A hammer I like to use when reviewing papers and PhD proposals is one that (lacking a good name) I call the “squeeze technique” and it applies to research that optimizes something. To squeeze an idea you ask:
- How much of the benefit can be attained without the new idea?
- If the new idea succeeds wildly, how much benefit can be attained?
- How large is the gap between these two?
I am not sure how big of a deal this is in academia. If you are happy to work in 2nd-tier or lower schools, then you probably need to execute well rather than to choose good ideas. However, it's a very big deal if you want to produce a real improvement to computer science.
The first item is the KISS principle: keep it simple, stupid. Given that human resources are usually the most tightly constrained, simple solutions are very valuable. Often doing nothing at all will already work out reasonably. Trickier, there is often a horribly crude solution to a problem that will work rather effectively. In such a case, be crude. There are better places to use your time.
The second item is sometimes called a speed of light bound, due to the speed of light being so impressively unbeatable. You ask yourself how much an idea could help even if you expend years of effort and everything goes perfectly. In many cases the maximum benefit is not that high, so you may as well save your effort. A common example is in speeding up a system. Unless you are working on a major bottleneck, any amount of speedup will not help very much.
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