Topological sorting

A topological sorting is the task of constructing a topological order of a finite directed graph, or reporting that a directed cycle makes one impossible. Kahn's algorithm repeatedly takes a vertex with no unfinished prerequisites. This is useful whenever an operation consumes results produced by earlier operations: once a vertex is reached in a topological order, every prerequisite along a directed path has already been processed. ^[ref]

The reason a choice is always available in a nonempty finite Directed acyclic graph is simple. If every vertex had an incoming directed edge, repeatedly following predecessors would eventually revisit a vertex, giving a directed cycle. Removing a vertex and its incident directed edges cannot create a directed cycle, so the argument repeats until every vertex is listed. This proves existence of a topological order and explains why finiteness matters to this procedure.

// Target: combinatorics.bigb

A finite nonempty Directed acyclic graph has a unique topological sort exactly when it has a Hamiltonian path. A Hamiltonian path forces the relative order of every consecutive pair and therefore of all vertices. Conversely, in a unique topological sort, every consecutive pair must have a forward edge: if such an edge were absent, swapping that adjacent pair would preserve all edge constraints and produce a second topological sort. The consecutive edges give a Hamiltonian path. Consequently one may compute any topological sort and test its consecutive edges, taking $O(n^2)$ time on an adjacency matrix representation.

A topological order of a finite directed graph $G=(V,E)$ is a sequence $(v_1,\dots ,v_n)$ containing every vertex exactly once, withThus every directed edge points forward in the list. Equivalently, a bijection $p:V\to \{1,\dots ,n\}$ assigning positions satisfies $p(u)<p(v)$ for every directed edge $u\to v$. A topological ordering names the same kind of list. ^[ref]

The toy Directed acyclic graph has exactly five topological orders: $ABCDE$, $ABDCE$, $ACBDE$, $BACDE$, and $BADCE$. These lists were checked by enumerating all $5!=120$ permutations and retaining precisely those satisfying all five directed edge inequalities. Every list ends with $E$, since all other tasks have a directed path to publication. A topological order need not put adjacent entries next to one another in the directed graph: $A$ and $B$ are consecutive in $ABCDE$ without a directed edge between them.

A directed cycle would force the impossible chain of position inequalities $p(u_1)<p(u_2)<\cdots <p(u_k)<p(u_1)$. In the toy example, adding $E\to C$ requires review before publication and publication before review, so there are no topological orders. Together with the construction in topological sorting, this proves that a finite directed graph admits a topological order if and only if it is a Directed acyclic graph. The empty directed graph has the empty sequence as its topological order.

There is also a useful connection to partial orders: define $u⪯v$ when $u=v$ or there is a directed path from $u$ to $v$. For a Directed acyclic graph, this reachability relation is a partial order, and its linear extensions are exactly the topological orders. The Directed acyclic graph specifies which pairs must be ordered; a topological order chooses positions for all the remaining pairs.

Kahn's algorithm maintains each remaining vertex's indegree, the number of its unfinished incoming directed edges, and a FIFO queue of ready vertices. Initialize the counts by scanning all directed edges and enqueue every vertex of indegree zero. Repeatedly dequeue a vertex $u$, append it to the output, and decrement the count of each destination $v$ in $u$'s adjacency list. Enqueue $v$ exactly when its count becomes zero. When the FIFO queue empties, accept the output if it contains all vertices; otherwise report a directed cycle. ^[ref]

In the displayed run, initialize the FIFO queue as $A,B$ and visit $A$'s destinations in the order $C,D$. Removing $A$ makes $C$ ready but leaves $D$ waiting for $B$. Removing $B$ then makes $D$ ready. Publication becomes ready only after both $C$ and $D$ are removed. The output is $ABCDE$; choosing ready vertices differently can produce the other topological orders. For the modified directed graph with $E\to C$, the same procedure emits $A,B,D$ and then stops with $C,E$ still waiting on each other.

The invariant is that each stored indegree counts incoming directed edges from unprocessed vertices. A ready vertex therefore has every prerequisite already in the output. If the FIFO queue empties with vertices left, every remaining vertex has a predecessor in the remaining directed graph; the predecessor argument gives a directed cycle. The unprocessed vertices can also include tasks blocked downstream of a directed cycle, so the leftover list alone is not a list of exactly the cyclic vertices.

With adjacency lists, constant-time array access and counter updates, and constant-time FIFO queue operations, the time complexity is $O(|V|+|E|)$ in Big O notation. Initialization scans all vertices and directed edges; each vertex is then enqueued at most once and each outgoing directed edge processed at most once. Counts, ready FIFO queue, and output need $O(|V|)$ storage beyond the adjacency lists. Shifting an array on every dequeue invalidates this bound. ^{[ref] [ref]}

The name refers to A. B. Kahn's 1962 paper "Topological sorting of large networks", published in Communications of the ACM, volume 5, issue 11, pages 558–562. Its abstract motivates topological sorting through network analysis and project planning. ^[ref]

// Target: foundations-of-mathematics.bigb