Follow the links to see the questions for that category.
Note that the difficulty ratings are very "subjectively" prescribed.
If you're anxious to learn the solutions for one I have yet to complete,
leave a note in the guestbook and I'll get to it next.
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Category |
Difficulty |
Description |
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Difficulty 1 Questions
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1/5 |
These are relatively simple questions, good for a warm-up
before the challenges which lie before you. With just a little
brainstorming or experimentation, you should be able to elucidate
the answers to these.
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Difficulty 2 Questions
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2/5 |
These questions will require a little more thought.
If the key "insights" do not present themselves,
some experimentation should eventually lead you
to the results.
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Difficulty 3 Questions
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3/5 |
These questions start to get more challenging and may
require some preexisting knowledge or skills on your part,
such as an intuition for physics or mathematical induction.
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Difficulty 4 Questions
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4/5 |
This is where some of the much "cooler" questions are.
They are quite challenging, and most likely will take you
some time to solve, assuming you can solve them at all!
As challenging as they are however, I promise that once
you learn the key "insights" to solving them, you
will be impressed at how nicely simple and elegant
the solutions are. If they weren't, I wouldn't bother
putting them on my site.
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Difficulty 5 Questions
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5/5 |
Not for the faint of heart, or mind, these questions
will really boggle you. As much as it may seem to the
contrary however, I promise that none of them are dumb
"there is no answer" questions. They all have legitimate
solutions, though you will almost surely require a couple
hints before figuring them out. Even then, you may
likely end up needing the full solution to understand them.
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Computer Science Questions
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Various |
Unlike the above, many of which have relation to without
direct association with computer science, these questions are
specifically for people with some background in Computer Science.
Most of these have to do with writing an algorithm,
and then optimizing the algorithm in some manner, or
solving the problem within some constraint.
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