MINIMUM SPANNING TREES STUDY GUIDE


Definition of edge-weighted graph and MST.

Cuts.

Manually performing Kruskal's and Prim's algorithms. These are easy and you should be able to do them even under the influence of powerful sedatives.

Why Kruskal's and Prim's algorithms work.

Implementing Kruskal's and Prim's algorithms.

Recommended Problems

C level

  1. Spring 08 Final, #2a, #2b
  2. Fall 08 Final, #2a, #2b
  3. Fall 09 Final, #1b
  4. Fall 09 Final, #3a, #3c
  5. Fall 10 Final, #4a, #4b
  6. Fall 10 Final, #3a, #3b
  7. Spring 12 Final, #4a, #4b
  8. Would Kruskal's or Prim's algorithm work with edge-weighted digraphs?

B level

  1. Fall 09 Final, #3b
  2. Fall 12 Final, #4a, #4b, #4c, #4d
  3. Textbook 4.3.8 - this is a particularly handy concept!
  4. Textbook 4.3.12
  5. Textbook 4.3.13
  6. Textbook 4.3.20
  7. True or False: Given any two components that are generated as Kruskal's algorithm is running (but before it has completed), the smallest edge connecting those two components is part of the MST.
  8. Textbook 4.3.19 - to be clear, for each vertex v, we maintain edgeTo[v] and distTo[v] and to find the nontree vertex with the smallest distTo[], we scan through the entire distTo[] array.

A level

  1. Spring 08 Final, #3
  2. Fall 09 Final, #3d
  3. Textbook 4.3.26

Just for fun

  1. Figure out if Kruskal's, Prim's Lazy, or Prim's Eager algorithm are faster on "typical" graphs. Use the code from the booksite.