) {
string +=
this.values[ value ][ key ] + " ";
}
}
console.log( string.trim() );
}
}
let hashTable = new HashTable( 3 );
hashTable.add( "first", 1 );
hashTable.add( "second", 2 );
hashTable.add( "third", 3 );
hashTable.add( "fourth", 4 );
hashTable.add( "fifth", 5 );
hashTable.print(); // = 2 4 1 3 5
console.log( "length gives 5:", hashTable.length() ); // = 5
console.log( "search second gives 2:", hashTable.search(
"second" ) ); // = 2
hashTable.remove( "fourth" );
hashTable.remove( "first" );
hashTable.print(); // = 2 3 5
console.log( "length gives 3:", hashTable.length() ); // = 3
/*
~ js-files : (master) node hash.js
2 4 1 3 5
length gives 5: 5
search second gives 2: 2
2 3 5
length gives 3: 3
*/
The Set
Sets
Sets are pretty much what it sounds
like.
It's the same intuition as Set in Mathematics. I visualize Sets as Venn
Diagrams.
// 23. Creating a new Set
let newSet = new Set();
// 24. Adding new elements
to a set
newSet.add(1); // Set[1]
newSet.add("text") // Set[1, "text"]
// 25. Check if element is
in set
newSet.has(1); // true
// 24. Check size of set
console.log(newSet.size) // Results: 2
// 26. Delete element from
set
newSet.delete(1) // Set["text"]
// 27. Set Operations:
isSuperSet
function isSuperset(set, subset) {
for (let elem of subset) {
if (!set.has(elem)) {
return false;
}
}
return true;
}
// 28. Set Operations: union
function union(setA, setB) {
let _union = new Set(setA);
for (let elem of setB) {
_union.add(elem);
}
return _union;
}
// 29. Set Operations:
intersection
function intersection(setA, setB) {
let _intersection = new Set();
for (let elem of setB) {
if (setA.has(elem)) {
_intersection.add(elem);
}
}
return _intersection;
}
// 30. Set Operations: symmetricDifference
function symmetricDifference(setA, setB) {
let _difference = new Set(setA);
for (let elem of setB) {
if (_difference.has(elem)) {
_difference.delete(elem);
} else {
_difference.add(elem);
}
}
return _difference;
}
// 31. Set Operations: difference
function difference(setA, setB) {
let _difference = new Set(setA);
for (let elem of setB) {
_difference.delete(elem);
}
return _difference;
}
// Examples
let setA = new Set([1, 2, 3, 4]);
let setB = new Set([2, 3]);
let setC = new Set([3, 4, 5, 6]);
console.log(isSuperset(setA,
setB)); // = true
console.log(union(setA,
setC)); // =
Set [1, 2, 3, 4, 5, 6]
console.log(intersection(setA, setC)); // = Set [3,
4]
console.log(symmetricDifference(setA, setC)); // = Set [1, 2, 5, 6]
console.log(difference(setA, setC)); // =
Set [1, 2]
Definition
A Set is an abstract
data type that can store certain values, without any particular order, and no
repeated values. It is a computer implementation of the mathematical concept of
a finite Set. From Wikipedia
The Set data structure is usually used to
test whether elements belong to set of values. Rather then only containing
elements, Sets are more used to perform operations on multiple values at once
with methods such as union, intersect, etc…
Complexity
Average
Access Search Insertion Deletion
- O(n) O(n) O(n)
The code
function Set() {
this.values = [];
this.numberOfValues = 0;
}
Set.prototype.add = function(value) {
if(!~this.values.indexOf(value)) {
this.values.push(value);
this.numberOfValues++;
}
};
Set.prototype.remove = function(value) {
let index = this.values.indexOf(value);
if(~index) {
this.values.splice(index, 1);
this.numberOfValues--;
}
};
Set.prototype.contains = function(value) {
return this.values.indexOf(value) !== -1;
};
Set.prototype.union = function(set) {
let newSet = new Set();
set.values.forEach(function(value) {
newSet.add(value);
});
this.values.forEach(function(value) {
newSet.add(value);
});
return newSet;
};
Set.prototype.intersect = function(set) {
let newSet = new Set();
this.values.forEach(function(value) {
if(set.contains(value)) {
newSet.add(value);
}
});
return newSet;
};
Set.prototype.difference = function(set) {
let newSet = new Set();
this.values.forEach(function(value) {
