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One Pager Cheat Sheet

  • We can effectively implement a graph data structure by using an adjacency list in a HashMap to store connected nodes, with an expected time and space complexity of O(1) and O(n), respectively.
  • A Hash Table is an efficient data structure used to quickly lookup key-value pairs in a Graph class.
  • We can store a graph representations in a hash table, which maps each vertex to its adjacent vertices.
  • We can edit the adjacency lists to add and remove nodes from the graph.
  • Hash Tables provide an O(1) time complexity for adding, deleting and referencing any data type in a graph, making them ideal for representing sparse graphs.
  • We can simply add or remove a key from a hash table to add or remove a vertex, but removal requires us to update the adjacency list of neighboring nodes.
  • An adjacency list allows for O(1) random access to a node's neighbors, allowing us to efficiently access and modify the graph with an array representation.
  • We can create edges between two nodes by simply adding them to each others' adjacency lists.
  • To remove an edge, we splice them out of each others' lists.
  • We have successfully created a graph class using various methods.

This is our final solution.

To visualize the solution and step through the below code, click Visualize the Solution on the right-side menu or the VISUALIZE button in Interactive Mode.

JAVASCRIPT
OUTPUT
:001 > Cmd/Ctrl-Enter to run, Cmd/Ctrl-/ to comment

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