X-Git-Url: http://git.megacz.com/?a=blobdiff_plain;f=ghc%2Fcompiler%2Futils%2FDigraph.lhs;h=df34dde833105bb8c82e53cb56d400604b016987;hb=4161ba13916463f8e67259498eacf22744160e1f;hp=2e8b03287f9bacf48a73df5e715f3cfb0e3714b4;hpb=6c381e873e222417d9a67aeec77b9555eca7b7a8;p=ghc-hetmet.git diff --git a/ghc/compiler/utils/Digraph.lhs b/ghc/compiler/utils/Digraph.lhs index 2e8b032..df34dde 100644 --- a/ghc/compiler/utils/Digraph.lhs +++ b/ghc/compiler/utils/Digraph.lhs @@ -1,182 +1,404 @@ -% -% (c) The GRASP/AQUA Project, Glasgow University, 1992-1996 -% -\section[Digraph]{An implementation of directed graphs} - \begin{code} -#include "HsVersions.h" +module Digraph( + + -- At present the only one with a "nice" external interface + stronglyConnComp, stronglyConnCompR, SCC(..), flattenSCC, flattenSCCs, + + Graph, Vertex, + graphFromEdges, buildG, transposeG, reverseE, outdegree, indegree, -module Digraph ( - stronglyConnComp, - topologicalSort, - dfs, - MaybeErr, + Tree(..), Forest, + showTree, showForest, + + dfs, dff, + topSort, + components, + scc, + back, cross, forward, + reachable, path, + bcc - -- alternative interface - findSCCs, SCC(..), Bag ) where -CHK_Ubiq() -- debugging consistency check +# include "HsVersions.h" + +------------------------------------------------------------------------------ +-- A version of the graph algorithms described in: +-- +-- ``Lazy Depth-First Search and Linear Graph Algorithms in Haskell'' +-- by David King and John Launchbury +-- +-- Also included is some additional code for printing tree structures ... +------------------------------------------------------------------------------ + -import Maybes ( Maybe, MaybeErr(..), maybeToBool ) -import Bag ( Bag, filterBag, bagToList, listToBag ) -import FiniteMap ( FiniteMap, listToFM, lookupFM, lookupWithDefaultFM ) -import Util +#define ARR_ELT (COMMA) + +import Util ( sortLt ) + +-- Extensions +import ST + +-- std interfaces +import Maybe +import Array +import List \end{code} -This module implements at least part of an abstract data type for -directed graphs. The part implemented is what we need for doing -dependency analyses. ->type Edge vertex = (vertex, vertex) ->type Cycle vertex = [vertex] +%************************************************************************ +%* * +%* External interface +%* * +%************************************************************************ + +\begin{code} +data SCC vertex = AcyclicSCC vertex + | CyclicSCC [vertex] + +flattenSCCs :: [SCC a] -> [a] +flattenSCCs = concatMap flattenSCC + +flattenSCC (AcyclicSCC v) = [v] +flattenSCC (CyclicSCC vs) = vs +\end{code} + +\begin{code} +stronglyConnComp + :: Ord key + => [(node, key, [key])] -- The graph; its ok for the + -- out-list to contain keys which arent + -- a vertex key, they are ignored + -> [SCC node] + +stronglyConnComp edges + = map get_node (stronglyConnCompR edges) + where + get_node (AcyclicSCC (n, _, _)) = AcyclicSCC n + get_node (CyclicSCC triples) = CyclicSCC [n | (n,_,_) <- triples] + +-- The "R" interface is used when you expect to apply SCC to +-- the (some of) the result of SCC, so you dont want to lose the dependency info +stronglyConnCompR + :: Ord key + => [(node, key, [key])] -- The graph; its ok for the + -- out-list to contain keys which arent + -- a vertex key, they are ignored + -> [SCC (node, key, [key])] + +stronglyConnCompR [] = [] -- added to avoid creating empty array in graphFromEdges -- SOF +stronglyConnCompR edges + = map decode forest + where + (graph, vertex_fn) = graphFromEdges edges + forest = scc graph + decode (Node v []) | mentions_itself v = CyclicSCC [vertex_fn v] + | otherwise = AcyclicSCC (vertex_fn v) + decode other = CyclicSCC (dec other []) + where + dec (Node v ts) vs = vertex_fn v : foldr dec vs ts + mentions_itself v = v `elem` (graph ! v) +\end{code} %************************************************************************ %* * -%* Strongly connected components * +%* Graphs %* * %************************************************************************ -John Launchbury provided the basic code for doing strongly-connected -components. -The result is a list of cycles (each of which is a list of vertices), -and these cycles are topologically sorted, so that if there is an edge from -cycle A to cycle B, then A occurs after B in the result list. +\begin{code} +type Vertex = Int +type Table a = Array Vertex a +type Graph = Table [Vertex] +type Bounds = (Vertex, Vertex) +type Edge = (Vertex, Vertex) +\end{code} \begin{code} -stronglyConnComp :: (vertex->vertex->Bool) -> [Edge vertex] -> [vertex] -> [[vertex]] +vertices :: Graph -> [Vertex] +vertices = indices -stronglyConnComp eq edges vertices - = snd (span_tree (new_range reversed_edges) - ([],[]) - ( snd (dfs (new_range edges) ([],[]) vertices) ) - ) - where - reversed_edges = map swap edges +edges :: Graph -> [Edge] +edges g = [ (v, w) | v <- vertices g, w <- g!v ] - swap (x,y) = (y,x) +mapT :: (Vertex -> a -> b) -> Table a -> Table b +mapT f t = array (bounds t) [ (,) v (f v (t!v)) | v <- indices t ] - -- new_range :: Eq v => [Edge v] -> v -> [v] +buildG :: Bounds -> [Edge] -> Graph +buildG bounds edges = accumArray (flip (:)) [] bounds edges - new_range [] w = [] - new_range ((x,y):xys) w - = if x `eq` w - then (y : (new_range xys w)) - else (new_range xys w) +transposeG :: Graph -> Graph +transposeG g = buildG (bounds g) (reverseE g) - elem x [] = False - elem x (y:ys) = x `eq` y || x `elem` ys +reverseE :: Graph -> [Edge] +reverseE g = [ (w, v) | (v, w) <- edges g ] -{- span_tree :: Eq v => (v -> [v]) - -> ([v], [[v]]) - -> [v] - -> ([v], [[v]]) --} - span_tree r (vs,ns) [] = (vs,ns) - span_tree r (vs,ns) (x:xs) - | x `elem` vs = span_tree r (vs,ns) xs - | True = case (dfs r (x:vs,[]) (r x)) of { (vs',ns') -> - span_tree r (vs',(x:ns'):ns) xs } +outdegree :: Graph -> Table Int +outdegree = mapT numEdges + where numEdges v ws = length ws -{- dfs :: Eq v => (v -> [v]) - -> ([v], [v]) - -> [v] - -> ([v], [v]) --} - dfs r (vs,ns) [] = (vs,ns) - dfs r (vs,ns) (x:xs) | x `elem` vs = dfs r (vs,ns) xs - | True = case (dfs r (x:vs,[]) (r x)) of { (vs',ns') -> - dfs r (vs',(x:ns')++ns) xs } +indegree :: Graph -> Table Int +indegree = outdegree . transposeG \end{code} + +\begin{code} +graphFromEdges + :: Ord key + => [(node, key, [key])] + -> (Graph, Vertex -> (node, key, [key])) +graphFromEdges edges + = (graph, \v -> vertex_map ! v) + where + max_v = length edges - 1 + bounds = (0,max_v) :: (Vertex, Vertex) + sorted_edges = sortLt lt edges + edges1 = zipWith (,) [0..] sorted_edges + + graph = array bounds [(,) v (mapMaybe key_vertex ks) | (,) v (_, _, ks) <- edges1] + key_map = array bounds [(,) v k | (,) v (_, k, _ ) <- edges1] + vertex_map = array bounds edges1 + + (_,k1,_) `lt` (_,k2,_) = case k1 `compare` k2 of { LT -> True; other -> False } + + -- key_vertex :: key -> Maybe Vertex + -- returns Nothing for non-interesting vertices + key_vertex k = find 0 max_v + where + find a b | a > b + = Nothing + find a b = case compare k (key_map ! mid) of + LT -> find a (mid-1) + EQ -> Just mid + GT -> find (mid+1) b + where + mid = (a + b) `div` 2 +\end{code} + +%************************************************************************ +%* * +%* Trees and forests +%* * +%************************************************************************ + \begin{code} -dfs :: (v -> v -> Bool) - -> (v -> [v]) - -> ([v], [v]) - -> [v] - -> ([v], [v]) +data Tree a = Node a (Forest a) +type Forest a = [Tree a] -dfs eq r (vs,ns) [] = (vs,ns) -dfs eq r (vs,ns) (x:xs) - | any (eq x) vs = dfs eq r (vs,ns) xs - | True = case (dfs eq r (x:vs,[]) (r x)) of - (vs',ns') -> dfs eq r (vs',(x:ns')++ns) xs +mapTree :: (a -> b) -> (Tree a -> Tree b) +mapTree f (Node x ts) = Node (f x) (map (mapTree f) ts) \end{code} \begin{code} -findSCCs :: Ord