Ans.A linked list is a linear data structure where elements are stored in nodes. Each node contains a data element and a reference (pointer) to the next node in the sequence.
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What is the difference between an array and a linked list?Ans.An array stores elements in contiguous memory locations, allowing for constant-time access to elements via indexing. In contrast, a linked list does not require contiguous memory and offers dynamic memory allocation, but accessing elements is slower and requires traversal.
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What is a doubly linked list?Ans.A doubly linked list is a linked list where each node contains a reference to both the next and the previous node, allowing traversal in both forward and backward directions.
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Explain the concept of a stack.Ans.A stack is a linear data structure that follows the Last In, First Out (LIFO) principle. Elements are added and removed from only one end, called the top. It supports operations like push (addition) and pop (removal).
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How is a queue different from a stack?Ans.A queue is a linear data structure that follows the First In, First Out (FIFO) principle, whereas a stack follows the Last In, First Out (LIFO) principle. In a queue, elements are added at the rear and removed from the front.
Ans.A binary tree is a hierarchical data structure composed of nodes, where each node has at most two children, referred to as the left child and the right child.
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Explain the concept of a binary search tree (BST).Ans.A binary search tree is a binary tree in which the value of each node in the left subtree is less than the value of the node itself, and the value of each node in the right subtree is greater. This property facilitates efficient searching, insertion, and deletion operations.
Ans.A hash table is a data structure that stores key-value pairs. It uses a hash function to compute an index into an array of buckets or slots, from which the desired value can be found.
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What is collision resolution in a hash table?Ans.Collision resolution is the process of handling the situation when two or more keys hash to the same index in a hash table. Common collision resolution techniques include chaining (using linked lists) and open addressing (probing).
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Explain the concept of dynamic programming.Ans.Dynamic programming is a method for solving complex problems by breaking them down into simpler subproblems and solving each subproblem only once. It stores the solutions to subproblems in a table to avoid redundant computations.
Ans.An AVL tree is a self-balancing binary search tree where the height difference between the left and right subtrees of any node is at most one. This property ensures that the tree remains balanced, optimizing search, insertion, and deletion operations.
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Explain the concept of a trie.Ans.A trie, also known as a prefix tree, is a tree-like data structure used to store a dynamic set of strings where each node represents a single character of the string. It allows for efficient prefix matching and is commonly used in dictionary implementations and IP routing tables.
Ans.A heap is a specialized tree-based data structure that satisfies the heap property. In a max heap, the value of each node is greater than or equal to the values of its children, while in a min heap, the value of each node is less than or equal to the values of its children. Heaps are commonly used in priority queues and heap sort algorithms.
Ans.A graph is a non-linear data structure composed of a finite set of vertices (nodes) and a collection of edges that connect pairs of vertices. Graphs are used to model relationships between objects and are fundamental in various applications, such as social networks, transportation systems, and computer networks.
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Explain depth-first search (DFS) and its applications.Ans.Depth-first search is a graph traversal algorithm that explores as far as possible along each branch before backtracking. It is used to solve problems such as finding connected components, topological sorting, and solving puzzles like mazes.
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What is breadth-first search (BFS) and where is it used?Ans.Breadth-first search is a graph traversal algorithm that explores all the vertices in a graph at the present depth before moving to the vertices at the next depth level. It is commonly used to find the shortest path in unweighted graphs, network broadcasting, and web crawling.
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Explain Dijkstra's algorithm and its significance.Ans.Dijkstra's algorithm is a graph search algorithm used to find the shortest path between nodes in a weighted graph with non-negative edge weights. It is widely used in various applications, including network routing protocols, transportation planning, and computer networks.
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What is the Floyd-Warshall algorithm?Ans.The Floyd-Warshall algorithm is a dynamic programming algorithm used to find the shortest paths between all pairs of vertices in a weighted graph with positive or negative edge weights (but no negative cycles). It is particularly useful for solving problems like the traveling salesman problem.
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Explain the concept of a segment tree.Ans.A segment tree is a tree-like data structure used for storing information about intervals or segments of an array. It allows for efficient querying of various interval-based problems, such as finding the sum, minimum, maximum, or other associative operation over a range of values in an array.
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What is the difference between a stack and a queue?Ans.A stack is a Last In, First Out (LIFO) data structure, while a queue is a First In, First Out (FIFO) data structure. Stacks are used in function calls and expression evaluation, while queues are used in scheduling, buffering, and breadth-first search algorithms.
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Explain the concept of a Red-Black tree.Ans.A Red-Black tree is a self-balancing binary search tree where each node is colored either red or black. It maintains balance by enforcing several properties, including ensuring that no path from the root to a leaf node is more than twice as long as any other path. Red-Black trees are commonly used in balanced tree implementations.
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What is a B-tree and where is it used?Ans.A B-tree is a self-balancing tree data structure that maintains sorted data and allows for efficient insertion, deletion, and searching operations. It is commonly used in databases and file systems where large amounts of data need to be stored and accessed efficiently.
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Explain the concept of a Bloom filter.Ans.A Bloom filter is a space-efficient probabilistic data structure used to test whether an element is a member of a set. It uses a bit array and multiple hash functions to represent the set and quickly determine if an element is probably in the set, with a small probability of false positives.
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What is a suffix tree and where is it used?Ans.A suffix tree is a compressed trie data structure that represents all the suffixes of a given string. It is commonly used in string processing applications such as pattern matching, substring search, and bioinformatics for DNA sequence analysis.
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Explain the concept of a disjoint-set data structure (Union-Find).Ans.A disjoint-set data structure, also known as Union-Find or merge-find set, is a data structure that keeps track of a set of elements partitioned into disjoint (non-overlapping) subsets. It supports two operations: union, which merges two sets, and find, which determines which set a particular element belongs to. It is used in various algorithms, including Kruskal's minimum spanning tree algorithm and image processing applications.
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What is a skip list and where is it used?Ans.A skip list is a probabilistic data structure that allows for efficient searching, insertion, and deletion operations in a sorted sequence. It consists of multiple layers of linked lists where each layer represents a subset of the elements in the lower layers. Skip lists are used in applications where balanced trees are too complex or impractical, such as in database indexing and caching.
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Explain the concept of an interval tree.Ans.An interval tree is a tree data structure used for storing intervals of the form [start, end]. It allows for efficient querying of overlapping intervals and finding intervals that contain a given point. Interval trees are commonly used in scheduling, computational geometry, and database systems.
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What is a cuckoo hash table?Ans.A cuckoo hash table is a variant of hash table that resolves collisions by using multiple hash functions and two hash tables. When a collision occurs, the existing element is relocated to an alternate location determined by the other hash function. Cuckoo hash tables offer constant-time worst-case lookup and deletion operations.
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Explain the concept of a splay tree.Ans.A splay tree is a self-adjusting binary search tree that reorganizes itself based on the access patterns of the elements. When an element is accessed, it is moved to the root of the tree through a series of rotations called splaying, which improves future access times for the same element. Splay trees are used in applications where frequently accessed elements need to be quickly accessible.
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What is the difference between a hash table and a hash map?Ans.A hash table is a data structure that stores key-value pairs, while a hash map is a general term used to describe any data structure that implements a mapping between keys and values. In many programming languages, the terms hash table and hash map are used interchangeably, but technically, a hash map may refer to an implementation of a hash table.