Found 1862 Articles for Data Structure

3-coloring is NP Complete

Aayush Shukla
Updated on 04-Aug-2023 12:55:57

341 Views

3-shading is an exemplary NP-complete issue in chart hypothesis where the goal is to decide whether a given diagram can be hued utilizing three tones, to such an extent that no two neighboring vertices share a similar variety. The issue is delegated NP-complete, importance there is no known effective calculation to tackle it for all occasions, and checking a potential arrangement should be possible in polynomial time. Numerous other NP-complete issues can be decreased to 3-shading, showing its computational intricacy and its importance in understanding the more extensive class of NP-complete issues. Subsequently, 3-shading assumes a major part in the ... Read More

Arrange the Array such that upon Performing given Operations an Increasing order is Obtained

Ayush Singh
Updated on 02-Aug-2023 16:07:44

77 Views

You must use the proper sorting algorithms in order to organise an array in increasing order using the specified operations. Determine the most effective method first depending on the array size and data properties. Bubble Sort, Merge Sort, and Quick Sort are examples of popular sorting algorithms. Apply the chosen algorithm repeatedly, shifting the positions of elements based on comparisons between them until the array is organised in ascending order. The effectiveness of an algorithm is determined by how time−consuming it is, with the best ones producing quicker results. The array may be effectively organised in increasing order by carefully ... Read More

Count of Nodes with Maximum Connection in an Undirected Graph

Ayush Singh
Updated on 02-Aug-2023 16:05:19

219 Views

In the field of network analysis, the number of nodes with the highest degree, signifying the greatest number of connections to other nodes in the network, is referred to as the "count of nodes with maximum connection" in an undirected graph. The number of edges that incident upon a node determines its degree. We may determine the critical or central points in the graph by identifying the nodes with the highest degree. This has important ramifications for a variety of applications, including network research, social network studies, and optimisation methods. Understanding these crucial nodes makes it easier to comprehend the ... Read More

Finding if a Node X is Present in Subtree of Another Node Y or Vice Versa for Q Queries

Ayush Singh
Updated on 02-Aug-2023 16:03:36

60 Views

For Q queries, do the following to see if node X is in node Y's subtree or vice versa: Starting at node Y, navigate its subtree while keeping an eye out for node X. If discovered, X is in Y's subtree. Start at node X and navigate its subtree to find node Y in the reverse scenario. If Y is found, Y is a member of X's subtree. To efficiently carry out these tests, use tree traversal algorithms like Depth−First Search (DFS) or Breadth−First Search (BFS). The procedure guarantees accurate relationship determination between the nodes in each query. Methods Used ... Read More

Count of Connected Components in given Graph after Removal of given Q Vertices

Ayush Singh
Updated on 02-Aug-2023 15:56:20

265 Views

The number of disconnected subgraphs created by the remaining vertices in a graph following the removal of Q specified vertices is represented by the count of connected components. There are no edges linking the various components; instead, each connected component is made up of a collection of vertices connected by edges. Some vertices may become isolated as a result of the removal of the Q vertices, causing connections to fall apart and new components to form. The approach seeks to ascertain how many disconnected subgraphs there will ultimately be. Numerous applications, including network analysis, social network studies, and optimisation methods, ... Read More

Find Edges Removing which does not Disconnect the Graph

Ayush Singh
Updated on 02-Aug-2023 15:54:42

109 Views

Analyse the connectedness of each edge in the Graph to locate edges whose removal won't break the Graph. We can identify which edges are essential for preserving connectivity between nodes by methodically examining the effect of eliminating individual edges. "Bridge edges" or "critical edges" are edges that, when eliminated, nonetheless leave the Graph connected. These edges are essential for maintaining the general structure of the Graph and avoiding disconnection. To ensure system robustness and effective communication, such edges must be identified in network analysis, transportation planning, and infrastructure design. Methods Used Tarjan's Algorithm Kruskal's Algorithm Tarjan's Algorithm In ... Read More

Minimum Cost to Convert 1 to N by Multiplying X or Right Rotation of Digits

Ayush Singh
Updated on 02-Aug-2023 15:52:57

49 Views

We can use the following technique to find the cheapest way to multiply X or right−rotate its digits from 1 to N. To monitor the initial lowest cost, create a cost variable. Check to see if N is evenly divided by X at each stage as you progress from N to 1. If so, divide N by X to update it and carry on with the process. Rotate N's digits to the right to increase its value if it is not divisible by X. Increase the cost variable in this situation. The ultimate cost variable value will be the least ... Read More

Generate Lexicographically Smallest Permutation of 1 to N where Elements follow given Relation

Ayush Singh
Updated on 02-Aug-2023 15:51:08

226 Views

In this topic, we seek the relationally constrained lexicographically minimal permutation of numbers from 1 to N. The relation describes the relative order of certain of the permutation's components. We ensure that the resulting permutation is the least possible when comparing lexicographically by carefully organising the numbers based on this relation. In order to achieve the lowest feasible arrangement of the numbers, the best sequence must be found that both meets the relation restrictions and does so. To efficiently produce the intended outcome, the procedure entails thorough analysis and element selection. Methods Used Greedy Approach Backtracking Greedy Approach ... Read More

Applications, Advantages and Disadvantages of Graph

Ayush Singh
Updated on 02-Aug-2023 15:48:03

3K+ Views

Graphs are used in different disciplines. They are utilised in biology to represent gene interactions, in transportation for route optimisation, and in social networks for user connection analysis. The visual representation of intricate relationships and the capacity to see patterns and trends are two benefits of graphs. However, dealing with large datasets can make graphs bulky and difficult to understand. Additionally, creating graphs can take time and necessitate knowledge. Despite these drawbacks, graphs continue to be an effective tool for data analysis and decision−making across a range of disciplines. Methods Used Set Representation Linked Representation Sequential Representaion Set ... Read More

Applications, Advantages and Disadvantages of Directed Graph

Ayush Singh
Updated on 02-Aug-2023 15:49:33

538 Views

Diverse domains, including CS, social networks, and logistics, use directed graphs, also known as digraphs. Arrows indicating the direction of links serve to depict the interconnections between the various components. They have the ability to represent intricate connections, handle data quickly, and facilitate pathfinding algorithms. Their drawbacks, however, include the potential for analysis complexity, the challenge of visualising vast graphs, and the requirement for cautious treatment of cyclic structures. Despite these drawbacks, directed graphs continue to be fundamental tools for comprehending, evaluating, and enhancing interconnected systems in a variety of real−world contexts. Methods Used Topological Sorting Strongly Connected Components ... Read More

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