key - => (vertex -> (key, Bag key)) -- Give key of vertex, and keys of thing's - -- immediate neighbours. It's ok for the - -- list to contain keys which don't correspond - -- to any vertex; they are ignored. - -> Bag vertex -- Stuff to be SCC'd - -> [SCC vertex] -- The union of all these is the original bag +instance Show a => Show (Tree a) where + showsPrec p t s = showTree t ++ s + +showTree :: Show a => Tree a -> String +showTree = drawTree . mapTree show -data SCC thing = AcyclicSCC thing - | CyclicSCC (Bag thing) +showForest :: Show a => Forest a -> String +showForest = unlines . map showTree -findSCCs v_info vs - = let - (keys, keys_of, edgess) = unzip3 (map do_vertex (bagToList vs)) - key_map = listToFM keys_of - edges = concat edgess +drawTree :: Tree String -> String +drawTree = unlines . draw - do_vertex v = (k, (k, (v, ok_ns)), ok_edges) - where - (k, ns) = v_info v - ok_ns = filter key_in_graph (bagToList ns) - ok_edges = map (\n->(k,n)) ok_ns +draw (Node x ts) = grp this (space (length this)) (stLoop ts) + where this = s1 ++ x ++ " " - key_in_graph n = maybeToBool (lookupFM key_map n) + space n = take n (repeat ' ') - the_sccs = stronglyConnComp (==) edges keys + stLoop [] = [""] + stLoop [t] = grp s2 " " (draw t) + stLoop (t:ts) = grp s3 s4 (draw t) ++ [s4] ++ rsLoop ts - cnv_sccs = map cnv_scc the_sccs + rsLoop [t] = grp s5 " " (draw t) + rsLoop (t:ts) = grp s6 s4 (draw t) ++ [s4] ++ rsLoop ts - cnv_scc [] = panic "findSCCs: empty component" - cnv_scc [k] | singlecycle k - = AcyclicSCC (get_vertex k) - cnv_scc ks = CyclicSCC (listToBag (map get_vertex ks)) + grp fst rst = zipWith (++) (fst:repeat rst) + + [s1,s2,s3,s4,s5,s6] = ["- ", "--", "-+", " |", " `", " +"] +\end{code} - singlecycle k = not (isIn "cycle" k (get_neighs k)) - get_vertex k = fst (lookupWithDefaultFM key_map vpanic k) - get_neighs k = snd (lookupWithDefaultFM key_map vpanic k) +%************************************************************************ +%* * +%* Depth first search +%* * +%************************************************************************ + +\begin{code} +type Set s = STArray s Vertex Bool - vpanic = panic "Digraph: vertix not found from key" - in - cnv_sccs +mkEmpty :: Bounds -> ST s (Set s) +mkEmpty bnds = newSTArray bnds False + +contains :: Set s -> Vertex -> ST s Bool +contains m v = readSTArray m v + +include :: Set s -> Vertex -> ST s () +include m v = writeSTArray m v True +\end{code} + +\begin{code} +dff :: Graph -> Forest Vertex +dff g = dfs g (vertices g) + +dfs :: Graph -> [Vertex] -> Forest Vertex +dfs g vs = prune (bounds g) (map (generate g) vs) + +generate :: Graph -> Vertex -> Tree Vertex +generate g v = Node v (map (generate g) (g!v)) + +prune :: Bounds -> Forest Vertex -> Forest Vertex +prune bnds ts = runST (mkEmpty bnds >>= \m -> + chop m ts) + +chop :: Set s -> Forest Vertex -> ST s (Forest Vertex) +chop m [] = return [] +chop m (Node v ts : us) + = contains m v >>= \visited -> + if visited then + chop m us + else + include m v >>= \_ -> + chop m ts >>= \as -> + chop m us >>= \bs -> + return (Node v as : bs) \end{code} + %************************************************************************ %* * -%* Topological sort * +%* Algorithms %* * %************************************************************************ -Topological sort fails if it finds any cycles, returning the offending cycles. +------------------------------------------------------------ +-- Algorithm 1: depth first search numbering +------------------------------------------------------------ + +\begin{code} +--preorder :: Tree a -> [a] +preorder (Node a ts) = a : preorderF ts + +preorderF :: Forest a -> [a] +preorderF ts = concat (map preorder ts) + +preOrd :: Graph -> [Vertex] +preOrd = preorderF . dff + +tabulate :: Bounds -> [Vertex] -> Table Int +tabulate bnds vs = array bnds (zipWith (,) vs [1..]) -If it succeeds, the result is a list