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Random search in graph

The graph is represented by a pair (vertices, successor)

The algorithm is a ministep of a random search in the graph. It is generic to any search strategy.
This completeness proof is adapted from Dowek and Munoz and is fully automatic.

module RandomSearch
  use import int.Int
  use import list.List
  use import list.Append
  use import list.Mem as L
  use import init_graph.GraphSetSucc
  use import list.NumOcc

  predicate white_vertex (x: vertex) (v: set vertex) =
    not (mem x v)

  predicate whitepath (x: vertex) (l: list vertex) (z: vertex) (v: set vertex) =
    path x l z /\ (forall y. L.mem y l -> white_vertex y v) /\ white_vertex z v

  lemma path_decomp_with_last_occ:
    forall x z l1 l2 y. path x (l1 ++ (Cons y l2)) z -> y <> z -> exists l3 l4. l1 ++ (Cons y l2) = l3 ++ (Cons y l4) /\ not L.mem y l4

  lemma whitepath_decomp_with_last_occ:
    forall x z l1 l2 y v. whitepath x (l1 ++ (Cons y l2)) z v -> y <> z -> exists l. whitepath y (Cons y l) z v /\ not L.mem y l

  lemma whitepath_enhance:
    forall x z l v. whitepath x (Cons x l) z v -> x <> z -> not L.mem x l -> exists y l'. edge x y /\ whitepath y l' z (add x v)


let rec random_search r v = 
  requires {subset r vertices }
  requires {subset v vertices }
  ensures {subset v result}
  ensures {forall z y l. mem y r -> whitepath y l z v -> mem z (diff result v)}

  if is_empty r then v else
  let x = choose r in
  let r' = remove x r in
  if mem x v then random_search r' v else
  let v' = random_search (union r' (successors x)) (add x v) in
  (*----------- whitepath_nodeflip -----------*)
   assert {forall z y l. mem y r -> whitepath y l z v -> z <> x ->
      whitepath y l z (add x v) \/
      exists x' l'. mem x' (successors x) /\ whitepath x' l' z (add x v) } ;

let random_search_main (roots: set vertex) =
  requires {subset roots vertices}
  ensures {forall z y l. mem y roots -> path y l z -> mem z result}
  random_search roots empty 



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