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HTML::Tree::AboutTreesUser Contributed Perl DocumentaHTML::Tree::AboutTrees(3)

       HTML::Tree::AboutTrees -- article on tree-shaped data structures in

	 # This an article, not a module.

       The following article by Sean M. Burke first appeared in The Perl Jour‐
       nal #18 and is copyright 2000 The Perl Journal. It appears courtesy of
       Jon Orwant and The Perl Journal.	 This document may be distributed
       under the same terms as Perl itself.

       -- Sean M. Burke

	   "AaaAAAaauugh!  Watch out for that tree!"
	     -- George of the Jungle theme

       Perl's facility with references, combined with its automatic management
       of memory allocation, makes it straightforward to write programs that
       store data in structures of arbitrary form and complexity.

       But I've noticed that many programmers, especially those who started
       out with more restrictive languages, seem at home with complex but uni‐
       form data structures -- N-dimensional arrays, or more struct-like
       things like hashes-of-arrays(-of-hashes(-of-hashes), etc.) -- but
       they're often uneasy with buliding more freeform, less tabular struc‐
       tures, like tree-shaped data structures.

       But trees are easy to build and manage in Perl, as I'll demonstrate by
       showing off how the HTML::Element class manages elements in an HTML
       document tree, and by walking you through a from-scratch implementation
       of game trees.  But first we need to nail down what we mean by a

       Socratic Dialogues: "What is a Tree?"

       My first brush with tree-shaped structures was in linguistics classes,
       where tree diagrams are used to describe the syntax underlying natural
       language sentences.  After learning my way around those trees, I
       started to wonder -- are what I'm used to calling "trees" the same as
       what programmers call "trees"?  So I asked lots of helpful and patient
       programmers how they would define a tree.  Many replied with a answer
       in jargon that they could not really explain (understandable, since
       explaining things, especially defining things, is harder than people

	   -- So what is a "tree", a tree-shaped data structure?

	   -- A tree is a special case of an acyclic directed graph!

	   -- What's a "graph"?

	   -- Um... lines... and... you draw it... with... arcs! nodes!	 um...

       The most helpful were folks who couldn't explain directly, but with
       whom I could get into a rather Socratic dialog (where I asked the half-
       dim half-earnest questions), often with much doodling of illustra‐

       Question: so what's a tree?

       Answer: A tree is a collection of nodes that are linked together in a,
       well, tree-like way!  Like this [drawing on a napkin]:

	   / \
	  B   C
	    / ⎪ \
	   D  E	 F

       Q: So what do these letters represent?

       A: Each is a different node, a bunch of data.  Maybe C is a bunch of
       data that stores a number, maybe a hash table, maybe nothing at all
       besides the fact that it links to D, E, and F (which are other nodes).

       Q: So what're the lines between the nodes?

       A: Links.  Also called "arcs".  They just symbolize the fact that each
       node holds a list of nodes it links to.

       Q: So what if I draw nodes and links, like this...

	    B -- E
	   / \	/ \
	  A   C
	   \ /

       Is that still a tree?

       A: No, not at all.  There's a lot of un-treelike things about that.
       First off, E has a link coming off of it going into nowhere.  You can't
       have a link to nothing -- you can only link to another node.  Second
       off, I don't know what that sideways link between B and E means...

       Q: Okay, let's work our way up from something simpler.  Is this a


       A: Yes, I suppose.  It's a tree of just one node.

       Q: And how about...



       A: No, you can't just have nodes floating there, unattached.

       Q: Okay, I'll link A and B.  How's this?


       A: Yup, that's a tree.  There's a node A, and a node B, and they're

       Q: How is that tree any different from this one...?


       A: Well, in both cases A and B are linked.  But it's in a different

       Q: Direction?  What does the direction mean?

       A: Well, it depends what the tree represents.  If it represents a cate‐
       gorization, like this:

	      /	   ⎪	\
	  orange  lemon	 kumquat ...

       then you mean to say that oranges, lemons, kumquats, etc., are a kind
       of citrus.  But if you drew it upside down, you'd be saying, falsely,
       that citrus is a kind of kumquat, a kind of lemon, and a kind of
       orange.	If the tree represented cause-and-effect (or at least what
       situations could follow others), or represented what's a part of what,
       you wouldn't want to get those backwards, either.  So with the nodes
       you draw together on paper, one has to be over the other, so you can
       tell which way the relationship in the tree works.

       Q:  So are these two trees the same?

	    A	       A
	   / \	      / \
	  B   C	     B	 \

       A: Yes, although by convention we often try to line up things in the
       same generation, like it is in the diagram on the left.

       Q: "generation"?	 This is a family tree?

       A: No, not unless it's a family tree for just yeast cells or something
       else that reproduces asexually.	But for sake of having lots of terms
       to use, we just pretend that links in the tree represent the "is a
       child of" relationship, instead of "is a kind of" or "is a part of", or
       "could result from", or whatever the real relationship is.  So we get
       to borrow a lot of kinship words for describing trees -- B and C are
       "children" (or "daughters") of A; A is the "parent" (or "mother") of B
       and C.  Node C is a "sibling" (or "sister") of node C; and so on, with
       terms like "descedants" (a node's children, children's children, etc.),
       and "generation" (all the nodes at the same "level" in the tree, i.e.,
       are either all grandchildren of the top node, or all great-grand-chil‐
       dren, etc.), and "lineage" or "ancestors" (parents, and parent's par‐
       ents, etc., all the way to the topmost node).