of vertices, such that if there is -an edge from vertex A to vertex B then A occurs after B in the result list. +preArr :: Bounds -> Forest Vertex -> Table Int +preArr bnds = tabulate bnds . preorderF +\end{code} + + +------------------------------------------------------------ +-- Algorithm 2: topological sorting +------------------------------------------------------------ \begin{code} -topologicalSort :: (vertex->vertex->Bool) -> [Edge vertex] -> [vertex] - -> MaybeErr [vertex] -- Success: the sorted list - [[vertex]] -- Failure: the cycles +--postorder :: Tree a -> [a] +postorder (Node a ts) = postorderF ts ++ [a] -topologicalSort eq edges vertices - = case (stronglyConnComp eq edges vertices) of { sccs -> - case (partition (is_cyclic edges) sccs) of { (cycles, singletons) -> - if null cycles - then Succeeded [ v | [v] <- singletons ] - else Failed cycles - }} - where - is_cyclic es [] = panic "is_cyclic: empty component" - is_cyclic es [v] = (v,v) `elem` es - is_cyclic es vs = True +postorderF :: Forest a -> [a] +postorderF ts = concat (map postorder ts) + +postOrd :: Graph -> [Vertex] +postOrd = postorderF . dff + +topSort :: Graph -> [Vertex] +topSort = reverse . postOrd +\end{code} + + +------------------------------------------------------------ +-- Algorithm 3: connected components +------------------------------------------------------------ + +\begin{code} +components :: Graph -> Forest Vertex +components = dff . undirected - elem (x,y) [] = False - elem z@(x,y) ((a,b):cs) = (x `eq` a && y `eq` b) || z `elem` cs +undirected :: Graph -> Graph +undirected g = buildG (bounds g) (edges g ++ reverseE g) \end{code} + + +-- Algorithm 4: strongly connected components + +\begin{code} +scc :: Graph -> Forest Vertex +scc g = dfs g (reverse (postOrd (transposeG g))) +\end{code} + + +------------------------------------------------------------ +-- Algorithm 5: Classifying edges +------------------------------------------------------------ + +\begin{code} +tree :: Bounds -> Forest Vertex -> Graph +tree bnds ts = buildG bnds (concat (map flat ts)) + where + flat (Node v rs) = [ (v, w) | Node w us <- ts ] ++ + concat (map flat ts) + +back :: Graph -> Table Int -> Graph +back g post = mapT select g + where select v ws = [ w | w <- ws, post!v < post!w ] + +cross :: Graph -> Table Int -> Table Int -> Graph +cross g pre post = mapT select g + where select v ws = [ w | w <- ws, post!v > post!w, pre!v > pre!w ] + +forward :: Graph -> Graph -> Table Int -> Graph +forward g tree pre = mapT select g + where select v ws = [ w | w <- ws, pre!v < pre!w ] \\ tree!v +\end{code} + + +------------------------------------------------------------ +-- Algorithm 6: Finding reachable vertices +------------------------------------------------------------ + +\begin{code} +reachable :: Graph -> Vertex -> [Vertex] +reachable g v = preorderF (dfs g [v]) + +path :: Graph -> Vertex -> Vertex -> Bool +path g v w = w `elem` (reachable g v) +\end{code} + + +------------------------------------------------------------ +-- Algorithm 7: Biconnected components +------------------------------------------------------------ + +\begin{code} +bcc :: Graph -> Forest [Vertex] +bcc g = (concat . map bicomps . map (do_label g dnum)) forest + where forest = dff g + dnum = preArr (bounds g) forest + +do_label :: Graph -> Table Int -> Tree Vertex -> Tree (Vertex,Int,Int) +do_label g dnum (Node v ts) = Node (v,dnum!v,lv) us + where us = map (do_label g dnum) ts + lv = minimum ([dnum!v] ++ [dnum!w | w <- g!v] + ++ [lu | Node (u,du,lu) xs <- us]) + +bicomps :: Tree (Vertex,Int,Int) -> Forest [Vertex] +bicomps (Node (v,dv,lv) ts) + = [ Node (v:vs) us | (l,Node vs us) <- map collect ts] + +collect :: Tree (Vertex,Int,Int) -> (Int, Tree [Vertex]) +collect (Node (v,dv,lv) ts) = (lv, Node (v:vs) cs) + where collected = map collect ts + vs = concat [ ws | (lw, Node ws us) <- collected, lw