![]() Trees have a number of important properties, including: The node at the top of the tree is called the root node. The nodes that do not have any children are called leaf nodes. Each node has a value, and it can have zero or more child nodes, which are represented as a list of pointers to the child nodes. Push adds an element to the top of the stack, and pop removes the element from the top of the stack.Ī tree is a hierarchical data structure that consists of nodes arranged in a tree-like structure. There are two main operations that can be performed on a stack: push and pop. This means that the last element added to the stack will be the first one to be removed. ![]() Enqueue adds an element to the end of the queue, and dequeue removes the element from the front of the queue.Ī stack is a type of data structure that stores a collection of elements in a linear order, and follows the principle of Last In First Out (LIFO). There are two main operations that can be performed on a queue: enqueue and dequeue. This means that the first element added to the queue will be the first one to be removed. The first node in the linked list is called the head, and the last node is called the tail.Ī queue is a type of data structure that stores a collection of elements in a linear order, and follows the principle of First In First Out (FIFO). The elements in an array are accessed by their indices, which are integer values that specify the position of an element in the array.Ī linked list is a linear data structure that consists of a sequence of nodes, where each node stores a reference to an object and a reference to the next node in the sequence. Most common types of data structures and there propertiesĪn array is a data structure that stores a collection of elements of the same data type. Non-linear data structures are usually more complex, but they can provide faster access to elements and allow for more efficient operations. Linear data structures are typically easier to understand and implement, but they may not be as efficient as non-linear data structures when it comes to searching, inserting, and deleting elements. Examples of non-linear data structures include trees, graphs, and hash tables. Non-linear data structures are structures that are not organized in a linear way, meaning that the elements are not stored in a sequential manner. Dynamic DS are more flexible, but they may require more memory and may be less efficient when it comes to accessing elements. Static DS are typically easier to implement and are more efficient when it comes to accessing elements, but they can be less flexible than dynamic data structures. Examples - linked lists, stacks, and queues. This means that you can add or remove elements from a dynamic data structure as needed. ![]() Examples - arrays and static lists.ĭynamic DS is a data structure that can change size during the execution of a program. This means that you cannot add or remove elements from a static data structure after it has been created. Static DS is a data structure that has a fixed size and does not change once it has been created. Examples of linear data structures include arrays, linked lists, and stacks. Linear Data Structure- are structures that are organized in a linear way, meaning that the elements are stored in a sequential manner, one after the other. Linear data structures are again categorized based on whether they are static or dynamic. also known as derived data types.Īs you can see - non-primitive data structures are further classified into linear and non-linear. For example, array, linked list, stack, queue, tree, graph, and so on.
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