       So then we get to express rules in terms like "A node cannot have more
       than one parent", which means that this is not a valid tree:

	  / \
	 B   C
	  \ /

       And: "A node can't be its own parent", which excludes this looped-up

	  A  ⎪

       Or, put more generally: "A node can't be its own ancestor", which
       excludes the above loop, as well as the one here:

	    Z  ⎪
	   /   ⎪
	  A    ⎪
	 / \   ⎪
	B   C  ⎪

       That tree is excluded because A is a child of Z, and Z is a child of C,
       and C is a child of A, which means A is its own great-grandparent.  So
       this whole network can't be a tree, because it breaks the sort of
       meta-rule: once any node in the supposed tree breaks the rules for
       trees, you don't have a tree anymore.

       Q: Okay, now, are these two trees the same?

	    A	      A
	  / ⎪ \	    / ⎪ \
	 B  C  D   D  C	 B

       A: It depends whether you're basing your concept of trees on each node
       having a set (unordered list) of children, or an (ordered) list of
       children.  It's a question of whether ordering is important for what
       you're doing.  With my diagram of citrus types, ordering isn't impor‐
       tant, so these tree diagrams express the same thing:

	      /	   ⎪	\
	  orange  lemon	 kumquat

	      /	    ⎪	 \
	  kumquat  orange  lemon

       because it doesn't make sense to say that oranges are "before" or
       "after" kumquats in the whole botanical scheme of things.  (Unless, of
       course, you are using ordering to mean something, like a degree of
       genetic similarity.)

       But consider a tree that's a diagram of what steps are comprised in an
       activity, to some degree of specificity:

		  make tea
		/    ⎪	   \
	  pour	   infuse   serve
	hot water    / \
       in cup/pot  /	 \
		  add	  let
		  tea	  sit

       This means that making tea consists of putting hot water in a cup or
       put, infusing it (which itself consists of adding tea leaves and let‐
       ting it sit), then serving it -- in that order.	If you serve an empty
       dry pot (sipping from empty cups, etc.), let it sit, add tea leaves,
       and pour in hot water, then what you're doing is performance art, not
       tea preparation:

	       /    ⎪	  \
	  serve	  infuse    pour
		   / \	     hot water
		 /     \      in cup/pot
		let	add
		sit	tea

       Except for my having renamed the root, this tree is the same as the
       making-tea tree as far as what's under what, but it differs in order,
       and what the tree means makes the order important.

       Q: Wait -- "root"?  What's a root?

       A: Besides kinship terms like "mother" and "daugher", the jargon for
       tree parts also has terms from real-life tree parts:  the part that
       everything else grows from is called the root; and nodes that don't
       have nodes attached to them (i.e., childless nodes) are called

       Q: But you've been drawing all your trees with the root at the top and
       leaves at the bottom.

       A: Yes, but for some reason, that's the way everyone seems to think of
       trees.  They can draw trees as above; or they can draw them sort of
       sideways with indenting representing what nodes are children of what:

	 * make tea
	    * pour hot water in cup/pot
	    * infuse
	       * add tea leaves
	       * let sit
	    * serve

       ...but folks almost never seem to draw trees with the root at the bot‐
       tom.  So imagine it's based on spider plant in a hanging pot.  Unfortu‐
       nately, spider plants aren't botanically trees, they're plants; but
       "spider plant diagram" is rather a mouthful, so let's just call them

       Trees Defined Formally

       In time, I digested all these assorted facts about programmers' ideas
       of trees (which turned out to be just a more general case of linguistic
       ideas of trees) into a single rule:

       * A node is an item that contains ("is over", "is parent of", etc.)
       zero or more other nodes.

       From this you can build up formal definitions for useful terms, like

       * A node's descendants are defined as all its children, and all their
       children, and so on.  Or, stated recursively: a node's descendants are
       all its children, and all its children's descendants.  (And if it has
       no children, it has no descendants.)

       * A node's ancestors consist of its parent, and its parent's parent,
       etc, up to the root.  Or, recursively: a node's ancestors consist of
       its parent and its parent's ancestors.  (If it has no parent, it has no

       * A tree is a root node and all the root's descendants.

       And you can add a proviso or two to clarify exactly what I impute to
       the word "other" in "other nodes":

       * A node cannot contain itself, or contain any node that contains it,
       etc.  Looking at it the other way: a node cannot be its own parent or

       * A node can be root (i.e., no other node contains it) or can be con‐
       tained by only one parent; no node can be the child of two or more par‐

       Add to this the idea that children are sometimes ordered, and sometimes
       not, and that's about all you need to know about defining what a tree
       is.  From there it's a matter of using them.

       Markup Language Trees: HTML-Tree

       While not all markup languages are inherently tree-like, the best-known
       family of markup languages, HTML, SGML, and XML, are about as tree-like
       as you can get.	In these languages, a document consists of elements
       and character data in a tree structure where there is one root element,
       and elements can contain either other elements, or character data.

	   Footnote: For sake of simplicity, I'm glossing over comments (<!--
	   ... -->), processing instructions (<?xml version='1.0'>), and dec‐
	   larations (<!ELEMENT ...>, <!DOCTYPE ...>).	And I'm not bothering
	   to distinguish entity references (<, @) or CDATA sections
	   (<![CDATA[ ...]]>) from normal text.

       For example, consider this HTML document:

	 <html lang="en-US">
	       Blank Document!
	   <body bgcolor="#d010ff">
	     I've got
	       something to saaaaay

       I've indented this to point out what nodes (elements or text items) are
       children of what, with each node on a line of its own.

       The HTML::TreeBuilder module (in the CPAN distribution HTML-Tree) does
       the work of taking HTML source and building in memory the tree that the
       document source represents.

