[table][br][tr][br][td][b]Factual Questions:[/b][br]What defines a Minimum Spanning Tree (MST) in graph theory?[br][br]How does Kruskal's algorithm find the MST in a graph?[br][br]Describe the process of Prim's algorithm for generating an MST.[br][/td][br][br][td][b]Conceptual Questions:[/b][br]Compare and contrast Kruskal’s and Prim’s algorithms in terms of their approach to finding an MST.[br][br]What role does the concept of "minimum total edge weight" play in the definition and finding of an MST?[br][br]How do the implementations of Kruskal's and Prim's algorithms differ when using an adjacency matrix?[br][/td][br][br][td][b]Debatable Questions:[/b][br]Which algorithm, Kruskal's or Prim's, is generally more efficient in practice for finding an MST, considering various graph structures?[br][br]Can the choice between using Kruskal’s and Prim’s algorithms significantly affect the performance of network design and optimization tasks?[br][br]In the context of real-world applications, how critical is the distinction between choosing Kruskal’s versus Prim’s algorithm for constructing minimum spanning trees?[br][/td][br][/tr][br][/table][br]

Minimum Spanning Tree (MST) Graph Algorithms: These algorithms find a subset of the edges of a connected, undirected graph that connects all the vertices together, without any cycles and with the minimum possible total edge weight.

Kruskal’s and Prim’s Algorithms: These are two different algorithms for finding the MST of a graph. Kruskal’s algorithm adds the shortest edge that doesn’t produce a cycle until all vertices are connected, while Prim’s algorithm grows the MST one vertex at a time, always choosing the cheapest edge to add.