if(!set.contains(value)) {
newSet.add(value);
}
});
return newSet;
};
Set.prototype.isSubset = function(set) {
return set.values.every(function(value) {
return this.contains(value);
}, this);
};
Set.prototype.length = function() {
return this.numberOfValues;
};
Set.prototype.print = function() {
console.log(this.values.join(' '));
};
let set = new Set();
set.add(1);
set.add(2);
set.add(3);
set.add(4);
set.print(); // = 1 2 3 4
set.remove(3);
set.print(); // = 1 2 4
console.log('contains 4 is true:', set.contains(4)); // = true
console.log('contains 3 is false:', set.contains(3)); // = false
console.log('---');
let set1 = new Set();
set1.add(1);
set1.add(2);
let set2 = new Set();
set2.add(2);
set2.add(3);
let set3 = set2.union(set1);
set3.print(); // = 1 2 3
let set4 = set2.intersect(set1);
set4.print(); // = 2
let set5 = set.difference(set3); // 1 2 4 diff 1 2 3
set5.print(); // = 4
let set6 = set3.difference(set); // 1 2 3 diff 1 2 4
set6.print(); // = 3
console.log('set1 subset of set is true:', set.isSubset(set1)); // =
true
console.log('set2 subset of set is false:', set.isSubset(set2)); // =
false
console.log('set1 length gives 2:', set1.length()); // = 2
console.log('set3 length gives 3:', set3.length()); // = 3
The Singly Linked List
Definition
A Singly Linked List
is a linear collection of data elements, called nodes pointing to the next node
by means of pointer. It is a data structure consisting of a group of nodes
which together represent a sequence. Under the simplest form, each node is
composed of data and a reference (in other words, a link) to the next node in
the sequence.
Linked Lists are among the simplest and most
common data structures because it allows for efficient insertion or removal of
elements from any position in the sequence.
Complexity
Average
Access Search Insertion Deletion
O(n) O(n) O(1) O(1)
The code
function Node(data) {
this.data = data;
this.next = null;
}
function SinglyLinkedList()
{
this.head = null;
this.tail = null;
this.numberOfValues = 0;
}
SinglyLinkedList.prototype.add
= function(data) {
let node = new Node(data);
if(!this.head) {
this.head = node;
this.tail = node;
} else {
this.tail.next = node;
this.tail = node;
}
this.numberOfValues++;
};
SinglyLinkedList.prototype.remove = function(data) {
let previous = this.head;
let current = this.head;
while(current) {
if(current.data === data) {
if(current === this.head) {
this.head = this.head.next;
}
if(current === this.tail) {
this.tail = previous;
}
previous.next = current.next;
this.numberOfValues--;
} else {
previous = current;
}
current = current.next;
}
};
SinglyLinkedList.prototype.insertAfter = function(data, toNodeData) {
let current = this.head;
while(current) {
if(current.data === toNodeData) {
let node = new Node(data);
if(current === this.tail) {
this.tail.next = node;
this.tail = node;
} else {
node.next = current.next;
current.next = node;
}
this.numberOfValues++;
}
current = current.next;
}
};
SinglyLinkedList.prototype.traverse = function(fn) {
let current = this.head;
while(current) {
if(fn) {
fn(current);
}
current = current.next;
}
};
SinglyLinkedList.prototype.length = function() {
return this.numberOfValues;
};
SinglyLinkedList.prototype.print = function() {
let string = '';
let current = this.head;
while(current) {
string += current.data + ' ';
current = current.next;
}
console.log(string.trim());
};
let singlyLinkedList = new
SinglyLinkedList();
singlyLinkedList.print(); // = ''
singlyLinkedList.add(1);
singlyLinkedList.add(2);
singlyLinkedList.add(3);
singlyLinkedList.add(4);
singlyLinkedList.print(); // = 1 2 3 4
console.log('length is 4:', singlyLinkedList.length()); // = 4
singlyLinkedList.remove(3); // remove value
singlyLinkedList.print(); // = 1 2 4
singlyLinkedList.remove(9); // remove non existing value
singlyLinkedList.print(); // = 1 2 4
singlyLinkedList.remove(1); // remove head
singlyLinkedList.print(); // = 2 4
