Static Data Structure vs Dynamic Data Structure - GeeksforGeeks (2024)

Static and Dynamic Data Structures

Data structures are the fundamental building blocks of computer programming. They determine how data is organized, stored, and manipulated within a software application. There are two main categories of data structures: static and dynamic. Static data structures have a fixed size and are allocated in memory during compile-time, while dynamic data s

Difference between Static Arrays and Dynamic Arrays

In the Data structure, we know that an array plays a vital role in having similar types of elements arranged in a contiguous manner with the same data type. According to the concept of array, an array can be defined in two ways as per the memory allocation concept. Types of Arrays:There are basically two types of arrays: Static Array: In this type

Difference between Static and Dynamic Memory Allocation in C

Memory Allocation: Memory allocation is a process by which computer programs and services are assigned with physical or virtual memory space. The memory allocation is done either before or at the time of program execution. There are two types of memory allocations: Compile-time or Static Memory AllocationRun-time or Dynamic Memory AllocationStatic

Implement Dynamic Multi Stack (K stacks) using only one Data Structure

In this article, we will see how to create a data structure that can handle multiple stacks with growable size. The data structure needs to handle three operations: push(x, stackNum) = pushes value x to the stack numbered stackNumpop(stackNum) = pop the top element from the stack numbered stackNumtop(stackNum) = shows the topmost element of the sta

Dynamic Disjoint Set Data Structure for large range values

Prerequisites: Disjoint Set Data StructureSetUnordered_MapDisjoint Set data structure is used to keep track of a set of elements partitioned into a number of disjoint (non-overlapping) subsets. In this article, we will learn about constructing the same Data Structure dynamically. This data structure basically helps in situations where we cannot sim

Count the number of objects using Static member function

Prerequisite : Static variables , Static Functions Write a program to design a class having static member function named showcount() which has the property of displaying the number of objects created of the class. Explanation: In this program we are simply explaining the approach of static member function. We can define class members and member fun

What will happen if i declare main() in java as non-static?

main() method in Java acts as an application's entry point. So declaration must read "public static void main(String[] args)" to work properly . What happens if you declare main to be non-static is as follows? Java Code import java.util.Scanner; public class Sample{ public void main(String[] args){ System.out.println("This is a sample code

CSES Solutions – Static Range Sum Queries

Given an array arr[] of N integers, your task is to process Q queries of the form: what is the sum of values in range [a,b]? Examples Input: arr[] = {1, 3, 4, 8, 6, 1, 4, 2}, Queries: {{2, 5}, {1, 3}}Output: 21 8Explanation: Query 1: Sum of elements from index 2 to 5 = 3 + 4 + 8 + 6 = 21Query 2: Sum of elements from index 1 to 3 = 1 + 3 + 4 = 8Inpu

Difference between a Static Queue and a Singly Linked List

Static Queue: A queue is an ordered list of elements. It always works in first in first out(FIFO) fashion. All the elements get inserted at the REAR and removed from the FRONT of the queue. In implementation of the static Queue, an array will be used so all operation of queue are index based which makes it faster for all operations except deletion

Is array a Data Type or Data Structure?

What is Data Type? In computer programming, a data type is a classification of data that determines the type of values that can be stored, manipulated, and processed. It tells the computer what kind of data a particular variable or constant can hold, and what operations can be performed on that data. Common data types include integers, floating-poi

Data Structure Alignment : How data is arranged and accessed in Computer Memory?

Data structure alignment is the way data is arranged and accessed in computer memory. Data alignment and Data structure padding are two different issues but are related to each other and together known as Data Structure alignment.Data alignment: Data alignment means putting the data in memory at an address equal to some multiple of the word size.

Difference between data type and data structure

Data Type A data type is the most basic and the most common classification of data. It is this through which the compiler gets to know the form or the type of information that will be used throughout the code. So basically data type is a type of information transmitted between the programmer and the compiler where the programmer informs the compile

Monkey Patching in Python (Dynamic Behavior)

In Python, the term monkey patch refers to dynamic (or run-time) modifications of a class or module. In Python, we can actually change the behavior of code at run-time. # monk.py class A: def func(self): print ("func() is being called") We use above module (monk) in below code and change behavior of func() at run-time by assigning differe

Introduction to Dynamic Programming on Trees

Dynamic Programming(DP) is a technique to solve problems by breaking them down into overlapping sub-problems which follows the optimal substructure. There are various problems using DP like subset sum, knapsack, coin change etc. DP can also be applied on trees to solve some specific problems.Pre-requisite: DFSGiven a tree with N nodes and N-1 edges

Print equal sum sets of Array (Partition Problem) using Dynamic Programming

Given an array arr[]. Determine whether it is possible to split the array into two sets such that the sum of elements in both sets is equal. If it is possible, then print both sets. If it is not possible then output -1. Examples : Input : arr = {5, 5, 1, 11} Output : Set 1 = {5, 5, 1}, Set 2 = {11} Sum of both the sets is 11 and equal. Input : arr

Implementation of Dynamic Array in Python

What is a dynamic array? A dynamic array is similar to an array, but with the difference that its size can be dynamically modified at runtime. Don't need to specify how much large an array beforehand. The elements of an array occupy a contiguous block of memory, and once created, its size cannot be changed. A dynamic array can, once the array is fi

Sorting a dynamic 2-dimensional array of Strings

Prerequisite: How to dynamically allocate a 2D array in C? Double pointer: A pointer pointing to another pointer is known as a Double pointer. To represent the double pointer ' ** ' is used. Double pointer is also called as pointer to pointer. Example: Input: Geeks, Gfg, Placement, Sudo, Gate Output: Gate, Geeks, Gfg, Placement, Sudo The idea is to

Dynamic Programming vs Divide-and-Conquer

In this article I’m trying to explain the difference/similarities between dynamic programming and divide and conquer approaches based on two examples: binary search and minimum edit distance (Levenshtein distance).The ProblemWhen I started to learn algorithms it was hard for me to understand the main idea of dynamic programming (DP) and how it is d

How do Dynamic arrays work?

