Shortest Paths in DAG solved by 338

Problem

There are two subclasses of graphs that automatically exclude the possibility of negative cycles: graphs without negative edges, and graphs without cycles. We already know how to efficiently handle the former (see the problem “Negative Weight Cycle”). We will now see how the single-source shortest-path problem can be solved in just linear time on directed acyclic graphs.

As before, we need to perform a sequence of updates (recall Bellman-Ford algorithm) that includes every shortest path as a subsequence. The key source of efficiency is that

In any path of a DAG, the vertices appear in increasing linearized order.

Notice that our scheme doesn’t require edges to be positive. In particular, we can find longest paths in a DAG by the same algorithm: just negate all edge lengths.

Source: Algorithms by Dasgupta, Papadimitriou, Vazirani. McGraw-Hill. 2006.

Given: A weighted DAG with integer edge weights from $-10^{3}$ to $10^3$ and $n \le 10^5$ vertices in the edge list format.

Return: An array $D[1..n]$ where $D[i]$ is the length of a shortest path from the vertex $1$ to the vertex $i$ ($D[1]=0$). If $i$ is not reachable from $1$ set $D[i]$ to x.

Sample Dataset

5 6
2 3 4
4 3 -2
1 4 1
1 5 -3
2 4 -2
5 4 1

Sample Output

0 x -4 -2 -3