singlyLinkedList.remove(4); // remove tail
singlyLinkedList.print(); // = 2
console.log('length is 1:', singlyLinkedList.length()); // = 1
singlyLinkedList.add(6);
singlyLinkedList.print(); // = 2 6
singlyLinkedList.insertAfter(3, 2);
singlyLinkedList.print(); // = 2 3 6
singlyLinkedList.insertAfter(4, 3);
singlyLinkedList.print(); // = 2 3 4 6
singlyLinkedList.insertAfter(5, 9); // insertAfter a non existing node
singlyLinkedList.print(); // = 2 3 4 6
singlyLinkedList.insertAfter(5, 4);
singlyLinkedList.insertAfter(7, 6); // insertAfter the tail
singlyLinkedList.print(); // = 2 3 4 5 6 7
singlyLinkedList.add(8); // add node with normal method
singlyLinkedList.print(); // = 2 3 4 5 6 7 8
console.log('length is 7:', singlyLinkedList.length()); // = 7
singlyLinkedList.traverse(function(node) { node.data = node.data + 10; });
singlyLinkedList.print(); // = 12 13 14 15 16 17 18
singlyLinkedList.traverse(function(node) { console.log(node.data); }); // =
12 13 14 15 16 17 18
console.log('length is 7:', singlyLinkedList.length()); // = 7
The Doubly Linked List
Definition
A Doubly Linked List
is a linked data structure that consists of a set of sequentially linked
records called nodes. Each node contains two fields, called links, that are
references to the previous and to the next node in the sequence of nodes. From
Wikipedia
Having two node links allow traversal in
either direction but adding or removing a node in a doubly linked list requires
changing more links than the same operations on a Singly Linked List.
Complexity
Average
Access Search Insertion Deletion
O(n) O(n) O(1) O(1)
The code
class Node {
constructor(data) {
this.data = data;
this.previous = null;
this.next = null;
}
}
class DoublyLinkedList {
constructor() {
this.head = null;
this.tail = null;
this.numberOfValues = 0;
}
add(data) {
let node = new Node(data);
if (!this.head) {
this.head = node;
this.tail = node;
} else {
node.previous = this.tail;
this.tail.next = node;
this.tail = node;
}
this.numberOfValues++;
}
remove(data) {
let current = this.head;
while (current) {
if (current.data === data) {
if (current ===
this.head && current === this.tail) {
this.head = null;
this.tail = null;
} else if (current
=== this.head) {
this.head = this.head.next;
this.head.previous = null;
} else if (current
=== this.tail) {
this.tail = this.tail.previous;
this.tail.next = null;
} else {
current.previous.next = current.next;
current.next.previous = current.previous;
}
this.numberOfValues--;
}
current = current.next;
}
}
insertAfter(data, toNodeData) {
let current = this.head;
while (current) {
if (current.data === toNodeData) {
let node = new
Node(data);
if (current ===
this.tail) {
this.add(data);
} else {
current.next.previous = node;
node.previous = current;
node.next = current.next;
current.next = node;
this.numberOfValues++;
}
}
current = current.next;
}
}
traverse(fn) {
let current = this.head;
while (current) {
if (fn) {
fn(current);
}
current = current.next;
}
}
traverseReverse(fn) {
let current = this.tail;
while (current) {
if (fn) {
fn(current);
}
current = current.previous;
}
}
length() {
return this.numberOfValues;
}
print() {
let string = "";
let current = this.head;
while (current) {
string += current.data + " ";
current = current.next;
}
console.log(string.trim());
}
}
let doublyLinkedList = new
DoublyLinkedList();
doublyLinkedList.print(); // = ''
doublyLinkedList.add(1);
doublyLinkedList.add(2);
doublyLinkedList.add(3);
doublyLinkedList.add(4);
doublyLinkedList.print(); // = 1 2 3 4
console.log("length is 4:", doublyLinkedList.length()); // = 4
doublyLinkedList.remove(3); // remove value
doublyLinkedList.print(); // = 1 2 4
doublyLinkedList.remove(9); // remove non existing value
doublyLinkedList.print(); // = 1 2 4
doublyLinkedList.remove(1); // remove head
doublyLinkedList.print(); // = 2 4
doublyLinkedList.remove(4); // remove tail
doublyLinkedList.print(); // = 2
console.log("length is 1:", doublyLinkedList.length()); // = 1
