Modularity3

Namespaces

In addition to functions (§1.3), classes (§2.3), and enumerations (§2.5), C++ offers namespaces as a mechanism for expressing that some declarations belong together and that their names shouldn’t clash with other names. For example, I might want to experiment with my own complex number type (§4.2.1, §14.4):

namespace My_code {
class complex {
// ...
};
complex sqr t(complex);
// ...
int main();
}
int My_code::main()
{
complex z {1,2};
auto z2 = sqrt(z);
std::cout << '{' << z2.real() << ',' << z2.imag() << "}\n";
// ...
}
int main()
{
return My_code::main();
}

By putting my code into the namespace My_code, I make sure that my names do not conflict with the standard-library names in namespace std (§3.4).

That precaution is wise, because the standard library does provide support for complex arithmetic (§4.2.1, §14.4). The simplest way to access a name in another namespace is to qualify it with the namespace name (e.g., std::cout and My_code::main). The ‘‘real main()’’ is defined in the global namespace, that is, not local to a defined namespace, class, or function. If repeatedly qualifying a name becomes tedious or distracting, we can bring the name into a scope with a using-declaration:

void my_code(vector<int>& x, vector<int>& y)
{
using std::swap; // use the standard-librar y sw ap
// ...
swap(x,y); // std::swap()
other::swap(x,y); // some other swap()
// ...
}

A using-declaration makes a name from a namespace usable as if it was declared in the scope in which it appears. After using std::swap, it is exactly as if swap had been declared in my_code(). To gain access to all names in the standard-library namespace, we can use a using-directive:

using namespace std;

A using-directive makes unqualified names from the named namespace accessible from the scope in which we placed the directive. So after the using-directive for std, we can simply write cout rather than std::cout. By using a using-directive, we lose the ability to selectively use names from that namespace, so this facility should be used carefully, usually for a library that’s pervasive in an application (e.g., std) or during a transition for an application that didn’t use namespaces. Namespaces are primarily used to organize larger program components, such as libraries. They simplify the composition of a program out of separately developed parts.

Error Handling

Error handling is a large and complex topic with concerns and ramifications that go far beyond language facilities into programming techniques and tools. However, C++ provides a few features to help. The major tool is the type system itself. Instead of painstakingly building up our applications from the built-in types (e.g., char, int, and double) and statements (e.g., if, while , and for), we build types (e.g., string, map, and reg ex) and algorithms (e.g., sor t(), find_if(), and draw_all()) that are appropriate for our applications. Such higher-level constructs simplify our programming, limit our opportunities for mistakes (e.g., you are unlikely to try to apply a tree traversal to a dialog box), and increase the compiler’s chances of catching errors. The majority of C++ language constructs are dedicated to the design and implementation of elegant and efficient abstractions (e.g., user-defined types and algorithms using them). One effect of such abstraction is that the point where a run-time error can be detected is separated from the point where it can be handled. As programs grow, and especially when libraries are used extensively, standards for handling errors become important. It is a good idea to articulate a strategy for error handling early on in the development of a program.

Exceptions

Consider again the Vector example. What ought to be done when we try to access an element that is out of range for the vector from §2.3?

• The writer of Vector doesn’t know what the user would like to hav e done in this case (the writer of Vector typically doesn’t even know in which program the vector will be running).
The user of Vector cannot consistently detect the problem (if the user could, the out-of-range access wouldn’t happen in the first place).

Assuming that out-of-range access is a kind of error that we want to recover from, the solution is for the Vector implementer to detect the attempted out-of-range access and tell the user about it. The user can then take appropriate action. For example, Vector::operator can detect an attempted out-of-range access and throw an out_of_rang e exception:

double& Vector::operator[](int i)
{
if (i<0 || size()<=i)
throw out_of_rang e{"Vector::operator[]"};
return elem[i];
}

The throw transfers control to a handler for exceptions of type out_of_rang e in some function that directly or indirectly called Vector::operator. To do that, the implementation will unwind the function call stack as needed to get back to the context of that caller. That is, the exception handling mechanism will exit scopes and functions as needed to get back to a caller that has expressed interest in handling that kind of exception, invoking destructors (§4.2.2) along the way as needed. For example:

void f(Vector& v)
{
// ...
tr y { // exceptions here are handled by the handler defined below
v[v.siz e()] = 7; // tr y to access beyond the end of v
}
catch (out_of_rang e& err) { // oops: out_of_range error
// ... handle range error ...
cerr << err.what() << '\n';
}
// ...
}

