Stacks, queues, deques, and lists are statistics collections with items ordered in line with how they are added or removed. Once an item is added, it stays inside the equal function relative to its buddies. Because of this function, we name these collections linear data systems.

Linear structures may be the concept of as having ended, stated variously as “left” and “right”, “pinnacle” and “bottom”, or “front” and “rear”. What distinguishes one linear structure from any other is where additions and removals may additionally arise. As an example, a shape may only allow new objects to be added at one end and eliminated at some other; every other may also permit the addition or elimination from either cease.

Those variations give an upward push to some of the maximum beneficial records systems in pc technology. They appear in many algorithms and can be used to remedy a diffusion of essential troubles.

Data structure where data elements are arranged sequentially or linearly is called a linear data structure. In a linear data structure, we can traverse all the data items in a single pass. Until now, all the data structures you have learned are linear only, whether it is Array, ArrayList, or String. Stack is also a linear data structure.

FILO (First In Last Out) or LIFO (Last In First Out) order:-

Let us try to get the meaning of FILO or LIFO using an example. Consider a pile of 3 books on a table.

If you want to take out the top blue book, then you need not do anything to the pile. Just pick it from the top.

But if you want to take out the bottom pink book, then first you need to remove the books on top (blue and yellow), and then only you can get access to the third (bottom-most) book.

Also, if you want to add a book, let's say, green in color, then you can add it above the blue book only. Otherwise, you will have to disturb the remaining 3 books' ordering.

An abstract data type, sometimes abbreviated ADT, is a logical description of how we view the data and the allowed operations without regard to how they’ll be implemented. This means that we’re only concerned with what the data represents and not with how it’ll be constructed. This level of abstraction encapsulates the data and hides implementation details from the user's view, a technique called information hiding.

A data structure is an implementation of an abstract data type and requires a physical view of the data using some collection of primitive data types and other programming constructs.

The separation of these two perspectives allows us to define complex data models for our problems without giving any details about how the model will actually be built. This provides an implementation-independent view of the data. Since there are usually many ways to implement an abstract data type, this independence allows the programmer to change implementation details without changing how the user interacts with it. Instead, the user can remain focused on the process of problem-solving.

The stack abstract data type is an ordered collection of items where items are added to and removed from the top. The interface for a stack is:

push(item) adds the given item to the top of the stack and returns nothing

pop() removes and returns the top item from the stack

peek() returns the top item from the stack but doesn’t remove it (the stack isn’t modified)

is_empty() returns a boolean representing whether the stack is empty

size() returns the number of items on the stack as an integer

For example, if s is a newly-created, empty stack, then the table below shows the results of a sequence of stack operations. The top item is the one farthest to the right in “Stack contents”.

Stack operations may involve initializing the stack, using it and then de-initializing it. Apart from these basic stuffs, a stack is used for the following two primary operations −

push() − Pushing (storing) an element on the stack.

pop() − Removing (accessing) an element from the stack.

To use a stack efficiently, we need to check the status of stack as well. For the same purpose, the following functionality is added to stacks −

peek() − get the top data element of the stack, without removing it.

At all times, we maintain a pointer to the last PUSHed data on the stack. As this pointer always represents the top of the stack, hence named top. The top pointer provides top value of the stack without actually removing it.

First we should learn about procedures to support stack functions −

Implementation of peek() function in C programming language −

Implementation of isfull() function in C programming language −

Introducing of Stacks

Following are some of the common scenarios in which Stacks can be Used.

To check if delimiters (parenthesis, brackets, etc.) are balanced in a computer program

Following Java program implements the stack functionality. It internally uses an array for the implementation.

Stacks follows the LIFO method and addition and retrieval of a data item take only Ο(n) time. Stacks are used where we need to access data in the reverse order of their arrival. Stacks are used commonly in recursive function calls, expression parsing, depth-first traversal of graphs, etc.

 -To check if delimiters (parenthesis, brackets, etc.) are balanced in a computer program

- To traverse the nodes of a binary tree.

In the circular queue, memory is utilized. If we delete any element that position is used later.

A circular queue consumes less memory than a linear queue because in the queue while doing insertion after deletion operation it allocates an extra space the first remaining vacant but in the circular queue, the first is used as it comes immediately after the last.

In CQ the memory of the deleted process can be used by some other new process.

A standard queue suffers from a rebuffering problem during deque operations. Making the queue circular and linking the head to the tail, alleviates the problem and allows insertion and deletion in constant time.

Queue backed by a singly-linked list. Enqueuing into the linked list can be implemented by appending to the back of the singly-linked list, which takes worst-case time O(1). Dequeuing can be implemented by removing the first element, which also takes worst-case time O(1). This also requires a new allocation per en queue, which may be slow.