doublyLinkedList.remove(2); // remove tail, the list should be empty
doublyLinkedList.print(); // = ''
console.log("length is 0:", doublyLinkedList.length()); // = 0
doublyLinkedList.add(2);
doublyLinkedList.add(6);
doublyLinkedList.print(); // = 2 6
doublyLinkedList.insertAfter(3, 2);
doublyLinkedList.print(); // = 2 3 6
doublyLinkedList.traverseReverse(function (node) {
console.log(node.data);
});
doublyLinkedList.insertAfter(4, 3);
doublyLinkedList.print(); // = 2 3 4 6
doublyLinkedList.insertAfter(5, 9); // insertAfter a non existing node
doublyLinkedList.print(); // = 2 3 4 6
doublyLinkedList.insertAfter(5, 4);
doublyLinkedList.insertAfter(7, 6); // insertAfter the tail
doublyLinkedList.print(); // = 2 3 4 5 6 7
doublyLinkedList.add(8); // add node with normal method
doublyLinkedList.print(); // = 2 3 4 5 6 7 8
console.log("length is 7:", doublyLinkedList.length()); // = 7
doublyLinkedList.traverse(function (node) {
node.data = node.data + 10;
});
doublyLinkedList.print(); // = 12 13 14 15 16 17 18
doublyLinkedList.traverse(function (node) {
console.log(node.data);
}); // = 12 13 14 15 16 17 18
console.log("length is 7:", doublyLinkedList.length()); // = 7
doublyLinkedList.traverseReverse(function (node) {
console.log(node.data);
}); // = 18 17 16 15 14 13 12
doublyLinkedList.print(); // = 12 13 14 15 16 17 18
console.log("length is 7:", doublyLinkedList.length()); // = 7
/*
~ js-files : (master) node double-linked-list.js
1 2 3 4
length is 4: 4
1 2 4
1 2 4
2 4
2
length is 1: 1
length is 0: 0
2 6
2 3 6
6
3
2
2 3 4 6
2 3 4 6
2 3 4 5 6 7
2 3 4 5 6 7 8
length is 7: 7
12 13 14 15 16 17 18
12
13
14
15
16
17
18
length is 7: 7
18
17
16
15
14
13
12
12 13 14 15 16 17 18
length is 7: 7
~ js-files : (master)
*/
The Stack
Definition
A Stack is an
abstract data type that serves as a collection of elements, with two principal
operations: push, which adds an element to the collection, and pop, which
removes the most recently added element that was not yet removed. The order in
which elements come off a Stack gives rise to its alternative name, LIFO (for
last in, first out). From Wikipedia
A Stack often has a third method peek which
allows to check the last pushed element without popping it.
Complexity
Average
Access Search Insertion Deletion
O(n) O(n) O(1) O(1)
The code
function Stack() {
this.stack = [];
}
Stack.prototype.push =
function(value) {
this.stack.push(value);
};
Stack.prototype.pop = function() {
return this.stack.pop();
};
Stack.prototype.peek = function() {
return this.stack[this.stack.length - 1];
};
Stack.prototype.length = function() {
return this.stack.length;
};
Stack.prototype.print = function() {
console.log(this.stack.join(' '));
};
let stack = new Stack();
stack.push(1);
stack.push(2);
stack.push(3);
stack.print(); // = 1 2 3
console.log('length is 3:', stack.length()); // = 3
console.log('peek is 3:', stack.peek()); // = 3
console.log('pop is 3:', stack.pop()); // = 3
stack.print(); // = 1 2
console.log('pop is 2:', stack.pop()); // = 2
console.log('length is 1:', stack.length()); // = 1
console.log('pop is 1:', stack.pop()); // = 1
stack.print(); // = ''
console.log('peek is undefined:', stack.peek()); // = undefined
console.log('pop is undefined:', stack.pop()); // = undefined
The Queue
Definition
A Queue is a particular
kind of abstract data type or collection in which the entities in the
collection are kept in order and the principal operations are the addition of
entities to the rear terminal position, known as enqueue, and removal of
entities from the front terminal position, known as dequeue. This makes the
Queue a First-In-First-Out (FIFO) data structure. In a FIFO data structure, the
first element added to the Queue will be the first one to be removed.
As for the Stack data structure, a peek
operation is often added to the Queue data structure. It returns the value of
the front element without dequeuing it.