	   Footnote: it requires the HTML::Parser module, which tokenizes the
	   source -- i.e., identifies each tag, bit of text, comment, etc.

       The trees structures that it builds represent bits of text with normal
       Perl scalar string values; but elements are represented with objects --
       that is, chunks of data that belong to a class (in this case,
       HTML::Element), a class that provides methods (routines) for accessing
       the pieces of data in each element, and otherwise doing things with
       elements.  (See my article in TPJ#17 for a quick explanation of
       objects, the POD document "perltoot" for a longer explanation, or
       Damian Conway's excellent book Object-Oriented Perl for the full

       Each HTML::Element object contains a number of pieces of data:

       * its element name ("html", "h1", etc., accessed as $element->tag)

       * a list of elements (or text segments) that it contains, if any
       (accessed as $element->content_list or $element->content, depending on
       whether you want a list, or an arrayref)

       * what element, if any, contains it (accessed as $element->parent)

       * and any SGML attributes that the element has, such as "lang="en-US"",
       "align="center"", etc. (accessed as $element->attr('lang'), $ele‐
       ment->attr('center'), etc.)

       So, for example, when HTML::TreeBuilder builds the tree for the above
       HTML document source, the object for the "body" element has these
       pieces of data:

	* element name: "body"
	* nodes it contains:
	   the string "I've got "
	   the object for the "em" element
	   the string "!"
	* its parent:
	   the object for the "html" element
	* bgcolor: "#d010ff"

       Now, once you have this tree of objects, almost anything you'd want to
       do with it starts with searching the tree for some bit of information
       in some element.

       Accessing a piece of information in, say, a hash of hashes of hashes,
       is straightforward:


       because you know that all data points in that structure are accessible
       with that syntax, but with just different keys.	Now, the "em" element
       in the above HTML tree does happen to be accessible as the root's child
       #1's child #1:


       But with trees, you typically don't know the exact location (via
       indexes) of the data you're looking for.	 Instead, finding what you
       want will typically involve searching through the tree, seeing if every
       node is the kind you want.  Searching the whole tree is simple enough
       -- look at a given node, and if it's not what you want, look at its
       children, and so on.  HTML-Tree provides several methods that do this
       for you, such as "find_by_tag_name", which returns the elements (or the
       first element, if called in scalar context) under a given node (typi‐
       cally the root) whose tag name is whatever you specify.

       For example, that "em" node can be found as:

	 my $that_em = $root->find_by_tag_name('em');

       or as:

	 @ems = $root->find_by_tag_name('em');
	  # will only have one element for this particular tree

       Now, given an HTML document of whatever structure and complexity, if
       you wanted to do something like change every



	   <em class="funky"> <b>[-</b> stuff <b>-]</b> </em>

       the first step is to frame this operation in terms of what you're doing
       to the tree.  You're changing this:


       to this:

	   /  ⎪	 \
	  b  ...   b
	  ⎪	   ⎪
	 "[-"	  "-]"

       In other words, you're finding all elements whose tag name is "em",
       setting its class attribute to "funky", and adding one child to the
       start of its content list -- a new "b" element whose content is the
       text string "[-" -- and one to the end of its content list -- a new "b"
       element whose content is the text string "-]".

       Once you've got it in these terms, it's just a matter of running to the
       HTML::Element documentation, and coding this up with calls to the
       appropriate methods, like so:

	 use HTML::Element 1.53;
	 use HTML::TreeBuilder 2.96;
	 # Build the tree by parsing the document
	 my $root = HTML::TreeBuilder->new;
	 $root->parse_file('whatever.html'); # source file

	 # Now make new nodes where needed
	 foreach my $em ($root->find_by_tag_name('em')) {
	   $em->attr('class', 'funky'); # Set that attribute

	   # Make the two new B nodes
	   my $new1 = HTML::Element->new('b');
	   my $new2 = HTML::Element->new('b');
	   # Give them content (they have none at first)

	   # And put 'em in place!
	  "<!-- Looky see what I did! -->\n",
	  $root->as_HTML(), "\n";

       The class HTML::Element provides just about every method I can image
       you needing, for manipulating trees made of HTML::Element objects.
       (And what it doesn't directly provide, it will give you the components
       to build it with.)

       Building Your Own Trees

       Theoretically, any tree is pretty much like any other tree, so you
       could use HTML::Element for anything you'd ever want to do with tree-
       arranged objects.  However, as its name implies, HTML::Element is basi‐
       cally for HTML elements; it has lots of features that make sense only
       for HTML elements (like the idea that every element must have a
       tag-name).  And it lacks some features that might be useful for general
       applications -- such as any sort of checking to make sure that you're
       not trying to arrange objects in a non-treelike way.  For a general-
       purpose tree class that does have such features, you can use
       Tree::DAG_Node, also available from CPAN.

       However, if your task is simple enough, you might find it overkill to
       bother using Tree::DAG_Node.  And, in any case, I find that the best
       way to learn how something works is to implement it (or something like
       it, but simpler) yourself.  So I'll here discuss how you'd implement a
       tree structure, without using any of the existing classes for tree

       Implementation: Game Trees for Alak

       Suppose that the task at hand is to write a program that can play
       against a human opponent at a strategic board game (as opposed to a
       board game where there's an element of chance).	For most such games, a
       "game tree" is an essential part of the program (as I will argue,
       below), and this will be our test case for implementing a tree struc‐
       ture from stratch.