Queue backed by a growing circular buffer. Enqueuing into the circular buffer works by inserting something at the next free position in the circular buffer. This works by growing the array if necessary, then inserting the new element. Using a similar analysis for the dynamic array, this takes best-case time O(1), worst-case time O(n), and amortized time O(1). Dequeuing from the buffer works by removing the first element of the circular buffer, which takes time O(1) in the worst case.

To summarise, all of the structures support pushing and popping n elements in O(n) time. The linked list versions have better worst-case behavior but may have a worse overall runtime because of the number of allocations performed. The array versions are slower in the worst-case but have better overall performance if the time per operation isn't too important.

Because they help manage your data in more a particular way than arrays and lists. It means that when you're debugging a problem, you won't have to wonder if someone randomly inserted an element into the middle of your list, messing up some invariants.

Arrays and lists are random access. They are very flexible and also easily corruptible. If you want to manage your data as FIFO or LIFO it's best to use those, already implemented, collections.

Use a queue when you want to get things out in the order that you put them in (FIFO)

Use a stack when you want to get things out in the reverse order than you put them in (LIFO)

Use a list when you want to get anything out, regardless of when you put them in (and when you don't want them to automatically be removed).

Queues offer random access to their contents by shifting the first element off the front of the queue. You have to do this repeatedly to access an arbitrary element somewhere in the queue. Therefore, access is O(n).

Searching for a given value in the queue requires iterating until you find it. So the search is O(n).

Inserting into a queue, by definition, can only happen at the back of the queue, similar to someone getting in line for a delicious Double-Double burger at In 'n Out. Assuming an efficient queue implementation, queue insertion is O(1).

Deleting from a queue happens at the front of the queue. Assuming an efficient queue implementation, queue deletion is `

A stack is a recursive data structure, so it's:

it consists of a top and the rest which is a stack by itself;

A Stack is a container of objects that are inserted and removed according to the last-in-first-out (LIFO) principle. In the pushdown stacks only two operations are allowed: push the item into the stack, and pop the item out of the stack.

There are three operations that can be performed on stacks. They are:

displaying the contents of the stack (peek or top).

A stack is a limited access data structure - elements can be added and removed from the stack only at the top. push adds an item to the top of the stack, pop removes the item from the top. A helpful analogy is to think of a stack of books; you can remove only the top book, also you can add a new book on the top.

A standard queue suffers from a rebuffering problem during deque operations. By making the queue circular and linking the head to the tail, alleviates the problem and allows insertion and deletion in constant time.

A stack is a data structure based on the principle Last In First Out. Stack is the container to hold nodes and has two operations - push and pop. Push operation is to add nodes into the stack and pop operation is to delete nodes from the stack and returns the topmost node.

A queue is a data structure based on the principle First in First Out. The nodes are kept in order. A node is inserted from the rear of the queue and a node is deleted from the front. The first element inserted in the first element is first to delete.

A queue can be implemented by using 2 stacks:-

1. An element is inserted in the queue by pushing it into stack 1

2. An element is extracted from the queue by popping it from stack 2

3. If stack 2 is empty then all elements currently in stack 1 are transferred to stack 2 but in the reverse order

4. If stack 2 is not empty just pop the value from stack 2.

Stack is a data structure that follows Last in First out strategy.

Push – Pushes (inserts) the element in the stack. The location is specified by the pointer.

Pop – Pulls (removes) the element out of the stack. The location is specified by the pointer

Swap: - the two top most elements of the stack can be swapped

Peek: - Returns the top element on the stack but does not remove it from the stack

Rotate:- the topmost (n) items can be moved on the stack in a rotating fashion

A stack has a fixed location in the memory. When a data element is pushed in the stack, the pointer points to the current element

The push() and pop() methods implemented in stacks take constant time to execute. i.e. the time to execute is very quick and is not dependent on the number of items on the stack. In Big O notation this is represented as O(1).

You can simulate a linked list by using two stacks. One stack is the "list," and the other is used for temporary storage.

To add an item at the head, simply push the item onto the stack.

To remove from the head, pop from the stack.

To insert into the middle somewhere, pop items from the "list" stack and push them onto the temporary stack until you get to your insertion point. Push the new item onto the "list" stack, then pop from the temporary stack and push back onto the "list" stack. Deletion of an arbitrary node is similar.

They’re very useful because they afford you constant time O(1) operations when inserting or removing from the front of a data structure. One common use of a stack is in compilers, where a stack can be used to make sure that the brackets and parentheses in a code file are all balanced, i.e., have an opening and closing counterpart. Stacks are also very useful in evaluating mathematical expressions.

Stacks usually provide the following key interfaces.

push() - Inserts a new data item on the top of the stack.

pop() - Removes the item from the top of the stack.

peek() - Returns the item from the top of the stack without removing it.

isFull() - Returns true if the stack is full.

isEmpty() - Returns true if the stack is empty.

