Graph serialization

Topological Sort (From Wikipedia):

In graph theory, a topological sort or topological ordering of a directed acyclic graph (DAG) is a linear ordering of its nodes in which each node comes before all nodes to which it has outbound edges. Every DAG has one or more topological sorts.

Pseudo code:

L ← Empty list where we put the sorted elements
Q ← Set of all nodes with no incoming edges
while Q is non-empty do
    remove a node n from Q
    insert n into L
    for each node m with an edge e from n to m do
        remove edge e from the graph
        if m has no other incoming edges then
            insert m into Q
if graph has edges then
    output error message (graph has a cycle)
else 
    output message (proposed topologically sorted order: L)

I would expect tools that need this simply walk the tree in a depth-first manner and when they hit a leaf, just process it (e.g. compile) and remove it from the graph (or mark it as processed, and treat nodes with all leaves processed as leaves).

As long as it's a DAG, this simple stack-based walk should be trivial.

I've come up with a fairly naive recursive algorithm (pseudocode):

Map<Object, List<Object>> source; // map of each object to its dependency list
List<Object> dest; // destination list

function resolve(a):
    if (dest.contains(a)) return;
    foreach (b in source[a]):
        resolve(b);
    dest.add(a);

foreach (a in source):
    resolve(a);

The biggest problem with this is that it has no ability to detect cyclic dependencies - it can go into infinite recursion (ie stack overflow ;-p). The only way around that that I can see would be to flip the recursive algorithm into an interative one with a manual stack, and manually check the stack for repeated elements.

Anyone have something better?