1. Chapter 25 Embedded systems programming
Bjarne Stroustrup

2. Abstract
This lecture provides a brief overview of what distinguishes embedded systems programming from “ordinary programming.” It then touches upon facilities that become prominent or problems when working “close to the hardware” such as free store use, bit manipulation, and coding standards. Remember: not all computers are little grey boxes hiding under desks in offices.
Stroustrup/Programming Nov'13

3. Overview Embedded systems What’s special/different Resource management
predictability
Resource management
memory
Access to hardware
Absolute addresses
Bits – unsigned
Coding standards
Stroustrup/Programming Nov'13

4. Embedded systems Hard real time Soft real time
Response must occur before the deadline
Soft real time
Response should occur before the deadline most of the time
Often there are plenty of resources to handle the common cases
But crises happen and must be handled
Predictability is key
Correctness is even more important than usual
“correctness” is not an abstract concept
“but I assumed that the hardware worked correctly” is no excuse
Over a long time and over a large range of conditions, it simply doesn’t
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5. Embedded systems Computers used as part of a larger system
That usually doesn’t look like a computer
That usually controls physical devices
Often reliability is critical
“Critical” as in “if the system fails someone might die”
Often resources (memory, processor capacity) are limited
Often real-time response is essential
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6. Embedded systems What are we talking about? Fuel injector controls
Assembly line quality monitors
Bar code readers
Bread machines
Cameras
Car assembly robots
Cell phones
Centrifuge controllers
CD players
Disk drive controllers
“Smart card” processors
Fuel injector controls
Medical equipment monitors
PDAs
Printer controllers
Sound systems
Rice cookers
Telephone switches
Water pump controllers
Welding machines
Windmills
Wrist watches …
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7. Do You Need to Know This Stuff ?
Computer Engineers – You will build and oversee the building of these systems
All “close to the hardware” code resembles this
The concern for correctness and predictability of embedded systems code is simply a more critical form of what we want for all code
Electrical Engineers – You will build and oversee the building of these systems.
You have to work with the computer guys
You have to be able to talk to them
You may have to teach them
You may have to take over for them
Computer scientists – you’ll know how to do this or only work on web applications (and the like)
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8. Predictability C++ operations execute in constant, measurable time
E.g., you can simply measure the time for an add operation or a virtual function call and that’ll be the cost of every such add operation and every virtual function call (pipelining, caching, implicit concurrency makes this somewhat trickier on some modern processors)
With the exception of:
Free store allocation (new)
Exception throw
So throw and new are typically banned in hard real-time applications
Today, I wouldn’t fly in a plane that used those
In 5 years, we’ll have solved the problem for throw
Each individual throw is predictable
Not just in C++ programs
Similar operations in other languages are similarly avoided
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9. Ideals/aims Given the constraints
Keep the highest level of abstraction
Don’t write glorified assembler code
Represent your ideas directly in code
As always, try to write the clearest, cleanest, most maintainable code
Don’t optimize until you have to
People far too often optimize prematurely
John Bentley’s rules for optimization
First law: Don’t do it
Second law (for experts only): Don’t do it yet
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10. Embedded systems programming
You (usually) have to be much more aware of the resources consumed in embedded systems programming than you have to in “ordinary” programs
Time
Space
Communication channels
Files
ROM (Read-Only Memory)
Flash memory …
You must take the time to learn about the way your language features are implemented for a particular platform
Hardware
Operating system
Libraries
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11. Embedded systems programming
A lot of this kind of programming is
Looking at specialized features of an RTOS (Real Time Operating System)
Using a “Non-hosted environment” (that’s one way of saying “a language right on top of hardware without an operating system”)
Involving (sometimes complex) device driver architectures
Dealing directly with hardware device interfaces …
We won’t go into details here
That’s what specific courses and manuals are for
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12. How to live without new What’s the problem?