Complexity
Average
Access Search Insertion Deletion
O(n) O(n) O(1) O(n)
The code
function Queue() {
this.queue = [];
}
Queue.prototype.enqueue =
function(value) {
this.queue.push(value);
};
Queue.prototype.dequeue = function() {
return this.queue.shift();
};
Queue.prototype.peek = function() {
return this.queue[0];
};
Queue.prototype.length = function() {
return this.queue.length;
};
Queue.prototype.print = function() {
console.log(this.queue.join(' '));
};
let queue = new Queue();
queue.enqueue(1);
queue.enqueue(2);
queue.enqueue(3);
queue.print(); // = 1 2 3
console.log('length is 3:', queue.length()); // = 3
console.log('peek is 1:', queue.peek()); // = 3
console.log('dequeue is 1:', queue.dequeue()); // = 1
queue.print(); // = 2 3
console.log('dequeue is 2:', queue.dequeue()); // = 2
console.log('length is 1:', queue.length()); // = 1
console.log('dequeue is 3:', queue.dequeue()); // = 3
queue.print(); // = ''
console.log('peek is undefined:', queue.peek()); // = undefined
console.log('dequeue is undefined:', queue.dequeue()); // = undefined
The Tree
Definition
A Tree is a widely
used data structure that simulates a hierarchical tree structure, with a root
value and subtrees of children with a parent node. A tree data structure can be
defined recursively as a collection of nodes (starting at a root node), where
each node is a data structure consisting of a value, together with a list of
references to nodes (the "children"), with the constraints that no reference is
duplicated, and none points to the root node. From Wikipedia
Complexity
Average
Access Search Insertion Deletion
O(n) O(n) O(n) O(n)
To get a full overview of the time and space complexity of the Tree data
structure, have a look to this excellent Big O cheat sheet.
The code
function Node(data) {
this.data = data;
this.children = [];
}
function Tree() {
this.root = null;
}
Tree.prototype.add =
function(data, toNodeData) {
let node = new Node(data);
let parent = toNodeData ? this.findBFS(toNodeData) : null;
if(parent) {
parent.children.push(node);
} else {
if(!this.root) {
this.root = node;
} else {
return 'Root node is already assigned';
}
}
};
Tree.prototype.remove = function(data) {
if(this.root.data === data) {
this.root = null;
}
let queue = [this.root];
while(queue.length) {
let node = queue.shift();
for(let i = 0; i < node.children.length; i++) {
if(node.children[i].data === data) {
node.children.splice(i, 1);
} else {
queue.push(node.children[i]);
}
}
}
};
Tree.prototype.contains = function(data) {
return this.findBFS(data) ? true : false;
};
Tree.prototype.findBFS = function(data) {
let queue = [this.root];
while(queue.length) {
let node = queue.shift();
if(node.data === data) {
return node;
}
for(let i = 0; i < node.children.length; i++) {
queue.push(node.children[i]);
}
}
return null;
};
Tree.prototype._preOrder = function(node, fn) {
if(node) {
if(fn) {
fn(node);
}
for(let i = 0; i < node.children.length; i++) {
this._preOrder(node.children[i], fn);
}
}
};
Tree.prototype._postOrder = function(node, fn) {
if(node) {
for(let i = 0; i < node.children.length; i++) {
this._postOrder(node.children[i], fn);
}
if(fn) {
fn(node);
}
}
};
Tree.prototype.traverseDFS = function(fn, method) {
let current = this.root;
if(method) {
this['_' + method](current, fn);
} else {
this._preOrder(current, fn);
}
};
Tree.prototype.traverseBFS = function(fn) {
let queue = [this.root];
while(queue.length) {
let node = queue.shift();
if(fn) {
fn(node);
}
for(let i = 0; i < node.children.length; i++) {
queue.push(node.children[i]);
}
}
};
Tree.prototype.print = function() {
if(!this.root) {
return console.log('No root node found');
}
let newline = new Node('|');
let queue = [this.root, newline];
let string = '';
while(queue.length) {
let node = queue.shift();
string += node.data.toString() + ' ';
if(node === newline && queue.length) {
queue.push(newline);
}
for(let i = 0; i < node.children.length; i++) {
