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<chapter id="ds">
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<chapter id="ds">
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  <?dbhtml filename="ds.html"?>
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  <?dbhtml filename="ds.html"?>
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  <title>Data structures</title>
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  <title>Data structures</title>
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  <para>There is lots of data that either flows through various HelenOS
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  <para>There is lots of data that either flows through various HelenOS
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  subsystems or is stored directly by them. Each subsystem uses its own data
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  subsystems or is stored directly by them. Each subsystem uses its own data
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  structures to represent the data. These data structures need to be kept
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  structures to represent the data. These data structures need to be kept
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  somewhere. In order to work efficiently, HelenOS, and especially its kernel,
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  somewhere. In order to work efficiently, HelenOS, and especially its kernel,
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  deploys several house keeping data types that are designed to faciliate
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  deploys several house keeping data types that are designed to faciliate
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  managing other data structures. Most of them serve like generic
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  managing other data structures. Most of them serve like generic
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  containers.</para>
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  containers.</para>
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  <section>
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  <section>
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    <title>Lists</title>
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    <title>Lists</title>
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    <indexterm>
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      <primary>linked list</primary>
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    </indexterm>
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    <para>HelenOS uses doubly-circularly-linked lists to bind related data
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    <para>HelenOS uses doubly-circularly-linked lists to bind related data
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    together. Lists are composed of an independent sentinel node called head
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    together. Lists are composed of an independent sentinel node called head
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    and links that are always part of the object that is to be put into the
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    and links that are always part of the object that is to be put into the
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    list. Adding items to a list thus doesn't require any further memory
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    list. Adding items to a list thus doesn't require any further memory
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    allocations. Head and each link then contains forward and backward
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    allocations. Head and each link then contains forward and backward
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    pointer. An empty list is composed of a sole head whose both pointers
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    pointer. An empty list is composed of a sole head whose both pointers
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    reference the head itself. The expense of two times bigger memory
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    reference the head itself. The expense of two times bigger memory
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    consumption as compared to memory consumption of singly linked lists is
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    consumption as compared to memory consumption of singly linked lists is
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    justified by constant insertion and removal times at random positions
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    justified by constant insertion and removal times at random positions
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    within the list.</para>
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    within the list.</para>
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    <para>Lists are frequently used to implement FIFO behaviour (e.g.
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    <para>Lists are frequently used to implement FIFO behaviour (e.g.
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    scheduler run queues or synchronization wait queues). Contrary to the FIFO
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    scheduler run queues or synchronization wait queues). Contrary to the FIFO
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    type, which is also supported by HelenOS, they don't take up any unused
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    type, which is also supported by HelenOS, they don't take up any unused
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    space and are more general. On the other hand, they are slower than
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    space and are more general. On the other hand, they are slower than
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    in-array FIFOs and can be hardly used to implement buffers.</para>
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    in-array FIFOs and can be hardly used to implement buffers.</para>
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  </section>
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  </section>
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  <section>
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  <section>
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    <title>FIFO queues</title>
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    <title>FIFO queues</title>
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    <indexterm>
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      <primary>FIFO queue</primary>
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    </indexterm>
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    <para>FIFO queues are implemented as either statically or dynamically
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    <para>FIFO queues are implemented as either statically or dynamically
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    allocated arrays<footnote>
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    allocated arrays<footnote>
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        <para>Depending on the array size.</para>
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        <para>Depending on the array size.</para>
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      </footnote> of some generic type with two indices. The first index
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      </footnote> of some generic type with two indices. The first index
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    points to the head of the FIFO queue and the other points to the tail
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    points to the head of the FIFO queue and the other points to the tail
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    thereof. There can be as many items in the FIFO as is the number of
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    thereof. There can be as many items in the FIFO as is the number of
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    elements in the array and no more. The indices are taken modulo size of
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    elements in the array and no more. The indices are taken modulo size of
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    the queue because as a consequence of insertions and deletions, the tail
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    the queue because as a consequence of insertions and deletions, the tail
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    can have numericaly lower index than the head.</para>
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    can have numericaly lower index than the head.</para>
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    <para>FIFO queues are used, for example, in ASID management code to store
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    <para>FIFO queues are used, for example, in ASID management code to store
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    inactive ASIDs or in userspace keyboard driver to buffer read
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    inactive ASIDs or in userspace keyboard driver to buffer read
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    characters.</para>
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    characters.</para>
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    <figure>
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    <figure>
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    <mediaobject id="fifo" xreflabel="">
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      <mediaobject id="fifo" xreflabel="">
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    <imageobject role="html">