old object
Free space
old object
What’s the problem?
C++ code refers directly to memory
Once allocated, an object cannot be moved (or can it?)
Allocation delays
The effort needed to find a new free chunk of memory of a given size depends on what has already been allocated
Fragmentation
If you have a “hole” (free space) of size N and you allocate an object of size M where M<N in it, you now have a fragment of size N-M to deal with
After a while, such fragments constitute much of the memory
New object
An object cannot be moved because it doesn’t know which pointers containing its address need to be updated.
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13. How to live without new Solution: pre-allocate Global objects Stacks
Allocated at startup time
Sets aside a fixed amount of memory
Stacks
Grow and shrink only at the top
No fragmentation
Constant time operations
Pools of fixed sized objects
We can allocate and deallocate in any order
Stack:
Top of stack
Pool:
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14. How to live without new No new (of course)
And no malloc() (memory allocation during runtime) either (for those of you who speak C)
No standard library containers (they use free store indirectly)
Unless you have a special hard-real time implementation
Instead
Define (or borrow) fixed-sized Pools
Define (or borrow) fixed-sized Stacks
Do not regress to using arrays and lots of pointers
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15. Pool example
// Note: element type known at compile time // allocation times are completely predictable (and short) // the user has to pre-calculate the maximum number of elements needed template<class T, int N> class Pool { public: Pool(); // make pool of N Ts – construct pools only during startup T* get(); // get a T from the pool; return 0 if no free Ts void free(T* p); // return a T given out by get() to the pool private: // keep track of T[N] array (e.g., a list of free objects) }; Pool<Small_buffer, 10> sb_pool; Pool<Status_indicator, 200> indicator_pool;
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16. Stack example
// Note: allocation times completely predictable (and short) // the user has to pre-calculate the maximum number of elements needed template<int N> class Stack { public: Stack(); // make an N byte stack – construct stacks only during startup void* get(int N); // allocate n bytes from the stack; return 0 if no free space void free(void* p); // return the last block returned by get() to the stack private: // keep track of an array of N bytes (e.g. a top of stack pointer) }; Stack<50*1024> my_free_store; // 50K worth of storage to be used as a stack void* pv1 = my_free_store.get(256 * sizeof(int)); // allocate array of ints int* pi = static_cast<int*>(pv1); // you have to convert memory to objects void* pv2 = my_free_store.get(50); Pump_driver* pdriver = static_cast<Pump_driver*>(pv2);
void * must be static_cast before storing in int *, etc.
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17. Templates Excellent for embedded systems work
No runtime overhead for inline operations
Sometimes performance matters
No memory used for unused operations
In embedded systems memory is often critical (limited)
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18. How to live with failing hardware
Failing how?
In general, we cannot know
In practice, we can assume that some kinds of errors are more common than others
But sometimes a memory bit just decides to change (cosmic ray, silicon fatigue, …)
Why?
Power surges/failure
The connector vibrated out of its socket
Falling debris
Falling computer
X-rays …
Transient errors are the worst
E.g., only when the temperature exceeds 100° F. and the cabinet door is closed
Errors that occur away from the lab are the worst
E.g., on Mars
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19. How to live with failing hardware
Replicate
In emergency, use a spare
Self-check
Know when the program (or hardware) is misbehaving
Have a quick way out of misbehaving code
Make systems modular
Have some other module, computer, part of the system responsible for serious errors
In the end, maybe a person i.e., manual override
Remember HAL ?
Monitor (sub)systems
In case they can’t/don’t notice problems themselves
Replicated navigation computers in space shuttle
“Limp home” mode for automobile control computers
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20. Absolute addresses
Physical resources (e.g., control registers for external devices) and their most basic software controls typically exist at specific addresses in a low-level system (e.g., memory-mapped I/O)
We have to enter such addresses into our programs and give a type to such data
For example
Device_driver* p
= reinterpret_cast<Device_driver*>(0xffb8);
Serial_port_base* Com1
= reinterpret_cast<Serial_port_base*>(0x3f8);
Stroustrup/Programming Nov'13

