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As you learn more about data structures, you ll discover new applications for recursion. For example, one of the most-often-used data structures in computer programming is the binary tree (see Figure 11-3). As you ll see later, binary trees were just made for recursion. The binary tree is similar to the linked list. Both consist of structs connected by pointers embedded in each struct.

Let s get some information about that object class Select graphic window, and press Cmd+ Shift+F; this displays the entry for the graphic window class For this project, you ll focus only on two properties: back pdf and front pdf; those are where the graphic window stores PDF data Here is an excerpt of Smile s dictionary describing the class graphic window: Class graphic window : (inherits from window) a window where you can draw pictures of various kinds by script, and that you can save as a PDF file or as a tiff file Plural form: graphic windows Properties: frame a list of small real -- {x origin, y origin, width, height} [..] [..] back pdf string -- The PDF data for the background of the window Can be set to a file, to some Graphic Kernel output or to raw PDF data as string.

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So, if we just run move() for mousemove events on the <h4>, the visitor s mouse will leave its confines Consequently, after an initial nudge, the <div> will not follow their mouse Sort of like a stubborn mule Not wanting that to be the case, let s bind move() to document rather than the <h4> And to improve performance in Internet Explorer 9, Firefox, Safari, Chrome, and Opera, let s do so for the capture phase Note that in Internet Explorer 8 or earlier, document will listen during the bubble phase instead So, pass true as the optional fourth parameter to addListener(): function drag(e) { if (!e) e = windowevent; if (!etarget) etarget = esrcElement; var wrapper = etargetparentNode; var left = parseInt(queryCascade(wrapper, "left")); var top = parseInt(queryCascade(wrapper, "top")); var clientX = eclientX; var clientY = eclientY; wrapperstyle.

Linked lists are linear. Each struct in the list is linked by pointers to the struct behind it and in front of it in the list. Binary trees always start with a single struct, known as the root struct or root node. Where the linked list structs we ve been working with contain a single pointer, named next, binary tree structs or nodes each have two pointers, usually known as left and right. Check out the binary tree in Figure 11-3. Notice that the root node has a left child and a right child. The left child has its own left child but its right pointer is set to NULL. The left child s left child has two NULL pointers. A node with two NULL pointers is known as a leaf node or terminal node. Binary trees are extremely useful. They work especially well when the data you are trying to sort has a comparative relationship. This means that if you compare one piece of data to another, you ll be able to judge the first piece as greater than, equal to, or less than the second piece. For example, numbers are comparative. Words in a dictionary can be comparative, if you consider their alphabetical order. The word iguana is greater than aardvark, but less than xenophobe. Here s how you might store a sequence of words, one at a time, in a binary tree. We ll start with this list of words:

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