////
Copyright 2011-2016 Beman Dawes

Distributed under the Boost Software License, Version 1.0.
(http://www.boost.org/LICENSE_1_0.txt)
////

[#choosing]
# Choosing between Conversion Functions, Buffer Types, and Arithmetic Types
:idprefix: choosing_

NOTE: Deciding which is the best endianness approach (conversion functions, buffer
types, or arithmetic types) for a particular application involves complex
engineering trade-offs. It is hard to assess those trade-offs without some
understanding of the different interfaces, so you might want to read the
<<conversion,conversion functions>>, <<buffers,buffer types>>, and
<<arithmetic,arithmetic types>> pages before proceeding.

The best approach to endianness for a particular application depends on the
interaction between the application's needs and the characteristics of each of
the three  approaches.

*Recommendation:* If you are new to endianness, uncertain, or don't want to
invest the time to study engineering trade-offs, use
<<arithmetic,endian arithmetic types>>. They are safe, easy to use, and easy to
maintain. Use the _<<choosing_anticipating_need,anticipating need>>_ design
pattern locally around performance hot spots like lengthy loops, if needed.

## Background

A dealing with endianness usually implies a program portability or a data
portability requirement, and often both. That means real programs dealing with
endianness are usually complex, so the examples shown here would really be
written as multiple functions spread across multiple translation units. They
would involve interfaces that can not be altered as they are supplied by
third-parties or the standard library.

## Characteristics

The characteristics that differentiate the three approaches to endianness are
the endianness invariants, conversion explicitness, arithmetic operations, sizes
available, and alignment requirements.

### Endianness invariants

*Endian conversion functions* use objects of the ordinary {cpp} arithmetic types
like `int` or `unsigned short` to hold values. That breaks the implicit
invariant that the {cpp} language rules apply. The usual language rules only apply
if the endianness of the object is currently set to the native endianness for
the platform. That can make it very hard to reason about logic flow, and result
in difficult to find bugs.

For example:

```
struct data_t  // big endian
{
  int32_t   v1;  // description ...
  int32_t   v2;  // description ...
  ... additional character data members (i.e. non-endian)
  int32_t   v3;  // description ...
};

data_t data;

read(data);
big_to_native_inplace(data.v1);
big_to_native_inplace(data.v2);

...

++v1;
third_party::func(data.v2);

...

native_to_big_inplace(data.v1);
native_to_big_inplace(data.v2);
write(data);
```

The programmer didn't bother to convert `data.v3` to native endianness because
that member isn't used. A later maintainer needs to pass `data.v3` to the
third-party function, so adds `third_party::func(data.v3);` somewhere deep in
the code. This causes a silent failure because the usual invariant that an
object of type `int32_t` holds a value as described by the {cpp} core language
does not apply.

*Endian buffer and arithmetic types* hold values internally as arrays of
characters with an invariant that the endianness of the array never changes.
That makes these types easier to use and programs easier to maintain.

Here is the same example, using an endian arithmetic type:

```
struct data_t
{
  big_int32_t   v1;  // description ...
  big_int32_t   v2;  // description ...
  ... additional character data members (i.e. non-endian)
  big_int32_t   v3;  // description ...
};

data_t data;

read(data);

...

++v1;
third_party::func(data.v2);

...

write(data);
```

A later maintainer can add `third_party::func(data.v3)` and it will just-work.

### Conversion explicitness

*Endian conversion functions* and *buffer types* never perform implicit
conversions. This gives users explicit control of when conversion occurs, and
may help avoid unnecessary conversions.

*Endian arithmetic types* perform conversion implicitly. That makes these types
very easy to use, but can result in unnecessary conversions. Failure to hoist
conversions out of inner loops can bring a performance penalty.

### Arithmetic operations

*Endian conversion functions* do not supply arithmetic operations, but this is
not a concern since this approach uses ordinary {cpp} arithmetic types to hold
values.

*Endian buffer types* do not supply arithmetic operations. Although this
approach avoids unnecessary conversions, it can result in the introduction of
additional variables and confuse maintenance programmers.

*Endian arithmetic types* do supply arithmetic operations. They are very easy to
use if lots of arithmetic is involved.

### Sizes

*Endianness conversion functions* only support 1, 2, 4, and 8 byte integers.
That's sufficient for many applications.

*Endian buffer and arithmetic types* support 1, 2, 3, 4, 5, 6, 7, and 8 byte
integers. For an application where memory use or I/O speed is the limiting
factor, using sizes tailored to application needs can be useful.

### Alignments

*Endianness conversion functions* only support aligned integer and
floating-point types. That's sufficient for most applications.

