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What general tips do you have for golfing(tips and tricks) in C?
1. Use bitwise XOR or - minus sign to check for inequality between integers:
if(a^b)
instead ofif(a!=b)
save 1 character.if(a-b)
instead ofif(a!=b)
also save 1 character.
2. Abuse main's
argument list to declare one or more integer variables:
3. The comma operator can be used to execute multiple expressions in a single block while avoiding braces:
4. The ternary conditional operator ?:
can often be used as a stand in for simple if-else
statements at considerable savings:
5. #define macros whose expansion has unbalanced braces/parentheses:
6. Use *a instead of a[0] for accessing the first element of an array.
7. Combine assignment with function calls:
Instead of this:
Do this:
8. Initialize multiple variables together:
Instead of this:
Do this:
9. Collapse zero/nonzero values
When you have an integer value and you need to collapse it to either 1 or 0, you can use !! to do so easily. This is sometimes advantageous for other alternatives like ?:.
Take this situation:
You could instead do this:
Another example:
Could be rewritten as:
10. Avoid catastrophic function-argument type declarations
If you're declaring a function where all five arguments are ints, then life is good. you can simply write
But suppose d
needs to be a char
, or even an int*
. Then you're screwed! If one parameter is preceded by a type, all of them must be:
But wait! There is a way around this disastrous explosion of useless characters. It goes like this:
This even saves on a standard main declaration if you need to use the command-line arguments:
is two bytes shorter than
You can submit your own in comment section.
Explore Programming Tricks Games
by Yanchang Zhao, RDataMining.com
There are more than 100 R tips at http://pj.freefaculty.org/R/Rtips.html, which provide quick examples to small challenges in everyday R programming, especially for users switching from other languages to R. There is also a .PDF version for it at http://pj.freefaculty.org/R/Rtips.pdf.
It presents short examples on:
– Data Input/Output
– Working with data frames: Recoding, selecting, aggregating
– Matrices and vector operations
– Applying functions, tapply, etc
– Graphing
– Common Statistical Chores
– Model Fitting (Regression-type things)
– Packages
– Misc. web resources
– R workspace
– Interface with the operating system
– Stupid R tricks: basics you can’t live without
– Misc R usages I find interesting.