Briefly describe and discuss the knowledge benefits associated with an Algorithm growth rate:

1. Briefly describe and discuss the knowledge benefits associated with an Algorithm growth rate:
2. What does best, worst, and average case refer to?
3. Why doesn’t a faster computer always solve large data processing problems?
4. About Asymptotic Analysis:
4.1. What does asymptotic analysis refer to and why is it helpful to know (i.e. why use big-O notation)?
4.2. What does Big-Oh refer to and what is it good for?
4.3. What does Big-Omega refer to and what is it good for?
4.4. What does big-theta refer to and what is it good for?
5. What are Space/time trade-offs and what should be considered when making determinations about them? 
6. Given multiple algorithms that perform the same process but with different time equations, what are your considerations, technical and otherwise, in selecting the one to use.
7. What is the benefit gained from hashing?
8. What performance implementation does Java invoke to counteract massive collisions?






Figure 1

9. Draw the adjacency matrix representation for the above graph (Figure 1).

10. Draw the adjacency list representation for the above graph (Figure 1)..

11.



Figure 2

12. Draw the DFS (Depth First Search) tree for the above graph (Figure 2).


13. Draw the BFS (Breadth First Search) tree for the above graph (Figure 2).



 
14. Show each of the shortest paths generated by running Dijkstra’s shortest-paths algorithm on the graph above beginning at Vertex 4 (Figure 2).