       For sake of simplicity, our game is not chess or backgammon, but
       instead a much simpler game called Alak.	 Alak was invented by the
       mathematician A. K.  Dewdney, and described in his 1984 book Plani‐
       verse. The rules of Alak are simple:

	   Footnote: Actually, I'm describing only my interpetation of the
	   rules Dewdney describes in Planiverse.  Many other interpretations
	   are possible.

       * Alak is a two-player game played on a one-dimensional board with
       eleven slots on it.  Each slot can hold at most one piece at a time.
       There's two kinds of pieces, which I represent here as "x" and "o" --
       x's belong to one player (called X), o's to the other (called O).

       * The initial configuration of the board is:


       For sake of the article, the slots are numbered from 1 (on the left) to
       11 (on the right), and X always has the first move.

       * The players take turns moving.	 At each turn, each player can move
       only one piece, once.  (This unlike checkers, where you move one piece
       per move but get to keep moving it if you jump an your opponent's
       piece.) A player cannot pass up on his turn.  A player can move any one
       of his pieces to the next unoccupied slot to its right or left, which
       may involve jumping over occupied slots.	 A player cannot move a piece
       off the side of the board.

       * If a move creates a pattern where the opponent's pieces are sur‐
       rounded, on both sides, by two pieces of the mover's color (with no
       intervening unoccupied blank slot), then those surrounded pieces are
       removed from the board.

       * The goal of the game is to remove all of your opponent's pieces, at
       which point the game ends.  Removing all-but-one ends the game as well,
       since the opponent can't surround you with one piece, and so will
       always lose within a few moves anyway.

       Consider, then, this rather short game where X starts:

	   ^	     Move 1: X moves from 3 (shown with caret) to 5
		      (Note that any of X's pieces could move, but
		      that the only place they could move to is 5.)
		 ^   Move 2: O moves from 9 to 7.
	    ^	     Move 3: X moves from 4 to 6.
		  ^  Move 4: O (stupidly) moves from 10 to 9.
	     ^	     Move 5: X moves from 5 to 10, making the board
		     "xx___xoooxo".  The three o's that X just
		     surrounded are removed.
		     O has only one piece, so has lost.

       Now, move 4 could have gone quite the other way:

		     Move 4: O moves from 8 to 4, making the board
		     "xx_oxxo__oo".  The surrounded x's are removed.
	 ^	     Move 5: X moves from 1 to 2.
	       ^     Move 6: O moves from 7 to 6.
	  ^	     Move 7: X moves from 2 to 5, removing the o at 4.
		     ...and so on.

       To teach a computer program to play Alak (as player X, say), it needs
       to be able to look at the configuration of the board, figure out what
       moves it can make, and weigh the benefit or costs, immediate or even‐
       tual, of those moves.

       So consider the board from just before move 3, and figure all the pos‐
       sible moves X could make.  X has pieces in slots 1, 2, 4, and 5.	 The
       leftmost two x's (at 1 and 2) are up against the end of the board, so
       they can move only right.  The other two x's (at 4 and 5) can move
       either right or left:

	 Starting board: xx_xx_oo_oo
	  moving 1 to 3 gives _xxxx_oo_oo
	  moving 2 to 3 gives x_xxx_oo_oo
	  moving 4 to 3 gives xxx_x_oo_oo
	  moving 5 to 3 gives xxxx__oo_oo
	  moving 4 to 6 gives xx__xxoo_oo
	  moving 5 to 6 gives xx_x_xoo_oo

       For the computer to decide which of these is the best move to make, it
       needs to quantify the benefit of these moves as a number -- call that
       the "payoff".  The payoff of a move can be figured as just the number
       of x pieces removed by the most recent move, minus the nubmer of o
       pieces removed by the mots recent move.	(It so happens that the rules
       of the game mean that no move can delete both o's and x's, but the for‐
       mula still applies.)  Since none of these moves removed any pieces, all
       these moves have the same immediate payoff: 0.

       Now, we could race ahead and write an Alak-playing program that could
       use the immediate payoff to decide which is the best move to make.  And
       when there's more than one best move (as here, where all the moves are
       equally good), it could choose randomly between the good alternatives.
       This strategy is simple to implement; but it makes for a very dumb pro‐
       gram.  Consider what O's response to each of the potential moves
       (above) could be.  Nothing immediately suggests itself for the first
       four possibilities (X having moved something to position 3), but either
       of the last two (illustrated below) are pretty perilous, because in
       either case O has the obvious option (which he would be foolish to pass
       up) of removing x's from the board:

	     ^	      X moves 4 to 6.
		 ^    O moves 8 to 4, giving "xx_oxxo__oo".  The two
		      surrounded x's are removed.


	      ^	      X moves 5 to 6.
		 ^    O moves 8 to 5, giving "xx_xoxo__oo".  The one
		      surrounded x is removed.

       Both contingencies are quite bad for X -- but this is not captured by
       the fact that they start out with X thinking his move will be harmless,
       having a payoff of zero.

       So what's needed is for X to think more than one step ahead -- to con‐
       sider not merely what it can do in this move, and what the payoff is,
       but to consider what O might do in response, and the payoff of those
       potential moves, and so on with X's possible responses to those cases
       could be.  All these possibilities form a game tree -- a tree where
       each node is a board, and its children are successors of that node --
       i.e., the boards that could result from every move possible, given the
       parent's board.

       But how to represent the tree, and how to represent the nodes?

       Well, consider that a node holds several pieces of data:

       1) the configuration of the board, which, being nice and simple and
       one-dimensional, can be stored as just a string, like "xx_xx_oo_oo".

       2) whose turn it is, X or O.  (Or: who moved last, from which we can
       figure whose turn it is).

       3) the successors (child nodes).

       4) the immediate payoff of having moved to this board position from its
       predecessor (parent node).

