Topological Sorting and Strongly Connected Components

In the world of competitive programming, having a strong grasp of graph algorithms is essential. One such algorithm that proves to be highly useful is Topological Sorting and the concept of Strongly Connected Components (SCC). In this article, we will explore these two concepts and understand how they can be applied in solving programming problems.

Topological Sorting

Topological sorting is an algorithmic approach used to sort the vertices of a directed graph in a linear order, such that for every directed edge (u, v), vertex u comes before vertex v in the ordering. In simpler terms, it arranges the vertices in a way that preserves the partial order of the graph.

There can be multiple valid topological sortings for a graph. The most common approach to perform topological sorting is using Depth-First Search (DFS) on the graph.

The algorithm works as follows:

  1. Perform a DFS traversal on the graph.
  2. Mark the visited vertices.
  3. When we finish exploring a vertex and backtrack, add it to the result list.

Topological sorting finds its applications in various scenarios, such as task scheduling, resolving dependencies, and determining the order of courses to be taken in a curriculum. It is also a critical component in solving several graph-related competitive programming problems.

Strongly Connected Components (SCC)

A strongly connected component refers to a subgraph in a directed graph where every vertex is reachable from every other vertex. In simple terms, it is a maximal group of vertices that can be reached from one another.

Finding strongly connected components can be done using the concept of Tarjan's algorithm, which is a linear-time algorithm based on DFS.

The algorithm works as follows:

  1. Perform DFS traversal on the graph and keep track of the order of visitation for each vertex.
  2. Maintain a stack to keep track of the vertices in the current strongly connected component.
  3. Consider each vertex in the graph and, if it is not visited, perform DFS from that vertex.
  4. During the DFS traversal, assign a unique number to each vertex based on the visitation order.
  5. Whenever we encounter a visited vertex during the DFS traversal, it means we have discovered a strongly connected component. Pop the stack until we reach the current vertex and assign the same unique number to all the popped vertices. This number will act as an identifier for the strongly connected component.

Understanding strongly connected components is valuable in problems related to finding cycles in a graph, analyzing network connectivity, and solving various optimization tasks.


Topological sorting and strongly connected components are essential concepts in competitive programming, especially in problems involving graphs. Mastering these concepts can significantly enhance your problem-solving skills and help you tackle a wide range of programming challenges. By implementing these algorithms effectively using Java, you can navigate complex graph-related problems with confidence.

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