A Dynamic array (vector in C++, ArrayList in Java) automatically grows when we try to make an insertion and there is no more space left for the new item. Usually the area doubles in size. A simple dynamic array can be constructed by allocating an array of fixed-size, typically larger than the number of elements immediately required. The elements of

Maximum sum of nodes in Binary tree such that no two are adjacent | Dynamic Programming

Given a N-ary tree with a value associated with each node, the task is to choose a subset of these nodes such that sum of chosen nodes is maximum under a constraint that no two chosen node in subset should be directly connected that is, if we have taken a node in our sum then we can’t take its any children in consideration and vice versa.Examples:

Distinct palindromic sub-strings of the given string using Dynamic Programming

Given a string str of lowercase alphabets, the task is to find all distinct palindromic sub-strings of the given string. Examples: Input: str = "abaaa" Output: 5 Palindromic sub-strings are "a", "aa", "aaa", "aba" and "b" Input: str = "abcd" Output: 4 Approach: The solution to this problem has been discussed here using Manacher’s algorithm. However

Implement dynamic deque using templates class and a circular array

The task is to implement a dynamic Deque using templates class and a circular array, having the following functionalities: front(): Get the front item from the deque.back(): Get the last item from the deque.push_back(X): Push X at the end of the deque.push_front(X): Push X at the start of the deque.pop_front(): Delete an element from the start of t

Longest path in a directed Acyclic graph | Dynamic Programming

Given a directed graph G with N vertices and M edges. The task is to find the length of the longest directed path in Graph.Note: Length of a directed path is the number of edges in it. Examples: Input: N = 4, M = 5 Output: 3 The directed path 1->3->2->4 Input: N = 5, M = 8 Output: 3 Simple Approach: A naive approach is to calculate the len

Count of numbers from range [L, R] whose sum of digits is Y using Dynamic Programming

Pre-requisites: Recursion, Dynamic Programming, Digit DP Given an integer Y and a range [L, R], the task is to find the count of all numbers from the given range whose sum of digits is equal to Y.Examples: Input: L = 0, R = 11, Y = 2 Output: 2 2 -> 2 11 -> 1 + 1 = 2Input: L = 500, R = 1000, Y = 6 Output: 3 Constraints: 0 <= L <= R <=

Minimum time required to rot all oranges | Dynamic Programming

Given a matrix of dimension m * n where each cell in the matrix can have values 0, 1, or 2 which has the following meaning: 0: Empty cell 1: Cells have fresh oranges 2: Cells have rotten oranges So the task is to determine what is the minimum time required so that all the oranges become rotten. A rotten orange at index [i, j] can rot other fresh or

Extendible Hashing (Dynamic approach to DBMS)

Extendible Hashing is a dynamic hashing method wherein directories, and buckets are used to hash data. It is an aggressively flexible method in which the hash function also experiences dynamic changes. Main features of Extendible Hashing: The main features in this hashing technique are: Directories: The directories store addresses of the buckets in

Reliability Design Problem in Dynamic Programming

The reliability design problem is the designing of a system composed of several devices connected in series or parallel. Reliability means the probability to get the success of the device. Let's say, we have to set up a system consisting of D1, D2, D3, ............, and Dn devices, each device has some costs C1, C2, C3, ........, Cn. Each device ha

Convert N to M with given operations using dynamic programming

Given two integers N and M and the task is to convert N to M with the following operations: Multiply N by 2 i.e. N = N * 2.Subtract 1 from N i.e. N = N - 1. Examples: Input: N = 4, M = 6 Output: 2 Perform operation 2: N = N - 1 = 4 - 1 = 3 Perform operation 1: N = N * 2 = 3 * 2 = 6 Input: N = 10, M = 1 Output: 9 Approach: Create an array dp[] of si

Longest subsequence with a given OR value : Dynamic Programming Approach

Given an array arr[], the task is to find the longest subsequence with a given OR value M. If there is no such sub-sequence then print 0.Examples: Input: arr[] = {3, 7, 2, 3}, M = 3 Output: 3 {3, 2, 3} is the required subsequence 3 | 2 | 3 = 3Input: arr[] = {2, 2}, M = 3 Output: 0 Approach: A simple solution is to generate all the possible sub-sequ

Python | Implementing Dynamic programming using Dictionary

Dynamic Programming is one way which can be used as an optimization over plain recursion. Wherever we see a recursive solution that has repeated calls for the same inputs, we can optimize it using Dynamic Programming. The idea is to simply store the results of subproblems so that we do not have to re-compute them when needed later. This simple opti