       5) and what move gets us from our predecessor node to here.  (Granted,
       knowing the board configuration before and after the move, it's easy to
       figure out the move; but it's easier still to store it as one is figur‐
       ing out a node's successors.)

       6) whatever else we might want to add later.

       These could be stored equally well in an array or in a hash, but it's
       my experience that hashes are best for cases where you have more than
       just two or three bits of data, or especially when you might need to
       add new bits of data.  Moreover, hash key names are mnemonic --
       $node->{'last_move_payoff'} is plain as day, whereas it's not so easy
       having to remember with an array that $node->[3] is where you decided
       to keep the payoff.

	   Footnote: Of course, there are ways around that problem: just swear
	   you'll never use a real numeric index to access data in the array,
	   and instead use constants with mnemonic names:

	     use strict;
	     use constant idx_PAYOFF => 3;

	   Or use a pseudohash.	 But I prefer to keep it simple, and use a

	   These are, incidentally, the same arguments that people weigh when
	   trying to decide whether their object-oriented modules should be
	   based on blessed hashes, blessed arrays, or what.  Essentially the
	   only difference here is that we're not blessing our nodes or talk‐
	   ing in terms of classes and methods.

	   [end footnote]

       So, we might as well represent nodes like so:

	 $node = { # hashref
	    'board'	     => ...board string, e.g., "xx_x_xoo_oo"

	    'last_move_payoff' => ...payoff of the move
				   that got us here.

	    'last_move_from' =>	 ...the start...
	    'last_move_to'   =>	 ...and end point of the move
				     that got us here.	E.g., 5 and 6,
				     representing a move from 5 to 6.

	    'whose_turn'     => ...whose move it then becomes.
				  just an 'x' or 'o'.

	    'successors' => ...the successors

       Note that we could have a field called something like 'last_move_who'
       to denote who last moved, but since turns in Alak always alternate (and
       no-one can pass), storing whose move it is now and who last moved is
       redundant -- if X last moved, it's O turn now, and vice versa.  I chose
       to have a 'whose_turn' field instead of a 'last_move_who', but it
       doesn't really matter.  Either way, we'll end up inferring one from the
       other at several points in the program.

       When we want to store the successors of a node, should we use an array
       or a hash?  On the one hand, the successors to $node aren't essentially
       ordered, so there's no reason to use an array per se; on the other
       hand, if we used a hash, with successor nodes as values, we don't have
       anything particularly meaningful to use as keys.	 (And we can't use the
       successors themselves as keys, since the nodes are referred to by hash
       references, and you can't use a reference as a hash key.)  Given no
       particularly compelling reason to do otherwise, I choose to just use an
       array to store all a node's successors, although the order is never
       actually used for anything:

	 $node = {
	   'successors' => [ ...nodes... ],

       In any case, now that we've settled on what should be in a node, let's
       make a little sample tree out of a few nodes and see what we can do
       with it:

	 # Board just before move 3 in above game
	 my $n0 = {
	   'board' => 'xx_xx_oo_oo',
	   'last_move_payoff' => 0,
	   'last_move_from' =>	9,
	   'last_move_to'   =>	7,
	   'whose_turn' => 'x',
	   'successors' => [],

	 # And, for now, just two of the successors:

	 # X moves 4 to 6, giving xx__xxoo_oo
	 my $n1 = {
	   'board' => 'xx__xxoo_oo',
	   'last_move_payoff' => 0,
	   'last_move_from' =>	4,
	   'last_move_to'   =>	6,
	   'whose_turn' => 'o',
	   'successors' => [],

	 # or X moves 5 to 6, giving xx_x_xoo_oo
	 my $n2 = {
	   'board' => 'xx_x_xoo_oo',
	   'last_move_payoff' => 0,
	   'last_move_from' =>	5,
	   'last_move_to'   =>	6,
	   'whose_turn' => 'o',
	   'successors' => [],

	 # Now connect them...
	 push @{$n0->{'successors'}}, $n1, $n2;

       Digression: Links to Parents

       In comparing what we store in an Alak game tree node to what HTML::Ele‐
       ment stores in HTML element nodes, you'll note one big difference:
       every HTML::Element node contains a link to its parent, whereas we
       don't have our Alak nodes keeping a link to theirs.

       The reason this can be an important difference is because it can affect
       how Perl knows when you're not using pieces of memory anymore.  Con‐
       sider the tree we just built, above:

	     node 0
	    /	   \
	 node 1	   node 2

       There's two ways Perl knows you're using a piece of memory: 1) it's
       memory that belongs directly to a variable (i.e., is necessary to hold
       that variable's value, or values in the case of a hash or array), or 2)
       it's a piece of memory that something holds a reference to.  In the
       above code, Perl knows that the hash for node 0 (for board
       "xx_xx_oo_oo") is in use because something (namely, the variable $n0)
       holds a reference to it.	 Now, even if you followed the above code with

	 $n1 = $n2 = 'whatever';

       to make your variables $n1 and $n2 stop holding references to the
       hashes for the two successors of node 0, Perl would still know that
       those hashes are still in use, because node 0's successors array holds
       a reference to those hashes.  And Perl knows that node 0 is still in
       use because something still holds a reference to it.  Now, if you

	 my $root = $n0;

       This would change nothing -- there's just be two things holding a ref‐
       erence to the node 0 hash, which in turn holds a reference to the node
       1 and node 2 hashes.  And if you then added:

	 $n0 = 'stuff';

       still nothing would change, because something ($root) still holds a
       reference to the node 0 hash.  But once nothing holds a reference to
       the node 0 hash, Perl will know it can destroy that hash (and reclaim
       the memory for later use, say), and once it does that, nothing will
       hold a reference to the node 1 or the node 2 hashes, and those will be
       destroyed too.

