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56 lines
2.1 KiB
Markdown
Executable File
56 lines
2.1 KiB
Markdown
Executable File
# C/C++
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The C/C++ code should focus on using simplicity over "modern solutions". This may often mean to heavily restrict the code. The following rule of thumb applies:
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1. C99 and C++11 should be used where reasonable
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2. C++ may be used in places where external libraries basically require C++
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The reason for the strong focus on C is that we **personally** believe that C is simpler and easier to understand than the various abstractions provided by C++.
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## Operating system support
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C/C++ solutions should be valid on Windows 10+ and Linux.
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## Namespace
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### use
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Namespaces must never be globally used. This means for example `use namespace std;` is prohibited and functions from the standard namespace should be prefixed instead `std::`
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## Data types
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### Unsigned Integer
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Be careful when you use unsigned and signed integers. When using unsigned integers the compiler may create additional instructions depending on the situation since it must support integer wrapping.
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## Structs
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Make sure structs don't have too much overhead due to alignment padding. Re-ordering struct members can fix a lot of padding overhead.
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## Templates
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Don't use C++ templates.
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## Allocation
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Use memory arenas instead of over and over manually allocating memory.
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However, if neccessary use C allocation methods for heap allocation.
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## Functions
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### C++ function
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Don't use C++ standard library functions or C++ functions provided by other C++ header files unless you have to work with C++ types which is often required when working with third party libraries.
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### Parameters
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Generally, functions that take pointers to non-scalar types should modify the data instead of allocating new memory **IF** reasonable. This forces programmers to consciously create copies before passing data **IF** they need the original data. To indicate that a reference/pointer is not modified by a function define them as const!
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We believe this approach provides a framework for better memory management and better performance in general.
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Examples for this can be:
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* Matrix multiplication with a scalar
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* Sorting data (depends on sorting algorithm)
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