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        <imageobject role="html">
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        <imagedata fileref="images/fifo.png" format="PNG" />
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          <imagedata fileref="images/fifo.png" format="PNG" />
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    </imageobject>
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        </imageobject>
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    <imageobject role="fop">
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        <imageobject role="fop">
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        <imagedata fileref="images.vector/fifo.svg" format="SVG" />
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          <imagedata fileref="images.vector/fifo.svg" format="SVG" />
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    </imageobject>
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        </imageobject>
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    </mediaobject>
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      </mediaobject>
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    <title>FIFO queue showing the wrap around the end of the array.</title>
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    </figure>
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      <title>FIFO queue showing the wrap around the end of the array.</title>
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    </figure>
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  </section>
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  </section>
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  <section>
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  <section>
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    <title>Hash tables</title>
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    <title>Hash tables</title>
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    <indexterm>
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      <primary>hash table</primary>
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    </indexterm>
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    <para>The kernel, as well as userspace, provides hash table data type
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    <para>The kernel, as well as userspace, provides hash table data type
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    which uses separate chaining. The hash table type is very generic in that
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    which uses separate chaining. The hash table type is very generic in that
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    it forces the user to supply methods for computing the hash index,
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    it forces the user to supply methods for computing the hash index,
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    comparing items against a set of keys and the item removal callback
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    comparing items against a set of keys and the item removal callback
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    function. Besides these virtual operations, the hash table is composed of
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    function. Besides these virtual operations, the hash table is composed of
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    a dynamically allocated array of list heads that represent each chain,
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    a dynamically allocated array of list heads that represent each chain,
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    number of chains and the maximal number of keys.</para>
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    number of chains and the maximal number of keys.</para>
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  </section>
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  </section>
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  <section>
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  <section>
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    <title>Bitmaps</title>
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    <title>Bitmaps</title>
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    <indexterm>
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      <primary>bitmap</primary>
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    </indexterm>
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    <para>Several bitmap operations such as clearing or setting consecutive
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    <para>Several bitmap operations such as clearing or setting consecutive
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    bit sequences as well as copying portions of one bitmap into another one
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    bit sequences as well as copying portions of one bitmap into another one
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    are supported.</para>
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    are supported.</para>
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  </section>
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  </section>
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  <section>
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  <section>
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    <title>B+trees</title>
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    <title>B+trees</title>
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    <indexterm>
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      <primary>B-tree</primary>
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    </indexterm>
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    <para>HelenOS makes use of a variant of B-tree called B+tree. B+trees, in
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    <para>HelenOS makes use of a variant of B-tree called B+tree. B+trees, in
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    HelenOS implementation, are 3-4-5 balanced trees. They are characteristic
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    HelenOS implementation, are 3-4-5 balanced trees. They are characteristic
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    by the fact that values are kept only in the leaf-level nodes and that
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    by the fact that values are kept only in the leaf-level nodes and that
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    these nodes are linked together in a list. This data structure has
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    these nodes are linked together in a list. This data structure has
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    logaritmic search, insertion and deletion times and, thanks to the
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    logaritmic search, insertion and deletion times and, thanks to the
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    leaf-level list, provides fantastic means of walking the nodes containing
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    leaf-level list, provides fantastic means of walking the nodes containing
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    data. Moreover, B+trees can be used for easy storing, resizing and merging
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    data. Moreover, B+trees can be used for easy storing, resizing and merging
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    of disjunctive intervals.</para>
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    of disjunctive intervals.</para>
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    <figure>
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    <figure>
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    <mediaobject id="btree" xreflabel="">
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      <mediaobject id="btree" xreflabel="">
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    <imageobject role="html">
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        <imageobject role="html">
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        <imagedata fileref="images/btree.png" format="PNG" />
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          <imagedata fileref="images/btree.png" format="PNG" />
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    </imageobject>
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        </imageobject>
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    <imageobject role="fop">
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        <imageobject role="fop">
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        <imagedata fileref="images.vector/btree.svg" format="SVG" />
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          <imagedata fileref="images.vector/btree.svg" format="SVG" />
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    </imageobject>
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        </imageobject>
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      </mediaobject>
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    </mediaobject>
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    <title>B+tree containing keys ranging from 1 to 12.</title>
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      <title>B+tree containing keys ranging from 1 to 12.</title>
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    </figure>
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    </figure>
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  </section>
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  </section>
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</chapter>
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</chapter>