       But consider if the node 1 and node 2 hashes each had an attribute
       "parent" (or "predecessor") that held a reference to node 0.  If your
       program stopped holding a reference to the node 0 hash, Perl could not
       then say that nothing holds a reference to node 0 -- because node 1 and
       node 2 still do.	 So, the memory for nodes 0, 1, and 2 would never get
       reclaimed (until your program ended, at which point Perl destroys
       everything).  If your program grew and discarded lots of nodes in the
       game tree, but didn't let Perl know it could reclaim their memory, your
       program could grow to use immense amounts of memory -- never a nice
       thing to have happen.  There's three ways around this:

       1) When you're finished with a node, delete the reference each of its
       children have to it (in this case, deleting $n1->{'parent'}, say).
       When you're finished with a whole tree, just go through the whole tree
       erasing links that children have to their children.

       2) Reconsider whether you really need to have each node hold a refer‐
       ence to its parent.  Just not having those links will avoid the whole

       3) use the WeakRef module with Perl 5.6 or later.  This allows you to
       "weaken" some references (like the references that node 1 and 2 could
       hold to their parent) so that they don't count when Perl goes asking
       whether anything holds a reference to a given piece of memory.  This
       wonderful new module eliminates the headaches that can often crop up
       with either of the two previous methods.

       It so happens that our Alak program is simple enough that we don't need
       for our nodes to have links to their parents, so the second solution is
       fine.  But in a more advanced program, the first or third solutions
       might be unavoidable.

       Recursively Printing the Tree

       I don't like working blind -- if I have any kind of a complex data
       structure in memory for a program I'm working on, the first thing I do
       is write something that can dump that structure to the screen so I can
       make sure that what I think is in memory really is what's in memory.
       Now, I could just use the "x" pretty-printer command in Perl's interac‐
       tive debugger, or I could have the program use the "Data::Dumper" mod‐
       ule.  But in this case, I think the output from those is rather too
       verbose.	 Once we have trees with dozens of nodes in them, we'll really
       want a dump of the tree to be as concise as possible, hopefully just
       one line per node.  What I'd like is something that can print $n0 and
       its successors (see above) as something like:

	 xx_xx_oo_oo  (O moved 9 to 7, 0 payoff)
	   xx__xxoo_oo	(X moved 4 to 6, 0 payoff)
	   xx_x_xoo_oo	(X moved 5 to 6, 0 payoff)

       A subroutine to print a line for a given node, and then do that again
       for each successor, would look something like:

	 sub dump_tree {
	   my $n = $_[0]; # "n" is for node
	     ...something expressing $n'n content...
	   foreach my $s (@{$n->{'successors'}}) {
	     # "s for successor

       And we could just start that out with a call to "dump_tree($n0)".

       Since this routine...

	   Footnote: I first wrote this routine starting out with "sub dump
	   {".	But when I tried actually calling "dump($n0)", Perl would dump
	   core!  Imagine my shock when I discovered that this is absolutely
	   to be expected -- Perl provides a built-in function called "dump",
	   the purpose of which is to, yes, make Perl dump core.  Calling our
	   routine "dump_tree" instead of "dump" neatly avoids that problem.

       ...does its work (dumping the subtree at and under the given node) by
       calling itself, it's recursive.	However, there's a special term for
       this kind of recursion across a tree: traversal.	 To traverse a tree
       means to do something to a node, and to traverse its children.  There's
       two prototypical ways to do this, depending on what happens when:

	 traversing X in pre-order:
	   * do something to X
	   * then traverse X's children

	 traversing X in post-order:
	   * traverse X's children
	   * then do something to X

       Dumping the tree to the screen the way we want it happens to be a mat‐
       ter of pre-order traversal, since the thing we do (print a description
       of the node) happens before we recurse into the successors.

       When we try writing the "print" statement for our above "dump_tree", we
       can get something like:

	 sub dump_tree {
	   my $n = $_[0];

	   # "xx_xx_oo_oo  (O moved 9 to 7, 0 payoff)"
	     $n->{'board'}, "  (",
	     ($n->{'whose_turn'} eq 'o' ? 'X' : 'O'),
	     # Infer who last moved from whose turn it is now.
	     " moved ", $n->{'last_move_from'},
	     " to ",	$n->{'last_move_to'},
	     ", ",	$n->{'last_move_payoff'},
	     " payoff)\n",

	   foreach my $s (@{$n->{'successors'}}) {

       If we run this on $n0 from above, we get this:

	 xx_xx_oo_oo  (O moved 9 to 7, 0 payoff)
	 xx__xxoo_oo  (X moved 4 to 6, 0 payoff)
	 xx_x_xoo_oo  (X moved 5 to 6, 0 payoff)

       Each line on its own is fine, but we forget to allow for indenting, and
       without that we can't tell what's a child of what.  (Imagine if the
       first successor had successors of its own -- you wouldn't be able to
       tell if it were a child, or a sibling.)	To get indenting, we'll need
       to have the instances of the "dump_tree" routine know how far down in
       the tree they're being called, by passing a depth parameter between

	 sub dump_tree {
	   my $n = $_[0];
	   my $depth = $_[1];
	   $depth = 0 unless defined $depth;
	     "	" x $depth,
	   foreach my $s (@{$n->{'successors'}}) {
	     dump_tree($s, $depth + 1);

       When we call "dump_tree($n0)", $depth (from $_[1]) is undefined, so
       gets set to 0, which translates into an indenting of no spaces.	But
       when "dump_tree" invokes itself on $n0's children, those instances see
       $depth + 1 as their $_[1], giving appropriate indenting.

