Solution: Course Schedule
Let's solve the Course Schedule problem using the Topological Sort pattern.
We'll cover the following
Statement
There are a total of num_courses
courses you have to take. The courses are labeled from 0
to num_courses - 1
. You are also given a prerequisites
array, where prerequisites[i] = [a[i], b[i]]
indicates that you must take course b[i]
first if you want to take the course a[i]
. For example, the pair indicates that to take course , you have to first take course .
Return TRUE if all of the courses can be finished. Otherwise, return FALSE.
Constraints:
-
num_courses
-
prerequisites.length
prerequisites[i].length
-
a[i]
,b[i]
num_courses
- All the pairs
prerequisites[i]
are unique.
Solution
Initialize the hash map with the vertices and their children. We’ll use another hash map to keep track of the number of in-degrees of each vertex. Then we’ll find the source vertex (with in-degree) and increment the counter
. Retrieve the source node’s children and add them to the queue. Decrement the in-degrees of the retrieved children.
We’ll check whether the in-degree of the child vertex becomes equal to zero, and we increment the counter
.
Repeat the process until the queue is empty.
Note: The in-degree is the number of edges coming into a vertex in a directed graph.
The primary purpose of finding a vertex with 0 in-degree is to find a course with a pre-requisite count of 0. When we take a course, say a (that is the pre-requisite of another course, say b), we’ll decrement the in-degree of b by 1, and if the in-degree count becomes 0, we can say that the b’s pre-requisites have been completed.
The slide deck below illustrates the algorithm above, where num_courses = 6
:
Level up your interview prep. Join Educative to access 80+ hands-on prep courses.