queue.push(node.children[i]);
}
}
console.log(string.slice(0, -2).trim());
};
Tree.prototype.printByLevel = function() {
if(!this.root) {
return console.log('No root node found');
}
let newline = new Node('\n');
let queue = [this.root, newline];
let string = '';
while(queue.length) {
let node = queue.shift();
string += node.data.toString() + (node.data !== '\n' ? ' ' : '');
if(node === newline && queue.length) {
queue.push(newline);
}
for(let i = 0; i < node.children.length; i++) {
queue.push(node.children[i]);
}
}
console.log(string.trim());
};
let tree = new Tree();
tree.add('ceo');
tree.add('cto', 'ceo');
tree.add('dev1', 'cto');
tree.add('dev2', 'cto');
tree.add('dev3', 'cto');
tree.add('cfo', 'ceo');
tree.add('accountant', 'cfo');
tree.add('cmo', 'ceo');
tree.print(); // = ceo | cto cfo cmo | dev1 dev2 dev3 accountant
tree.printByLevel(); // = ceo \n cto cfo cmo \n dev1 dev2 dev3 accountant
console.log('tree contains dev1 is true:', tree.contains('dev1')); // =
true
console.log('tree contains dev4 is false:', tree.contains('dev4')); // =
false
console.log('--- BFS');
tree.traverseBFS(function(node) { console.log(node.data); }); // = ceo cto
cfo cmo dev1 dev2 dev3 accountant
console.log('--- DFS preOrder');
tree.traverseDFS(function(node) { console.log(node.data); }, 'preOrder'); //
= ceo cto dev1 dev2 dev3 cfo accountant cmo
console.log('--- DFS postOrder');
tree.traverseDFS(function(node) { console.log(node.data); }, 'postOrder'); //
= dev1 dev2 dev3 cto accountant cfo cmo ceo
tree.remove('cmo');
tree.print(); // = ceo | cto cfo | dev1 dev2 dev3 accountant
tree.remove('cfo');
tree.print(); // = ceo | cto | dev1 dev2 dev3
The Graph
Definition
A Graph data structure
consists of a finite (and possibly mutable) set of vertices or nodes or points,
together with a set of unordered pairs of these vertices for an undirected
Graph or a set of ordered pairs for a directed Graph. These pairs are known as
edges, arcs, or lines for an undirected Graph and as arrows, directed edges,
directed arcs, or directed lines for a directed Graph. The vertices may be part
of the Graph structure, or may be external entities represented by integer
indices or references. From Wikipedia
A Graph data structure may also associate to
each edge some edge value, such as a symbolic label or a numeric attribute
(cost, capacity, length, etc.).
Representation
There are different ways of representing a graph, each of them with its own
advantages and disadvantages. Here are the main 2:
Adjacency list: For every vertex a list of
adjacent vertices is stored. This can be viewed as storing the list of edges.
This data structure allows the storage of additional data on the vertices and
edges.
Adjacency matrix: Data are stored in a two-dimensional matrix, in which the
rows represent source vertices and columns represent destination vertices. The
data on the edges and vertices must be stored externally.
Complexity
Adjacency list
Storage Add Vertex Add Edge Query
O( V + E
Adjacency matrix
Storage Add Vertex Add Edge Query
O( V ^2) O(
Graph
The code
//below uses the adjacency
list representation.
function Graph() {
this.vertices = [];
this.edges = [];
this.numberOfEdges = 0;
}
Graph.prototype.addVertex = function(vertex) {
this.vertices.push(vertex);
this.edges[vertex] = [];
};
Graph.prototype.removeVertex = function(vertex) {
let index = this.vertices.indexOf(vertex);
if(~index) {
this.vertices.splice(index, 1);
}
while(this.edges[vertex].length) {
let adjacentVertex = this.edges[vertex].pop();
this.removeEdge(adjacentVertex, vertex);
}
};
Graph.prototype.addEdge = function(vertex1, vertex2) {
this.edges[vertex1].push(vertex2);
this.edges[vertex2].push(vertex1);
this.numberOfEdges++;
};
Graph.prototype.removeEdge = function(vertex1, vertex2) {
let index1 = this.edges[vertex1] ? this.edges[vertex1].indexOf(vertex2) :
-1;
let index2 = this.edges[vertex2] ? this.edges[vertex2].indexOf(vertex1) :
-1;