	   Footnote: Passing values around between different invocations of a
	   recursive routine, as shown, is a decent way to share the data.
	   Another way to share the data is by keeping it in a global vari‐
	   able, like $Depth, initially set to 0.  Each time "dump_tree" is
	   about to recurse, it must "++$Depth", and when it's back, it must

	   Or, if the reader is familiar with closures, consider this

	     sub dump_tree {
	       # A wrapper around calls to a recursive closure:
	       my $start_node = $_[0];
	       my $depth = 0;
		# to be shared across calls to $recursor.
	       my $recursor;
	       $recursor = sub {
		 my $n = $_[0];
		 print "  " x $depth,
		 foreach my $s (@{$n->{'successors'}}) {
	       $recursor->($start_node); # start recursing
	       undef $recursor;

	   The reader with an advanced understanding of Perl's reference-
	   count-based garbage collection is invited to consider why it is
	   currently necessary to undef $recursor (or otherwise change its
	   value) after all recursion is done.

	   The reader whose mind is perverse in other ways is invited to con‐
	   sider how (or when!) passing a depth parameter around is unneces‐
	   sary because of information that Perl's caller(N) function reports!

	   [end footnote]

       Growing the Tree

       Our "dump_tree" routine works fine for the sample tree we've got, so
       now we should get the program working on making its own trees, starting
       from a given board.

       In "Games::Alak" (the CPAN-released version of Alak that uses essen‐
       tially the same code that we're currently discussing the tree-related
       parts of), there is a routine called "figure_successors" that, given
       one childless node, will figure out all its possible successors.	 That
       is, it looks at the current board, looks at every piece belonging to
       the player whose turn it is, and considers the effect of moving each
       piece every possible way -- notably, it figures out the immediate pay‐
       off, and if that move would end the game, it notes that by setting an
       "endgame" entry in that node's hash.  (That way, we know that that's a
       node that can't have successors.)

       In the code for "Games::Alak", "figure_successors" does all these
       things, in a rather straightforward way.	 I won't walk you through the
       details of the "figure_successors" code I've written, since the code
       has nothing much to do with trees, and is all just implementation of
       the Alak rules for what can move where, with what result.  Espicially
       interested readers can puzzle over that part of code in the source
       listing in the archive from CPAN, but others can just assume that it
       works as described above.

       But consider that "figure_successors", regardless of its inner work‐
       ings, does not grow the tree; it only makes one set of successors for
       one node at a time.  It has to be up to a different routine to call
       "figure_successors", and to keep applying it as needed, in order to
       make a nice big tree that our game-playing program can base its deci‐
       sions on.

       Now, we could do this by just starting from one node, applying "fig‐
       ure_successors" to it, then applying "figure_successors" on all the
       resulting children, and so on:

	 sub grow {  # Just a first attempt at this!
	   my $n = $_[0];
	       # already has successors.
	     or $n->{'endgame'}
	       # can't have successors.
	   foreach my $s (@{$n->{'successors'}}) {
	     grow($s); # recurse

       If you have a game tree for tic-tac-toe, and you grow it without limi‐
       tation (as above), you will soon enough have a fully "solved" tree,
       where every node that can have successors does, and all the leaves of
       the tree are all the possible endgames (where, in each case, the board
       is filled).  But a game of Alak is different from tic-tac-toe, because
       it can, in theory, go on forever.  For example, the following sequence
       of moves is quite possible:

	 xxxx__o_ooo (x moved back)
	 xxxx___oooo (o moved back)
	 ...repeat forever...

       So if you tried using our above attempt at a "grow" routine, Perl would
       happily start trying to construct an infinitely deep tree, containing
       an infinite number of nodes, consuming an infinite amount of memory,
       and requiring an infinite amount of time.  As the old saying goes: "You
       can't have everything -- where would you put it?"  So we have to place
       limits on how much we'll grow the tree.

       There's more than one way to do this:

       1. We could grow the tree until we hit some limit on the number of
       nodes we'll allow in the tree.

       2. We could grow the tree until we hit some limit on the amount of time
       we're willing to spend.

       3. Or we could grow the tree until it is fully fleshed out to a certain

       Since we already know to track depth (as we did in writing
       "dump_tree"), we'll do it that way, the third way.  The implementation
       for that third approach is also pretty straightforward:

	 $Max_depth = 3;
	 sub grow {
	   my $n = $_[0];
	   my $depth = $_[1] ⎪⎪ 0;
	     $depth >= $Max_depth
	     or @{$n->{'successors'}}
	     or $n->{'endgame'}
	   foreach my $s (@{$n->{'successors'}}) {
	     grow($s, $depth + 1);
	   # If we're at $Max_depth, then figure_successors
	   #  didn't get called, so there's no successors
	   #  to recurse under -- that's what stops recursion.

       If we start from a single node (whether it's a node for the starting
       board "xxxx___oooo", or for whatever board the computer is faced with),
       set $Max_depth to 4, and apply "grow" to it, it will grow the tree to
       include several hundred nodes.

	   Footnote: If at each move there are four pieces that can move, and
	   they can each move right or left, the "branching factor" of the
	   tree is eight, giving a tree with 1 (depth 0) + 8 (depth 1) + 8 **
	   2 + 8 ** 3 + 8 ** 4	= 4681 nodes in it.  But, in practice, not all
	   pieces can move in both directions (none of the x pieces in
	   "xxxx___oooo" can move left, for example), and there may be fewer
	   than four pieces, if some were lost.	 For example, there are 801
	   nodes in a tree of depth four starting from "xxxx___oooo", suggest‐
	   ing an average branching factor of about five (801 ** (1/4) is
	   about 5.3), not eight.

