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Traversing trees

In many situations it is required to traverse all the nodes in a rooted tree. This can be done in many ways, depending in which order the nodes are visited:

  • preorder traversal first visits the current node and then (recursively) its children one-by-one.

  • inorder traversal, especially on binary trees, first (recursively) visits the left child, then the node itself and then (recursively) the right child.

  • postorder traversal first visits (recursively) all the children one-by-one and then the node itself.

  • level order traversal, which is not so common, visits the nodes level-by-level left-to-right starting from the root node.

In pseudo-code, we can express each of the traversal methods as follows. Observe the use of queues in the level order traversal.

traverse-preorder(tree \( T \)): def traverse(\( n \)): visit(\( n \)) for each child \( c \) of \( n \): traverse(\( c \)) traverse(\( \TRootOf{T} \))
traverse-inorder(tree \( T \)): def traverse(\( n \)): traverse(\( \TLChildOf{n} \)) visit(\( n \)) traverse(\( \TRChildOf{n} \)) traverse(\( \TRootOf{T} \))
traverse-postorder(tree \( T \)): def traverse(\( n \)): for each child \( c \) of \( n \): traverse(\( c \)) visit(\( n \)) traverse(\( \TRootOf{T} \))
traverse-levelorder(tree \( T \)): \( level \Asgn \)new Queue \( \PEnqueue{level}{\TRootOf{T}} \) while \( level \) is non-empty: \( nextLevel \Asgn \)new Queue while \( level \) is non-empty: \( n \Asgn \PDequeue{level} \) visit(\( n \)) for each child \( c \) of \( n \): \( \PEnqueue{nextLevel}{c} \) \( level \Asgn nextLevel \)

Example

The visiting orders for the nodes in the tree shown below are as follows.

  • ​ Preorder: \(c,d,e,g,f,a,b,h\)

  • ​ Inorder: \(g,e,f,d,c,b,a,h\)

  • ​ Postorder: \(g,f,e,d,b,h,a,c\)

  • ​ Level order: \(c,d,a,e,b,h,g,f\)

_images/trees-binary-6.png

In practise, tree traversal functions may mix orders.

Example

The following Scala code shows how to print arithmetic expressions in the prefix, infix, and postfix notations.

abstract class Expr {
  def prefixStr: String
  def infixStr: String
  def postfixStr: String
}
case class Negate(expr: Expr) extends Expr {
  def prefixStr: String = "Negate("+expr.prefixStr+")"
  def infixStr: String = "-"+expr.infixStr
  def postfixStr: String = expr.postfixStr + " -"
}
case class Add(left: Expr, right: Expr) extends Expr {
  def prefixStr: String = "Add("+left.prefixStr+","+right.prefixStr+")"
  def infixStr: String = "("+left.infixStr+"+"+right.infixStr+")"
  def postfixStr: String = left.postfixStr+" "+right.postfixStr+" +"
}
case class Multiply(left: Expr, right: Expr) extends Expr {
  def prefixStr: String = "Multiply("+left.prefixStr+","+right.prefixStr+")"
  def infixStr: String = "("+left.infixStr+"*"+right.infixStr+")"
  def postfixStr: String = left.postfixStr + " "+ right.postfixStr + " *"
}
case class Var(name: String) extends Expr {
  def prefixStr: String = "Var(\""+name+"\")"
  def infixStr: String = name
  def postfixStr: String = name
}
case class Num(value: Double) extends Expr {
  def prefixStr: String = "Num("+value.toString+")"
  def infixStr: String = value.toString
  def postfixStr: String = value.toString
}

val e = Negate(Add(Multiply(Num(2.0),Var("x")),Var("y")))
println(e.prefixStr)
println(e.infixStr)
println(e.postfixStr)

The parse tree corresponding to the expression \(-(2.0x + y)\) is obtained with val e = Negate(Add(Multiply(Num(2.0),Var(“x”)),Var(“y”))) is shown below.

_images/exprs-objects.jpg
  • e.prefixStr produces Negate(Add(Multiply(Num(2.0),Var(“x”)),Var(“y”))).

  • e.infixStr produces -((2.0*x)+y).

  • e.postfixStr gives 2.0 x * y + -.

    The postfix notation does not need parentheses and it is easy to read and evaluate from the textual representation by using a stack (see e.g. this article).