Stacks are programmatic data structures that allow access to only one item at a time, the last item inserted. Stacks internally use other data structures such as arrays for their implementation. A stack is a Last-In-First-Out (LIFO) storage mechanism because the last item inserted is the first to be removed.

Stack is a linear data structure which follows a particular order in which the operations are performed. The order may be LIFO(Last In First Out) or FILO(First In Last Out).

Stacks

I've been told by others that writing using namespace std; in code is wrong, and that I should use std::cout and std::cin directly instead.

Why is using namespace std; considered a bad practice? Is it inefficient or does it risk declaring ambiguous variables (variables that share the same name as a function in std namespace)? Does it impact performance?

Why is "using namespace std;" considered bad practice?

I have an account on some Stack Exchange sites. I would like to remove one or more of my accounts. What is the process to delete my account(s)? 

How can I delete a Stack Exchange account of mine?

While using new_list = my_list, any modifications to new_list changes my_list every time. Why is this, and how can I clone or copy the list to prevent it? 

List changes unexpectedly after assignment. Why is this and how can I prevent it?

can we able to establish the connection between aws account and other services out side the aws? the scenario is like: I want to use my stack template from other application for eg some website A which run the script and create VPC in AWS. for that I need a connection between these two.

How to establish connection between AWS account to outside services or application (which are not on AWS)

given a stack (NOT AN ARRAY) with N elements, what is the most efficient algorithm to shuffle the stack randomly? i.e. given a stack of N songs like in Spotify, what is the best way to shuffle them? 

What is the most optimized algorithm to randomly shuffle a stack?

Array and stack both are Linear data structures then Why stack is implemented using another data structures but array is not? 

Why stack is implemented using another data structures but array is not?

Are Stacks and Queue considered LinkedList?

The time complexity of indexing a LinkedList is 0(n). So am I right to assume that's the same for stacks and queues.

I have started learning Data Structures recently and just had my own linked list implementation.

Now I stumbled upon two new data structures: stack and queue.

stack is a linked list that allows insertion/removal only from its tail, and

the queue is a linked list that allows insertion only at its tail and removal only from its head.

Are Stacks and Queue's considered LinkedList?

I am trying to create a 2D stack (which i called s), but such that the number of columns in each row of s isn't the same, it changes in every rows. I just learned what stacks in C++ are (so a beginner) so any simple (or medium) level explanations are welcome. 

Variable length in a 2D stack

I'm working on an old file I found on a Linux server and this file contains the Arabic words in the following strange format.

\350\343\240\317\344\307\345\331\307\...


I don't if the Linux convert the Arabic chars automatically or someone did that himself but I need to understand the Arabic written in that way.

So, does anyone knows what is the above format/encoding?

Decode Arabic chars from a linux encoding

I'm just starting to learn LINQ, I'm wondering if it would be possible to group the elements in 3 different stacks using LINQ. this is what I have, could it be possible to add more than one array in the from clause, and how? 

Is it possible to Merge stacks with LINQ

What is the best way to implement a Stack and a Queue in JavaScript?

I'm looking to do the shunting-yard algorithm and I'm going to need these data-structure

Let's learn something about two important data structure stack and queue:

1>Stack :- Stack is a sequential and ordered data structure and it is LIFO (Last In First Out) based data structure.

1>PUSH : Push operation is responsible for inserting data into a stack data structure.

2>POP: Pop operation is  for removing the data from a stack.

class Stack {
 constructor() {
   this.stack = [];
 }
 push(item) {
   this.stack.push(item);
 }
 pop() {
   this.stack.pop();
 }
}

1>Queue:- Queue is a sequential and ordered data structure and it is FIFO (First In First Out) based data structure.

enqueue—This operation is responsible for inserting or pushing a new element to the queue.

dequeue—This operation is responsible for removing the oldest element from the queue.

How do you implement a Stack and a Queue in JavaScript?

How would you explain JavaScript closures to someone with a knowledge of the concepts they consist of (for example functions, variables and the like), but does not understand closures themselves?

I have seen the Scheme example given on Wikipedia, but unfortunately it did not help

How do JavaScript closures work?

 What is the easiest way to convert the result of Throwable.getStackTrace() to a string that depicts the stacktrace? 

How can I convert a stack trace to a string?

I want to delete a branch both locally and remotely.

Failed Attempts to Delete a Remote Branch

$ git branch -d remotes/origin/bugfix
error: branch 'remotes/origin/bugfix' not found.

$ git branch -d origin/bugfix
error: branch 'origin/bugfix' not found.

$ git branch -rd origin/bugfix
Deleted remote branch origin/bugfix (was 2a14ef7).

$ git push
Everything up-to-date

$ git pull
From github.com:gituser/gitproject

* [new branch] bugfix -> origin/bugfix
Already up-to-date.


What should I do differently to successfully delete the remotes/origin/bugfix branch both locally and remotely?

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