Problems: Difference between revisions

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* [[ZINC:Problems]]
* [[ZINC:Problems]]


= Technical Problems =
= Kinds of problems =  
Technical problems are ones where we think we know pretty well exactly how to solve them, algorithmically.  Scientific problems may be technical, but are differentiated because I cannot describe algorithmically how to solve them. Instead, we should take an experimental approach, probably trying at least two different ways, and seeing which works best. Philosophical problems in this context means that I am not even sure how to phrase a scientific question or a testable hypothesis, but I recognize that there is a problem.  
We differentiate among bugs, blunders, technical problems, algorithmic problems and other problems.
 
* *Blunders* are typos or errors that can be put right immediately by typographical correction.
* *Bugs* are errors that may be put right, and do not require major new coding, but more than simple typographical correction.
* *Technical problems* are ones we know pretty well exactly how to solve, but may require more time or money than we have available, or maybe we are just lazy.
* *Algorithmic problems* are cases where the best method of doing something is in some doubt, and requires study. Examples of algorthmic problems are: what is the best way to score a molecule given the constraints of fast docking?
* There are other problems too. If a problem can be classified as one of the above, that can be helpful.


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= Philosophical Problems =
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[[Category:Problems]]
[[Category:Problems]]

Revision as of 16:10, 7 August 2009

This is the general problem page at docking.org. There are also specific problem pages as follows:

Kinds of problems

We differentiate among bugs, blunders, technical problems, algorithmic problems and other problems.

  • *Blunders* are typos or errors that can be put right immediately by typographical correction.
  • *Bugs* are errors that may be put right, and do not require major new coding, but more than simple typographical correction.
  • *Technical problems* are ones we know pretty well exactly how to solve, but may require more time or money than we have available, or maybe we are just lazy.
  • *Algorithmic problems* are cases where the best method of doing something is in some doubt, and requires study. Examples of algorthmic problems are: what is the best way to score a molecule given the constraints of fast docking?
  • There are other problems too. If a problem can be classified as one of the above, that can be helpful.
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