Lakhasly

At its heart, Computer Science is about problem solving. That is not to say that only
Computer Science is about problem solving. It would be hubris to think that
Computer Science holds a monopoly on “problem solving.” Indeed, it would be hard
to find any discipline in which solving problems was not a substantial aspect or
motivation if not integral. Instead, Computer Science is the study of computers and
computation. It involves studying and understanding computational processes and
the development of algorithms and techniques and how they apply to problems.
Problem solving skills are not something that can be distilled down into a single
step by-step process. Each area and each problem comes with its own unique
challenges and considerations. General problem solving techniques can be identified,
studied and taught, but problem solving skills are something that come with
experience, hard work, and most importantly, failure. Problem solving is part and
parcel of the human experience.
That doesn’t mean we can’t identify techniques and strategies for approaching
problems, in particular problems that lend themselves to computational solutions. A
prerequisite to solving a problem is understanding it. What is the problem? Who or
what entities are involved in the problem? How do those entities interact with each
other? What are the problems or deficiencies that need to be addressed? Answering
these questions, we get an idea of where we are.
Ultimately, what is desired in a solution? What are the objectives that need to be
achieved? What would an ideal solution look like or what would it do? Who would
use the solution and how would they use it? By answering these questions, we get
an idea of where we want to be. Once we know where we are and where we want to
be, the problem solving process can begin: how do we get from point A to point B?
One of the first things a good engineer asks is: does a solution already exist? If a
solution already exists, then the problem is already solved! Ideally the solution is an
“off-the-shelf” solution: something that already exists and which may have been
designed for a different purpose but that can be repurposed for our problem.
However, there may be exceptions to this. The existing solution may be infeasible: it
may be too resource intensive or expensive. It may be too difficult or too expensive
to adapt to our problem. It may solve most of our problem, but may not work in some
corner cases. It may need to be heavily modified in order to work. Still, this basic
question may save a lot of time and effort in many cases.