diff --git a/search/floydwarshall.go b/search/floydwarshall.go
index 04d3748d..827296b2 100644
--- a/search/floydwarshall.go
+++ b/search/floydwarshall.go
@@ -14,15 +14,12 @@ type AllPathFunc func(start, goal gr.Node) (path [][]gr.Node, cost float64, err
 // Finds one path between start and goal, which it finds is arbitrary
 type SinglePathFunc func(start, goal gr.Node) (path []gr.Node, cost float64, err error)
 
-// This function returns two functions: one that will generate all shortest paths between two nodes with ids i and j, and one that will generate just one path.
+// This function returns two functions that will generate all shortest paths between two nodes with ids i and j.
 //
 // This algorithm requires the CrunchGraph interface which means it only works on nodes with dense ids since it uses an adjacency matrix.
 //
 // This algorithm isn't blazingly fast, but is relatively fast for the domain. It runs at O((number of vertices)^3), and successfully computes
-// the cost between all pairs of vertices.
-//
-// Generating a single path should be pretty cheap after FW is done running. The AllPathFunc is likely to be considerably more expensive,
-// simply because it has to effectively generate all combinations of known valid paths at each recursive step of the algorithm.
+// the cost between all pairs of vertices. Using just a little extra memory, we can remember all shortest paths
 func FloydWarshall(graph gr.CrunchGraph, cost func(gr.Node, gr.Node) float64) (AllPathFunc, SinglePathFunc) {
 	graph.Crunch()
 	_, _, _, _, _, _, cost, _ = setupFuncs(graph, cost, nil)