Problem:

Using templates can lead to code bloat: binaries with replicated (or almost replicated) code, data, or both.
The result can be source code that looks fit and trim, yet object code that’s fat and flabby. Fat and flabby is rarely fashionable, so you need to know how to avoid such binary bombast.

Solution:

Your primary tool has the imposing name commonality and variability analysis.

Non-template code

When you’re writing a function and you realize that some part of the function’s implementation is essentially the same as another function’s implementation, do you just replicate the code?
Of course not. You factor the common code out of the two functions, put it into a third function, and have both of the other functions call the new one.
Similarly, if you’re writing a class and you realize that some parts of the class are the same as parts of another class, you don’t replicate the common parts. Instead, you move the common parts to a new class, then you use inheritance or composition (see Items 32, 38, and 39) to give the original classes access to the common features.

Template code

In non-template code, replication is explicit: you can see that there’s duplication between two functions or two classes. In template code, replication is implicit: there’s only one copy of the template source code, so you have to train yourself to sense the replication that may take place when a template is instantiated multiple times.

Example:

template<typename T, 		// template for n x n matrices of
			std::size_t n>	// objects of type T; see below for info
class SquareMatrix { 		// on the size_t parameter
public:
	...
	void invert();			// invert the matrix in place
};

SquareMatrix<double, 5> sm1; 
...
sm1.invert();		// call SquareMatrix<double, 5>::invert
SquareMatrix<double, 10> sm2; 
...
sm2.invert();		// call SquareMatrix<double, 10>::invert

Two copies of invert will be instantiated here. The functions won’t be identical, because one will work on 5 ×5 matrices and one will work on 10 ×10 matrices, but other than the constants 5 and 10, the two functions will be the same. This is a classic way for template-induced code bloat to arise.

Solution

template<typename T> 
class SquareMatrixBase { 	// size-independent base class for
protected:					// square matrices
	...
	void invert(std::size_t matrixSize); // invert matrix of the given size
	...
};
template<typename T, std::size_t n>
class SquareMatrix: private SquareMatrixBase<T> { 
private:
	using SquareMatrixBase<T>::invert;	// make base class version of invert
										// visible in this class; see Items 33
										// and 43
public: 
	...
	void invert() { invert(n); }		// make implicit inline call to 
										// base class version of invert
};

They will thus share a single copy of that class’s version of invert. (Provided, of course, you refrain from declaring that function inline. If it’s inlined, each instantiation of SquareMatrix::invert will get a copy of SquareMatrixBase::invert’s code, and you’ll find yourself back in the land of object code replication). The additional cost of calling it should be zero, because derived classes’ inverts call the base class version using inline functions. (The inline is implicit — see Item 30.)

How does SquareMatrixBase::invert know what data to operate on?

• One possibility would be to add another parameter to SquareMatrixBase::invert
  That would work, but in all likelihood, invert is not the only function in SquareMatrix that can be written in a size-independent manner and moved into SquareMatrixBase. We could add an extra parameter to all of them, but it is wrong to tell SquareMatrixBase the same information repeatedly.

• An alternative is to have SquareMatrixBase store a pointer to the memory for the matrix values

  template<typename T> 
  class SquareMatrixBase { 
  protected:
  	SquareMatrixBase(std::size_t n, T *pMem) // store matrix size and a 
  	: size(n), pData(pMem) {}				// ptr to matrix values
  	void setDataPtr(T *ptr) { pData = ptr; }// reassign pData
  	...
  private: 
  	std::size_t size;						// size of matrix
  	T *pData;								// pointer to matrix values
  };
  
  template<typename T, std::size_t n>
  class SquareMatrix: private SquareMatrixBase<T> { 
  public:
  	SquareMatrix()							// send matrix size and
  	: SquareMatrixBase<T>(n, data) {} ...	// data ptr to base class
  private:
  	T data[n*n];
  };
  

  Objects of such types have no need for dynamic memory allocation, but the objects themselves could be very large. An alternative would be to put the data for each matrix on the heap

  template<typename T, std::size_t n>
  class SquareMatrix: private SquareMatrixBase<T> { 
  public:
  	SquareMatrix( )					// set base class data ptr to null,
  	: SquareMatrixBase<T>(n,0),			// allocate memory for matrix
  	  pData(new T[n*n])					// values, save a ptr to the
  	{ this->setDataPtr(pData.get()); } 	// memory, and give a copy of it
  	...									// to the base class
  private:
  	boost::scoped_array<T> pData;		// see Item 13 for info on
  };										// boost::scoped_array
  

Tradeoff

1. Certain Optimization vs. decrease the size of executable
   • For previous size-specific version, the versions of invert with the matrix sizes hardwired into them are likely to generate better code than the shared version where the size is passed as a function parameter or is stored in the object. For example, in the size-specific versions, the sizes would be compiletime constants, hence eligible for such optimizations as constant propagation, including their being folded into the generated instructions as immediate operands. That can’t be done in the size-independent version.
   • having only one version of invert for multiple matrix sizes decreases the size of the executable, and that could reduce the program’s working set size and improve locality of reference in the instruction cache
2. Another efficiency consideration concerns the sizes of objects.
   If you’re not careful, moving size-independent versions of functions up into a base class can increase the overall size of each object.
   For example, each SquareMatrix object has a pointer to its data in the SquareMatrixBase class, even though each derived class already has a way to get to the data. This increases the size of each SquareMatrix object by at least the size of a pointer.
   It’s possible to modify the design so that these pointers are unnecessary

Bloat on type parameters

This Item has discussed only bloat due to non-type template parame- ters, but type parameters can lead to bloat, too.
For example, on many platforms, intand long have the same binary representation, so the member functions for, say, vector<int> and vector<long> would likely be identical — the very definition of bloat. Some linkers will merge identical function implementations, but some will not, and that means that some templates instantiated on both int and long could cause code bloat in some environments.

For Pointer
all pointer types have the same binary representation, so templates holding pointer types (e.g., list<int*>, list<const int*>, list<SquareMatrix<long, 3>*>, etc.) should often be able to use a single underlying implementation for each member function.
Typically, this means implementing member functions that work with strongly typed pointers (i.e., T* pointers) by having them call functions that work with untyped pointers (i.e., void* pointers)

Things to Remember

• Templates generate multiple classes and multiple functions, so any template code not dependent on a template parameter causes bloat.
• Bloat due to non-type template parameters can often be eliminated by replacing template parameters with function parameters or class data members.
• Bloat due to type parameters can be reduced by sharing implementations for instantiation types with identical binary representations.

标签：templates,independent,code,SquareMatrixBase,invert,template,class,size
来源： https://blog.csdn.net/weixin_45360983/article/details/100151913