21. Bit manipulation: Unsigned integers
How do you represent a set of bits in C++?
unsigned char uc; // 8 bits
unsigned short us; // typically 16 bits
unsigned int ui; // typically 16 bits or 32 bits // (check before using) // many embedded systems have 16-bit ints
unsigned long int ul; // typically 32 bits or 64 bits
std::vector<bool> vb(93); // 93 bits
true/false auto-converts to/from 1/0
Use only if you really need more than 32 bits
std::bitset bs(314); // 314 bits
Use if you really need more than 32 bits
Typically efficient for multiples of sizeof(int)
In C, 2  sizeof(short)  sizeof(int)  sizeof(long), I think, and so the sizes vary from compiler to compiler. Thus the program should check how many bytes a type contains to avoid portability problems.
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22. Bit manipulation & and | inclusive or ^ exclusive or1 1 1 1
0xaa b:
& and
| inclusive or
^ exclusive or
<< left shift
>> right shift
~ one’s complement 1 1 1 1
0x0f
a&b:
0x0a 1 1
a|b:
0xaf 1 1 1 1 1 1
a^b:
0xa5 1 1 1 1
a<<1:
0x54 1 1 1
b>>2:
0x03 1 1
~b:
0xf0 1 1 1 1
Stroustrup/Programming Nov'13

23. Bit manipulation Bitwise operations For example
Sign bit
Bitwise operations
& (and)
| (or)
^ (exclusive or – xor)
<< (left shift)
>> (right shift)
~ (one's complement)
Basically, what the hardware provides right:
For example
void f(unsigned short val) // assume 16-bit, 2-byte unsigned short integer {
unsigned char right = val & 0xff ; // rightmost (least significant) byte
unsigned char left = (val>>8) & 0xff ; // leftmost (most significant) byte
bool negative = val & 0x8000 ; // sign bit (if 2’s complement)
// … }
8 bits == 1 byte
val 1 1 1 1 1 1 1 1
0xff: 1 1 1 1 1 1 1 1 1 1 1 1
true
false
Stroustrup/Programming Nov'13

24. Bit manipulation Or | And & For example:
Set a bit (whether or not already set)
And &
Is a bit set? Select (mask) some bits
For example:
enum Flags { bit4=1<<4, bit3=1<<3, bit2=1<<2, bit1=1<<1, bit0=1 };
unsigned char x = bit3 | bit1; // x becomes 8+2
x |= bit2; // x becomes 8+4+2
if (x & bit3) { // is bit3 set? (yes, it is)
// … }
unsigned char y = x & (bit4 | bit2); // y becomes 4
Flags z = Flags(bit2 | bit0); // the cast is necessary because the compiler
// doesn’t know that 5 is in the Flags range
0xff: 1 1 1 1 1 1 1 1
val 1 1 1 1
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25. Bit manipulation Exclusive or (xor) ^
a^b means (a|b) & !(a&b) “either a or b but not both”
unsigned char a = 0xaa;
unsigned char b = 0x0f;
unsigned char c = a^b;
Immensely important in graphics and cryptography a: 1 1 1 1
0xaa b: 1 1 1 1
0x0f
a^b:
0xa5 1 1 1 1
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26. Unsigned integers You can do ordinary arithmetic on unsigned integers
Avoid that when you can
Try never to use unsigned just to get another bit of precision
If you need one extra bit, soon, you’ll need another
Don’t mix signed and unsigned in an expression
int x = -2;// a negative number
unsigned int y = x;// a very large positive number
if (x < 1) cout << "no surprise: x<1\n";
if (y < 1) cout << "y<1\n"; else cout << "surprise? not y<1\n";
if (-3 < x) cout << "no surprise: -3<x\n";
if (-3 < y) cout << "surprise? -3<y\n";
if (3 < y) cout << "surprise? 3<y\n";
Stroustrup/Programming Nov'13

27. Unsigned integers You can do ordinary arithmetic on unsigned integers
You can’t completely avoid unsigned arithmetic
Indexing into standard library containers uses unsigned (in my opinion, that’s a design error; arrays use signed ints)
vector<int> v;
// …
for (int i = 0; i<v.size(); ++i) …
for (unsigned int i = 0; i<v.size(); ++i) …
for (vector<int>::size_type i = 0; i<v.size(); ++i) …
for (vector<int>::iterator p = v.begin(); p!=v.end(); ++p) …
for (auto p = v.begin(); p!=v.end(); ++p) …
for (auto i = 0; i<v.size(); ++i) …
for (int x : v) …
unsigned
signed
correct, but pedantic
A C++11 way
signed
Yet another C++11 way
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28. Complexity One source of errors is complicated problems
Inherent complexity
Another source of errors is poorly-written code
Incidental complexity
Reasons for unnecessarily complicated code
Overly clever programmers
Who use features they don’t understand
Undereducated programmers
Who don’t use the most appropriate features
Large variations in programming style
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29. Coding standards
A coding standard is a set of rules for what code should look like
Typically specifying naming and indentation rules
E.g., use “Stroustrup” layout
Typically specifying a subset of a language
E.g., don’t use new or throw (to avoid predictability problems)
Typically specifying rules for commenting
Every function must have a comment explaining what it does
Often requiring the use of certain libraries
E.g., use <iostream> rather than <stdio.h> to avoid safety problems
Organizations often try to manage complexity through coding standards
Often they fail and create more complexity than they manage
Stroustrup/Programming Nov'13

