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<li><a href="#Algorithms">Algorithms</a></li>
<li><a href="#Data_Structure">Data Structure</a></li>
<li><a href="#Practice">Practice</a></li>
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<b>GeeksforGeeks</b>
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<div id='Algorithms'>
<p>
The answer to this is simple, we can have all the
above things only if we have performance. So
performance is like currency through which we can
buy all the above things. Another reason
for studying performance is – speed is fun!
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<div id='Data_Structure'>
<p>
For example, let us say, we want to store marks of
all students in a class, we can use an array to store
them. This helps in reducing the use of number of
variables as we don’t need to create a separate
variable for marks of every subject. All marks can
be accessed by simply traversing the array.
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<div id='Practice'>
<p>
Asymptotic Analysis is the big idea that handles
above issues in analyzing algorithms. In Asymptotic
Analysis, we evaluate the performance of an algorithm
in terms of input size (we don’t measure the actual
running time). We calculate, how does the time
(or space) taken by an algorithm increases with
the input size.
</p>
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<div id='interview'>
<p>
Also, in Asymptotic analysis, we always talk about
input sizes larger than a constant value. It might
be possible that those large inputs are never given
to your software and an algorithm which is
asymptotically slower, always performs better for
your particular situation. So, you may end up choosing
an algorithm that is Asymptotically slower but faster
for your software.
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