Description
1. A node v in a directed rooted tree T = (V, E) is an ancestor of node u if the path from the root to u
passes through v. The lowest common ancestor(LCA) of two nodes u and v in T is the deepest node
w that is an ancestor of both u and v, where the depth of node is defined as the number of edges on
the path from the root to that node. Given two nodes u and v in an directed rooted tree T, design
an algorithm that finds the lowest common ancestor in O(h) time, where h is the distance between
u and v in the underlying undirected version of T. You are allowed to do O(|E|) preprocessing on
the tree before various pairs u and v are given to you, and the cost of preprocessing will not be
counted in your LCA algorithm.
2. In some country, there are n flights among n cities. Each city has an exactly one outgoing flight
but may have no incoming flight or multiple incoming flights. Design an algorithm to find the
largest subset S of cities such that each city in S has at least one incoming flight from another
city in S. (hint: recall the in-degree array we used in developing the topological sort algorithm in
class)
3. A directed graph G = (V, E) is acyclic if there is no cycle in G. Given a directed graph G, design
an O(|E|) algorithm to determine whether it is acyclic or not.
4. Given a directed acyclic graph(DAG) G = (V, E) which is just a directed simple path and |V| = n.
The topological sorting can be solved on G by doing DFS from the source node and numbering
nodes from n down to 1 when the DFS colors a node black, i.e., reverse post-ordering on the DFS
tree. If we are given another DAG G
0 which are two node-disjoint simple paths, we can extend
G
0 by creating a super source node and two edges from the super source to the two sources of
the paths. The topological sorting on extended G
0
can be solved if we start a DFS from the super
source node and allocate numbers from n down to 0 in the manner described above. The super
source node will get the number 0, and all the other nodes will be topologically sorted from 1
to n. Given an arbitrary DAG G = (V, E), extend this idea to give an O(|E|) algorithm to solve
topological sorting on G by using DFS. Argue the correctness of your algorithm and its O(|E|) time
complexity.
Æ Express your algorithm in a well-structured manner. Use pseudo code and the textbook has good
examples to follow. Avoid using a long continuous piece of text to describe your algorithm. Start
each problem on a NEW page. Unless specified, you should justify the time complexity of your
algorithm and why it works. For grading, we will take into account both the correctness and
the clarity. Your answers are supposed to be in a simple and understandable manner and sloppy
answers are expected to receiver fewer points.
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scanner app. Match each problem with your answer on Gradescope. Use dark pen or pencil and
your handwriting should be clear and legible.
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Æ We recommend using LATEX, LYX or other word processing software for writing the homework. This
is NOT a requirement but it helps us to grade and give feedback.
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