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{{distinguish2|[[Vlist]], a municipality in the Netherlands}}
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In [[computer science]], the '''VList''' is a [[persistent data structure|persistent]] [[data structure]] designed by [[Phil Bagwell]] in 2002 that combines the fast indexing of [[Array data structure|arrays]] with the easy extension of [[cons]]-based (or singly linked) [[linked list]]s.<ref> {{Citation | title=Fast Functional Lists, Hash-Lists, Deques and Variable Length Arrays | first1=Phil | last1=Bagwell | year=2002 | publisher=EPFL | url=http://infoscience.epfl.ch/record/64410/files/techlists.pdf}} </ref>
 
Like arrays, VLists have constant-time lookup on average and are highly compact, requiring only [[Big-O notation|O]](log ''n'') storage for pointers, allowing them to take advantage of [[locality of reference]].  Like singly linked or cons-based lists, they are [[persistent data structure|persistent]], and elements can be added to or removed from the front in constant time. Length can also be found in O(log ''n'') time.
 
The primary operations of a VList are:
* Locate the ''k''th element (O(1) average, O(log ''n'') worst-case)
* Add an element to the front of the VList (O(1) average, with an occasional allocation)
* Obtain a new array beginning at the second element of an old array (O(1))
* Compute the length of the list (O(log ''n''))
 
The primary advantage VLists have over arrays is that different updated versions of the VList automatically share structure. Because VLists are immutable, they are most useful in [[functional programming language]]s, where their efficiency allows a purely functional implementation of data structures traditionally thought to require mutable arrays, such as [[hash table]]s.  
 
However, VLists also have a number of disadvantages over their competitors:
* While immutability is a benefit, it is also a drawback, making it inefficient to modify elements in the middle of the array.
* Access near the end of the list can be as expensive as O(log ''n''); it is only constant on average over all elements. This is still, however, much better than performing the same operation on cons-based lists.
* Wasted space in the first block is proportional to ''n''.  This is similar to linked lists, but there are data structures with less overhead.  When used as a [[Persistent data structure|fully persistent data structure]], the overhead may be considerably higher and this data structure may not be appropriate.
 
== Structure ==
 
The underlying structure of a VList can be seen as a singly linked list of arrays whose sizes decrease geometrically; in its simplest form, the first contains the first half of the elements in the list, the next the first half of the remainder, and so on. Each of these blocks stores some information such as its size and a pointer to the next.
 
<center>[[File:VList example diagram.png|A diagram of a simple VList]]<br>
<small>''An array-list. The reference shown refers to the VList (2,3,4,5,6).''</small>
</center>
 
The average constant-time indexing operation comes directly from this structure; given a random valid index, we simply observe the size of the blocks and follow pointers until we reach the one it should be in. The chance is 1/2 that it falls in the first block and we need not follow any pointers; the chance is 1/4 we have to follow only one, and so on, so that the expected number of pointers we have to follow is:
 
<math>\sum_{i=1}^{\lceil log_2 n \rceil} \frac{i-1}{2^i} < \sum_{i=1}^{\infty} \frac{i-1}{2^i} = 1.</math>
 
Any particular reference to a VList is actually a <''base'', ''offset''> pair indicating the position of its first element in the data structure described above. The ''base'' part indicates which of the arrays its first element falls in, while the ''offset'' part indicates its index in that array. This makes it easy to "remove" an element from the front of the list; we simply increase the offset, or increase the base and set the offset to zero if the offset goes out of range. If a particular reference is the last to leave a block, the block will be [[garbage collection (computer science)|garbage-collected]] if such facilities are available, or otherwise must be freed explicitly.
 
Because the lists are constructed incrementally, the first array in the array list may not contain twice as many values as the next one, although the rest do; this does not significantly impact indexing performance. We nevertheless allocate this much space for the first array, so that if we add more elements to the front of the list in the future we can simply add them to this list and update the size. If the array fills up, we create a new array, twice as large again as this one, and link it to the old first array.
 
The trickier case, however, is adding a new item to the front of a list, call it A, which starts somewhere in the middle of the array-list data structure. This is the operation that allows VLists to be persistent. To accomplish this, we create a new array, and we link it to the array containing the first element of A. The new array must also store the offset of the first element of A in that array. Then, we can proceed to add any number of items we like to our new array, and any references into this new array will point to VLists which share a tail of values with the old array. Note that with this operation it is possible to create VLists which degenerate into simple linked lists, thus obliterating the performance claims made at the beginning of this article.
 
==Variants==
VList may be modified to support the implementation of a [[growable array]].  In the application of a [[growable array]], [[immutable object|immutability]] is no longer required. Instead of growing at the beginning of the list, the ordering interpretation is reversed to allow growing at the end of the array.
 
==See also==
* [[Purely functional]]
 
== References ==
{{reflist}}
 
==External links==
* [http://www.ootl.org/doc/vlist.html C++ implementation of VLists]
* [http://www.codeproject.com/KB/collections/vlist.aspx C# implementation of VLists]
* [http://git.savannah.gnu.org/cgit/guile.git/tree/module/ice-9/vlist.scm Scheme implementation of VLists and VList-based hash lists] for [[GNU Guile]]
* [http://planet.plt-scheme.org/package-source/krhari/pfds.plt/1/3/vlist.ss Scheme (Typed Racket) implementation of VLists] for [[Racket (programming language)|Racket]]
 
[[Category:Arrays]]
[[Category:Linked lists]]

Latest revision as of 23:42, 18 December 2014

You may discover convenient techniques to speed up computer by making the most from the built in tools inside a Windows as well as downloading the Service Pack updates-speed up a PC and fix error. Simply follow a limited regulations to instantaneously create the computer rapidly than ever.

We should recognize certain convenient and inexpensive ways that will solve the problem of the computer plus speed it up. The earlier you fix it, the less damage the computer gets. I usually tell about some worthwhile techniques which might assist you to accelerate you computer.

One of the most overlooked factors a computer will slow down is because the registry has become corrupt. The registry is essentially your computer's running system. Anytime you're running your computer, entries are being prepared plus deleted from a registry. The impact this has is it leaves false entries inside a registry. So, the computer's resources must function around these false entries.

In purchase to remove the programs on the computer, Windows Installer need to be inside a healthy state. If its installation is corrupted you will receive error 1721 inside Windows 7, Vista and XP throughout the system removal task. Simply re-registering its component files would solve your issue.

When it comes to software, this really is the vital part because it is the one running the program and additional programs required inside a functions. Always keep the cleanliness of the system from obsolete data by getting a advantageous tuneup utilities 2014. Protect it from a virus found on the net by providing a workable virus protection system. You could have a monthly clean up by running the defragmenter system. This method it may enhance the performance of the computer plus for you to avoid any mistakes. If you think something is incorrect with all the computer software, and we don't know how to fix it then refer to a technician.

Although I usually utilize the latest variation of browser, sometimes different extensions plus plugins become the cause of mistakes with my browser and the system. The same is the story with my browser that was crashing frequently possibly due to the Flash player error.

The 'registry' is just the central database that shops all your settings and options. It's a certainly significant part of the XP program, which means that Windows is continually adding and updating the files inside it. The issues occur when Windows actually corrupts & loses a few of these files. This makes the computer run slow, because it attempts difficult to locate them again.

You are able to click here to find out how to speed up Windows plus heighten PC perfomance. And you can click here to download a registry cleaner to aid you clean up registry.