*Endian buffer and arithmetic types* support both aligned and unaligned
integer and floating-point types. Unaligned types are rarely needed, but when
needed they are often very useful and workarounds are painful. For example:

Non-portable code like this:

```
struct S {
  uint16_t a; // big endian
  uint32_t b; // big endian
} __attribute__ ((packed));
```

Can be replaced with portable code like this:

```
struct S {
  big_uint16_ut a;
  big_uint32_ut b;
};
```

## Design patterns

Applications often traffic in endian data as records or packets containing
multiple endian data elements. For simplicity, we will just call them records.

If desired endianness differs from native endianness, a conversion has to be
performed. When should that conversion occur? Three design patterns have
evolved.

### Convert only as needed (i.e. lazy)

This pattern defers conversion to the point in the code where the data
element is actually used.

This pattern is appropriate when which endian element is actually used varies
greatly according to record content or other circumstances

[#choosing_anticipating_need]
### Convert in anticipation of need

This pattern performs conversion to native endianness in anticipation of use,
such as immediately after reading records. If needed, conversion to the output
endianness is performed after all possible needs have passed, such as just
before writing records.

One implementation of this pattern is to create a proxy record with endianness
converted to native in a read function, and expose only that proxy to the rest
of the implementation. If a write function, if needed, handles the conversion
from native to the desired output endianness.

This pattern is appropriate when all endian elements in a record are typically
used regardless of record content or other circumstances.

### Convert only as needed, except locally in anticipation of need

This pattern in general defers conversion but for specific local needs does
anticipatory conversion. Although particularly appropriate when coupled with the
endian buffer or arithmetic types, it also works well with the conversion
functions.

Example:

[subs=+quotes]
```
struct data_t
{
  big_int32_t   v1;
  big_int32_t   v2;
  big_int32_t   v3;
};

data_t data;

read(data);

...
++v1;
...

int32_t v3_temp = data.v3;  // hoist conversion out of loop

for (int32_t i = 0; i < `large-number`; ++i)
{
  ... `lengthy computation that accesses v3_temp` ...
}
data.v3 = v3_temp;

write(data);
```

In general the above pseudo-code leaves conversion up to the endian arithmetic
type `big_int32_t`. But to avoid conversion inside the loop, a temporary is
created before the loop is entered, and then used to set the new value of
`data.v3` after the loop is complete.

Question: Won't the compiler's optimizer hoist the conversion out of the loop
anyhow?

Answer: V{cpp} 2015 Preview, and probably others, does not, even for a toy test
program. Although the savings is small (two register `bswap` instructions), the
cost might be significant if the loop is repeated enough times. On the other
hand, the program may be so dominated by I/O time that even a lengthy loop will
be immaterial.

## Use case examples

### Porting endian unaware codebase

An existing codebase runs on  big endian systems. It does not currently deal
with endianness. The codebase needs to be modified so it can run on little
endian systems under various operating systems. To ease transition and protect
value of existing files, external data will continue to be maintained as big
endian.

The <<arithmetic,endian arithmetic approach>> is recommended to meet these
needs. A relatively small number of header files dealing with binary I/O layouts
need to change types. For example, `short` or `int16_t` would change to
`big_int16_t`. No changes are required for `.cpp` files.

### Porting endian aware codebase

An existing codebase runs on little-endian Linux systems. It already deals with
endianness via
http://man7.org/linux/man-pages/man3/endian.3.html[Linux provided functions].
Because of a business merger, the codebase has to be quickly modified for
Windows and possibly other operating systems, while still supporting Linux. The
codebase is reliable and the programmers are all well-aware of endian issues.

These factors all argue for an <<conversion, endian conversion approach>> that
just mechanically changes the calls to `htobe32`, etc. to
`boost::endian::native_to_big`, etc. and replaces `<endian.h>` with
`<boost/endian/conversion.hpp>`.

### Reliability and arithmetic-speed

A new, complex, multi-threaded application is to be developed that must run
on little endian machines, but do big endian network I/O. The developers believe
computational speed for endian variable is critical but have seen numerous bugs
result from inability to reason about endian conversion state. They are also
worried that future maintenance changes could inadvertently introduce a lot of
slow conversions if full-blown endian arithmetic types are used.

The <<buffers,endian buffers>> approach is made-to-order for this use case.

### Reliability and ease-of-use

A new, complex, multi-threaded application is to be developed that must run on
little endian machines, but do big endian network I/O. The developers believe
computational speed for endian variables is *not critical* but have seen
numerous bugs result from inability to reason about endian conversion state.
They are also concerned about ease-of-use both during development and long-term
maintenance.

Removing concern about conversion speed and adding concern about ease-of-use
tips the balance strongly in favor the
<<arithmetic,endian arithmetic approach>>.
