Use an abstract finite sequence of integers, initially empty. In the following trait, comments are the mathematical specification; means the abstract state on entry, and result means the returned value.
trait ReversableBuffer {
  // Abstract state s: finite sequence of Int, initially [].

  // Pre: true. Post: s = s0 ++ [x].
  def append(x: Int): Unit

  // Pre: true. Post: s = [x] ++ s0.
  def prepend(x: Int): Unit

  // Pre: 0 <= i < length(s0).
  // Post: result = s0 !! i,
  //       s = take i s0 ++ drop (i+1) s0.
  def get(i: Int): Int

  // Pre: true. Post: s = reverse(s0).
  def rev: Unit
}
The postcondition of get includes removal: it is not merely indexed reading. In particular,
Repeated equal values elsewhere in the sequence remain present. List concatenation, indexing and list reversal in the specification describe abstract behavior without committing to a physical representation.
Place these methods inside the LLBuffer class. The two private insertion methods operate on physical endpoints; the public methods interpret logical endpoints using the reversal flag.
private def addFirst(x: Int): Unit = {
  val q = new Node(x)
  q.next = first
  if (first == null) last = q else first.prev = q
  first = q
  size += 1
}

private def addLast(x: Int): Unit = {
  val q = new Node(x)
  q.prev = last
  if (last == null) first = q else last.next = q
  last = q
  size += 1
}

def append(x: Int): Unit = {
  if (backwards) addFirst(x) else addLast(x)
}

def prepend(x: Int): Unit = {
  if (backwards) addLast(x) else addFirst(x)
}

def get(i: Int): Int = {
  require(0 <= i && i < size)
  val j = if (backwards) size - 1 - i else i
  var q: Node = null
  if (j <= size - 1 - j) {
    q = first
    var k = 0
    while (k < j) { q = q.next; k += 1 }
  } else {
    q = last
    var k = size - 1
    while (k > j) { q = q.prev; k -= 1 }
  }
  val x = q.value
  if (q.prev == null) first = q.next else q.prev.next = q.next
  if (q.next == null) last = q.prev else q.next.prev = q.prev
  q.prev = null
  q.next = null
  size -= 1
  x
}

def rev: Unit = { backwards = !backwards }
In the forward traversal, the loop invariant is that q is physical node , with ; its loop variant is . In the backward traversal, q is physical node , with ; its loop variant is . Thus both locate physical index , which is exactly logical index under the abstraction function.
Deletion bypasses the chosen linked list node in both directions. Deleting the first or last linked list node updates the corresponding endpoint; deleting the only linked list node sets both endpoints to null. The surviving values keep their physical relative order, so the abstraction function gives precisely the required logical deletion. Each insertion preserves reciprocal links and adds its value at the physical end corresponding to the required logical end. Toggling the flag changes to its list reversal without moving any linked list nodes. Consequently
These are worst-case time complexity bounds in the constant-cost pointer model; total storage is and each operation uses constant auxiliary space.
Write the segment as , where and . The desired array rotation is . Reverse each block, then the whole segment:
PROCEDURE rotate(i, n, k: INTEGER);
BEGIN
  IF (k = 0) OR (k = n) THEN RETURN END;
  reverse(i, n-k);
  reverse(i+n-k, k);
  reverse(i, n)
END rotate;
The state changes are , using the list reversal identity supplied in the paper and reversal being an involution. Three reversals implement the right rotation in time and auxiliary space. The initial return covers empty and identity rotations.