30. Coding standards A good coding standard is better than no standard
I wouldn’t start a major (multi-person, multi-year) industrial project without one
A poor coding standard can be worse than no standard
C++ coding standards that restrict programming to something like the C subset do harm
They are not uncommon
All coding standards are disliked by programmers
Even the good ones
All programmers want to write their code exactly their own way
A good coding standard is prescriptive as well as restrictive
“Here is a good way of doing things” as well as
“Never do this”
A good coding standard gives rationales for its rules
And examples
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31. Coding standards Common aims Reliability Portability Maintainability
Testability
Reusability
Extensibility
Readability
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32. Some sample rules
No function shall have more than 200 lines (30 would be even better)
that is, 200 non-comment source lines
Each new statement starts on a new line
E.g., int a = 7; x = a+7; f(x,9); // violation!
No macros shall be used except for source control
using #ifdef and #ifndef
Identifiers should be given descriptive names
May contain common abbreviations and acronyms
When used conventionally, x, y, i, j, etc., are descriptive
Use the number_of_elements style rather than the numberOfElements style
Type names and constants start with a capital letter
E.g., Device_driver and Buffer_pool
Identifiers shall not differ only by case
E.g., Head and head // violation!
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33. Some more sample rules
Identifiers in an inner scope should not be identical to identifiers in an outer scope
E.g., int var = 9; { int var = 7; ++var; } // violation: var hides var
Declarations shall be declared in the smallest possible scope
Variables shall be initialized
E.g., int var; // violation: var is not initialized
Casts should be used only when essential
Code should not depend on precedence rules below the level of arithmetic expressions
E.g., x = a*b+c; // ok
if( a<b || c<=d) // violation: parenthesize (a<b) and (c<=d)
Increment and decrement operations shall not be used as subexpressions
E.g., int x = v[++i]; // violation (that increment might be overlooked)
Stroustrup/Programming Nov'13

34. An example of bit manipulation
The Tiny Encryption Algorithm (TEA)
Originally by David Wheeler
Don’t look too hard at the code (unless you happen to need a good simple encryption algorithm for an application); it’s simply to give you the flavor of some bit manipulation code
It takes one word (4 bytes at a time)
E.g., 4 characters from a string or an image file
It assumes 4-byte long integers
Explanation is at the link (and in the book)
Without the explanation this is just an example of how bit manipulation code can look. This code is not meant to be self-explanatory.
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35. TEA
void encipher( const unsigned long *const v, unsigned long *const w, const unsigned long * const k) { unsigned long y = v[0]; unsigned long z = v[1]; unsigned long sum = 0; unsigned long delta = 0x9E3779B9; unsigned long n = 32; while(n-->0) { y += (z << 4 ^ z >> 5) + z ^ sum + k[sum&3]; sum += delta; z += (y << 4 ^ y >> 5) + y ^ sum + k[sum>>11 & 3]; } w[0]=y; w[1]=z;
Stroustrup/Programming Nov'13

36. TEA
void decipher( const unsigned long *const v, unsigned long *const w, const unsigned long * const k) { unsigned long y = v[0]; unsigned long z = v[1]; unsigned long sum = 0xC6EF3720; unsigned long delta = 0x9E3779B9; unsigned long n = 32; // sum = delta<<5; in general, sum = delta * n while(n-->0) { z -= (y << 4 ^ y >> 5) + y ^ sum + k[sum>>11 & 3]; sum -= delta; y -= (z << 4 ^ z >> 5) + z ^ sum + k[sum&3]; } w[0]=y; w[1]=z;
Stroustrup/Programming Nov'13