if(~index1) {
this.edges[vertex1].splice(index1, 1);
this.numberOfEdges--;
}
if(~index2) {
this.edges[vertex2].splice(index2, 1);
}
};
Graph.prototype.size = function() {
return this.vertices.length;
};
Graph.prototype.relations = function() {
return this.numberOfEdges;
};
Graph.prototype.traverseDFS = function(vertex, fn) {
if(!~this.vertices.indexOf(vertex)) {
return console.log('Vertex not found');
}
let visited = [];
this._traverseDFS(vertex, visited, fn);
};
Graph.prototype._traverseDFS = function(vertex, visited, fn) {
visited[vertex] = true;
if(this.edges[vertex] !== undefined) {
fn(vertex);
}
for(let i = 0; i < this.edges[vertex].length; i++) {
if(!visited[this.edges[vertex][i]]) {
this._traverseDFS(this.edges[vertex][i], visited,
fn);
}
}
};
Graph.prototype.traverseBFS = function(vertex, fn) {
if(!~this.vertices.indexOf(vertex)) {
return console.log('Vertex not found');
}
let queue = [];
queue.push(vertex);
let visited = [];
visited[vertex] = true;
while(queue.length) {
vertex = queue.shift();
fn(vertex);
for(let i = 0; i < this.edges[vertex].length; i++) {
if(!visited[this.edges[vertex][i]]) {
visited[this.edges[vertex][i]] = true;
queue.push(this.edges[vertex][i]);
}
}
}
};
Graph.prototype.pathFromTo = function(vertexSource, vertexDestination) {
if(!~this.vertices.indexOf(vertexSource)) {
return console.log('Vertex not found');
}
let queue = [];
queue.push(vertexSource);
let visited = [];
visited[vertexSource] = true;
let paths = [];
while(queue.length) {
let vertex = queue.shift();
for(let i = 0; i < this.edges[vertex].length; i++) {
if(!visited[this.edges[vertex][i]]) {
visited[this.edges[vertex][i]] = true;
queue.push(this.edges[vertex][i]);
// save paths between vertices
paths[this.edges[vertex][i]] = vertex;
}
}
}
if(!visited[vertexDestination]) {
return undefined;
}
let path = [];
for(let j = vertexDestination; j != vertexSource; j = paths[j]) {
path.push(j);
}
path.push(j);
return path.reverse().join('-');
};
Graph.prototype.print = function() {
console.log(this.vertices.map(function(vertex) {
return (vertex + ' - ' + this.edges[vertex].join(',
')).trim();
}, this).join(' | '));
};
```
let graph = new Graph();
graph.addVertex(1);
graph.addVertex(2);
graph.addVertex(3);
graph.addVertex(4);
graph.addVertex(5);
graph.addVertex(6);
graph.print(); // 1 - | 2 - | 3 - | 4 - | 5 - | 6 -
graph.addEdge(1, 2);
graph.addEdge(1, 5);
graph.addEdge(2, 3);
graph.addEdge(2, 5);
graph.addEdge(3, 4);
graph.addEdge(4, 5);
graph.addEdge(4, 6);
graph.print(); // 1 - 2, 5 | 2 - 1, 3, 5 | 3 - 2, 4 | 4 -
3, 5, 6 | 5 - 1, 2, 4 | 6 - 4
console.log('graph size (number of vertices):', graph.size()); // = 6
console.log('graph relations (number of edges):', graph.relations()); //
= 7
graph.traverseDFS(1, function(vertex) { console.log(vertex); }); // = 1
2 3 4 5 6
console.log('---');
graph.traverseBFS(1, function(vertex) { console.log(vertex); }); // = 1
2 5 3 4 6
graph.traverseDFS(0, function(vertex) { console.log(vertex); }); // =
'Vertex not found'
graph.traverseBFS(0, function(vertex) { console.log(vertex); }); // =
'Vertex not found'
console.log('path from 6 to 1:', graph.pathFromTo(6, 1)); // = 6-4-5-1
console.log('path from 3 to 5:', graph.pathFromTo(3, 5)); // = 3-2-5
graph.removeEdge(1, 2);
graph.removeEdge(4, 5);
graph.removeEdge(10, 11);
console.log('graph relations (number of edges):', graph.relations()); //
= 5
console.log('path from 6 to 1:', graph.pathFromTo(6, 1)); // =
6-4-3-2-5-1
graph.addEdge(1, 2);
graph.addEdge(4, 5);
console.log('graph relations (number of edges):', graph.relations()); //
= 7
console.log('path from 6 to 1:', graph.pathFromTo(6, 1)); // = 6-4-5-1
graph.removeVertex(5);
console.log('graph size (number of vertices):', graph.size()); // = 5
console.log('graph relations (number of edges):', graph.relations()); //
= 4
console.log('path from 6 to 1:', graph.pathFromTo(6, 1)); // =
6-4-3-2-1
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