Just because the dijstra works for this case, does not mean that it works for every case. it might just be happening that two negatives cancelled each other to create a positive.
here is a proof of why dijikstra does not work for that
Recall that in Dijkstra’s algorithm, once a vertex is marked as “closed” (and out of the open set) - the algorithm found the shortest path to it , and will never have to develop this node again - it assumes the path developed to this path is the shortest.
But with negative weights - it might not be true. For example:
A
/ \
/ \
/ \
5 2
/ \
B--(-10)-->C
V={A,B,C} ; E = {(A,C,2), (A,B,5), (B,C,-10)}
Dijkstra from A will first develop C, and will later fail to find A->B->C
Note that this is important, because in each relaxation step, the algorithm assumes the “cost” to the “closed” nodes is indeed minimal, and thus the node that will next be selected is also minimal.
The idea of it is: If we have a vertex in open such that its cost is minimal - by adding any positive number to any vertex - the minimality will never change.
Without the constraint on positive numbers - the above assumption is not true.
Since we do “know” each vertex which was “closed” is minimal - we can safely do the relaxation step - without “looking back”. If we do need to “look back” - Bellman-Ford offers a recursive-like (DP) solution of doing so.
As for working with set, remember that Dijkstra is a greedy algorithm, meaning we assume that we have made the best choice possible in every step of the algorithm. With negative edges, this is no longer possible and thus a greedy algorithm will not suffice, even if we store the values in a set