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An introduction to Searching Algorithms

Searching is integral to life - we search for things all the time - or at least I do! As often is the case, just as it is in life, so it is in computer science and searching plays a very important role when it comes to working with data.  A search algorithm is any algorithm which solves the Search problem, namely, to retrieve information stored within some data structure, or calculated in the search space of a problem domain. Examples of such structures include but are not limited to a Linked List, an Array data structure, or a Search tree. The appropriate search algorithm often depends on the data structure being searched, but also on any a priori knowledge about the data. Searching also encompasses algorithms that query the data structure, such as the SQL SELECT command.

This series will primarily look at python code for the various searching algorithms, along with an explanation (video or presentation) for each. If you're really interested however, there is plenty of additional information on this topic below:

From http://www.geeksforgeeks.org/searching-algorithms/#algo and BBC Bitesize

Why Searching Algorithms?

We often need to find one particular item of data amongst many hundreds, thousands, millions or more. For example, you might need to find someone’s phone number on your phone, or a particular business’s address in the UK.

This is why searching algorithms are important. Without them you would have to look at each item of data – each phone number or business address – individually, to see whether it is what you are looking for. In a large set of data, it will take a long time to do this. Instead, a searching algorithm can be used to help find the item of data you are looking for.

Searching Algorithms :

Linear Search

Binary Search

Jump Search

Interpolation Search

Exponential Search

Sublist Search (Search a linked list in another list)

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