Data structures and algorithms are
among the first things Computer Science students learn regarding
programming, and for good reason. Every trade has it's tools, and
among a programmer's tools you will find a knowledge base of various
data structures. Almost all programming revolves around manipulating
data structures, whether they are arrays, lists, queues or trees.
It's because of this a knowledge of data structures is fundamental.
In writing this blog post I wanted to
learn. I wanted to find something I didn't know previously, and set
out to understand more about data structures for both this blog and
myself. I've come to find that knowledge of data structures is used
as a means of testing new hires in interviews. Various companies like
Amazon, Google, and Microsoft all integrate some testing of their
candidates knowledge of data structures, as it provides a window to
their knowledge of programming.
The importance of knowing the ins and
outs of data structures isn't readily apparent from working on
projects at a university. Often it takes a mistake to appreciate a
correct decision, and in our college work we don't get to work on
projects quite as big as one would encounter in the real world.
Projects typically span a semester at most, and don’t' deal with
the amount of data that would really exasperate a poorly chosen data
structure. It's because o this that a sound working knowledge of
these systems is so important, that you need not conduct a trial by
fire at the workplace.
Personally I know I have room for
improvement in my understanding of data structures. This is a result
of my work ethic and personal introspection. There is always more to
learn, and I will never consider a topic mastered. Perfection in this
manner, to me, is unachievable, and always gives me something to work
for.
An interesting presentation I rifled
through was “Data Structures from the Future:Bloom Filters,
Distributed Hash Tables, and More!” By Tom Limoncelli, which gave
some insight on various data structures I knew less about.
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