       What we need to derive from that tree is the information about what are
       the best moves for X.  The simplest way to consider the payoff of dif‐
       ferent successors is to just average them -- but what we average isn't
       always their immediate payoffs (because that'd leave us using only one
       generation of information), but the average payoff of their successors,
       if any.	We can formalize this as:

	 To figure a node's average payoff:
	   If the node has successors:
	     Figure each successor's average payoff.
	     My average payoff is the average of theirs.
	     My average payoff is my immediate payoff.

       Since this involves recursing into the successors before doing anything
       with the current node, this will traverse the tree in post-order.

       We could work that up as a routine of its own, and apply that to the
       tree after we've applied "grow" to it.  But since we'd never grow the
       tree without also figuring the average benefit, we might as well make
       that figuring part of the "grow" routine itself:

	 $Max_depth = 3;
	 sub grow {
	   my $n = $_[0];
	   my $depth = $_[1] ⎪⎪ 0;
	     $depth >= $Max_depth
	     or @{$n->{'successors'}}
	     or $n->{'endgame'}

	   if(@{$n->{'successors'}}) {
	     my $a_payoff_sum = 0;
	     foreach my $s (@{$n->{'successors'}}) {
	       grow($s, $depth + 1);  # RECURSE
	       $a_payoff_sum += $s->{'average_payoff'};
	      = $a_payoff_sum / @{$n->{'successors'}};
	   } else {
	      = $n->{'last_move_payoff'};

       So, by time "grow" has applied to a node (wherever in the tree it is),
       it will have figured successors if possible (which, in turn, sets
       "last_move_payoff" for each node it creates), and will have set "aver‐

       Beyond this, all that's needed is to start the board out with a root
       note of "xxxx___oooo", and have the computer (X) take turns with the
       user (O) until someone wins.  Whenever it's O's turn, "Games::Alak"
       presents a prompt to the user, letting him know the state of the cur‐
       rent board, and asking what move he selects.  When it's X's turn, the
       computer grows the game tree as necessary (using just the "grow" rou‐
       tine from above), then selects the move with the highest average payoff
       (or one of the highest, in case of a tie).

       In either case, "selecting" a move means just setting that move's node
       as the new root of the program's game tree.  Its sibling nodes and
       their descendants (the boards that didn't get selected) and its parent
       node will be erased from memory, since they will no longer be in use
       (as Perl can tell by the fact that nothing holds references to them

       The interface code in "Games::Alak" (the code that prompts the user for
       his move) actually supports quite a few options besides just moving --
       including dumping the game tree to a specified depth (using a slightly
       fancier version of "dump_tree", above), resetting the game, changing
       $Max_depth in the middle of the game, and quitting the game.  Like
       "figure_successors", it's a bit too long to print here, but interested
       users are welcome to peruse (and freely modify) the code, as well as to
       enjoy just playing the game.

       Now, in practice, there's more to game trees than this: for games with
       a larger branching factor than Alak has (which is most!), game trees of
       depth four or larger would contain too many nodes to be manageable,
       most of those nodes being strategically quite uninteresting for either
       player; dealing with game trees specifically is therefore a matter of
       recognizing uninteresting contingencies and not bothering to grow the
       tree under them.

	   Footnote: For example, to choose a straightforward case: if O has a
	   choice between moves that put him in immediate danger of X winning
	   and moves that don't, then O won't ever choose the dangerous moves
	   (and if he does, the computer will know enough to end the game), so
	   there's no point in growing the tree any further beneath those

       But this sample implementation should illustrate the basics of how to
       build and manipulate a simple tree structure in memory.	And once
       you've understood the basics of tree storage here, you should be ready
       to better understand the complexities and peculiarities of other sys‐
       tems for creating, accessing, and changing trees, including
       Tree::DAG_Node, HTML::Element, XML::DOM, or related formalisms like
       XPath and XSL.

       [end body of article]

       [Author Credit]

       Sean M. Burke ("") is a tree-dwelling hominid.


       Dewdney, A[lexander] K[eewatin].	 1984.	Planiverse: Computer Contact
       with a Two-Dimensional World.  Poseidon Press, New York.

       Knuth, Donald Ervin.  1997.  Art of Computer Programming, Volume 1,
       Third Edition: Fundamental Algorithms.  Addison-Wesley,	Reading, MA.

       Wirth, Niklaus.	1976.  Algorithms + Data Structures = Programs Pren‐
       tice-Hall, Englewood Cliffs, NJ.

       Worth, Stan and Allman Sheldon.	Circa 1967.  George of the Jungle
       theme.  [music by Jay Ward.]

       Wirth's classic, currently and lamentably out of print, has a good sec‐
       tion on trees.  I find it clearer than Knuth's (if not quite as ency‐
       clopedic), probably because Wirth's example code is in a block-struc‐
       tured high-level language (basically Pascal), instead of in assembler
       (MIX).  I believe the book was re-issued in the 1980s under the titles
       Algorithms and Data Structures and, in a German edition, Algorithmen
       und Datenstrukturen.  Cheap copies of these editions should be avail‐
       able through used book services such as "".

       Worth's classic, however, is available on the soundtrack to the 1997
       George of the Jungle movie, as performed by The Presidents of the
       United States of America.

       Return to the HTML::Tree docs.

perl v5.8.8			  2006-08-04	     HTML::Tree::AboutTrees(3)

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