/// Computes the SES (shortest edit script), i.e. the shortest sequence of diffs (`Free>`) for two arrays of `Term`s which would suffice to transform `a` into `b`. /// /// This is computed w.r.t. an `equals` function, which computes the equality of leaf nodes within terms, and a `recur` function, which produces diffs representing matched-up terms. public func SES(a: [Term], _ b: [Term], cost: Free> -> Int, recur: (Term, Term) -> Free>?) -> [Free>] { typealias Diff = Free> if a.isEmpty { return b.map { .Insert($0) } } if b.isEmpty { return a.map { .Delete($0) } } func cons(diff: Diff, rest: Memo>) -> Stream<(Diff, Int)> { return .Cons((diff, cost(diff) + costOfStream(rest)), rest) } func costOfStream(stream: Memo>) -> Int { return stream.value.first?.1 ?? 0 } func min(a: A, _ rest: A..., _ isLessThan: (A, A) -> Bool) -> A { return rest.reduce(a, combine: { isLessThan($0, $1) ? $0 : $1 }) } // A matrix whose values are streams representing paths through the edit graph, carrying both the diff & the cost of the remainder of the path. var matrix: Matrix>! matrix = Matrix(width: a.count + 1, height: b.count + 1) { i, j in // Some explanation is warranted: // // 1. `matrix` captures itself during construction, because each vertex in the edit graph depends on other vertices. This is safe, because a) `Matrix` populates its fields lazily, and b) vertices only depend on those vertices downwards and rightwards of them. // // 2. `matrix` is sized bigger than `a.count` x `b.count`. This is safe, because a) we only get a[i]/b[j] when right/down are non-nil (respectively), and b) right/down are found by looking up elements (i + 1, j) & (i, j + 1) in the matrix, which returns `nil` when out of bounds. So we only access a[i] and b[j] when i and j are in bounds. let right = matrix[i + 1, j] let down = matrix[i, j + 1] let diagonal = matrix[i + 1, j + 1] if let right = right, down = down, diagonal = diagonal { let here = recur(a[i], b[j]) // If the diff at this vertex is zero-cost, we’re not going to find a cheaper one either rightwards or downwards. We can therefore short-circuit selecting the best outgoing edge and save ourselves evaluating the entire row rightwards and the entire column downwards from this point. // // Thus, in the best case (two equal sequences), we now complete in O(n + m). However, this optimization only applies to equalities at the beginning of the edit graph; once inequalities are encountered, the remainder of the diff is effectively O(nm). if let here = here where cost(here) == 0 { return cons(here, rest: diagonal) } let right = (right, Diff.Delete(a[i]), costOfStream(right)) let down = (down, Diff.Insert(b[j]), costOfStream(down)) let diagonal = here.map { (diagonal, $0, costOfStream(diagonal)) } // nominate the best edge to continue along, not considering diagonal if `recur` returned `nil`. let (best, diff, _) = diagonal .map { min($0, right, down) { $0.2 < $1.2 } } ?? min(right, down) { $0.2 < $1.2 } return cons(diff, rest: best) } // right extent of the edit graph; can only move down if let down = down { return cons(Diff.Insert(b[j]), rest: down) } // bottom extent of the edit graph; can only move right if let right = right { return cons(Diff.Delete(a[i]), rest: right) } // bottom-right corner of the edit graph return Stream.Nil } return Array(matrix[0, 0]!.value.map { diff, _ in diff }) } import Memo import Prelude import Stream