We put code for which we are interested in handling exceptions into a tr y-block. The attempted assignment to v[v.siz e()] will fail. Therefore, the catch-clause providing a handler for exceptions of type out_of_rang e will be entered. The out_of_rang e type is defined in the standard library (in ) and is in fact used by some standard-library container access functions. I caught the exception by reference to avoid copying and used the what() function to print the error message put into it at the throw-point. Use of the exception-handling mechanisms can make error handling simpler, more systematic, and more readable. To achieve that, don’t overuse tr y-statements. The main technique for making error handling simple and systematic (called Resource Acquisition Is Initialization; RAII) is explained in §4.2.2. The basic idea behind RAII is for a constructor to acquire all resources necessary for a class to operate and have the destructor release all resources, thus making resource release guaranteed and implicit.

A function that should never throw an exception can be declared noexcept. For example:

void user(int sz) noexcept
{
Vector v(sz);
iota(&v[0],&v[sz],1); // fill v with 1,2,3,4... (see §14.3)
// ...
}

If all good intent and planning fails, so that user() still throws, std::terminate() is called to immediately terminate the program.

Invariants

The use of exceptions to signal out-of-range access is an example of a function checking its argument and refusing to act because a basic assumption, a precondition, didn’t hold. Had we formally specified Vector’s subscript operator, we would have said something like ‘‘the index must be in the [0:siz e()) range,’’ and that was in fact what we tested in our operator. The [a:b) notation specifies a half-open range, meaning that a is part of the range, but b is not. Whenever we define a function, we should consider what its preconditions are and consider whether to test them (§3.5.3). For most applications it is a good idea to test simple invariants; see also §3.5.4.

However, operator operates on objects of type Vector and nothing it does makes any sense unless the members of Vector have ‘‘reasonable’’ values. In particular, we did say ‘‘elem points to an array of sz doubles’’ but we only said that in a comment. Such a statement of what is assumed to be true for a class is called a class invariant, or simply an invariant. It is the job of a constructor to establish the invariant for its class (so that the member functions can rely on it) and for the member functions to make sure that the invariant holds when they exit. Unfortunately, our Vector constructor only partially did its job. It properly initialized the Vector members, but it failed to check that the arguments passed to it made sense. Consider:

Vector v(−27);

This is likely to cause chaos.

Here is a more appropriate definition:

Vector::Vector(int s)
{
if (s<0)
throw length_error{"Vector constructor: negative size"};
elem = new double[s];
sz = s;
}

I use the standard-library exception length_error to report a non-positive number of elements because some standard-library operations use that exception to report problems of this kind. If operator new can’t find memory to allocate, it throws a std::bad_alloc. We can now write:

void test()
{
tr y {
Vector v(−27);
}
catch (std::length_error& err) {
// handle negative size
}
catch (std::bad_alloc& err) {
// handle memory exhaustion
}
}

You can define your own classes to be used as exceptions and have them carry arbitrary information from a point where an error is detected to a point where it can be handled (§3.5.1). Often, a function has no way of completing its assigned task after an exception is thrown. Then, ‘‘handling’’ an exception means doing some minimal local cleanup and rethrowing the exception. For example:

void test()
{
tr y {
Vector v(−27);
}
catch (std::length_error&) { // do something and rethrow
cerr << "test failed: length error\n";
throw; // rethrow
}
catch (std::bad_alloc&) { // Ouch! this program is not designed to handle memory exhaustion
std::terminate(); // ter minate the program
}
}

In well-designed code tr y-blocks are rare. Av oid overuse by systematically using the RAII technique (§4.2.2, §5.3). The notion of invariants is central to the design of classes, and preconditions serve a similar role in the design of functions. Invariants

help us to understand precisely what we want
force us to be specific; that gives us a better chance of getting our code correct (after debugging and testing).

The notion of invariants underlies C++’s notions of resource management supported by constructors (Chapter 4) and destructors (§4.2.2, §13.2)

Error-Handling Alternatives

Error handling is a major issue in all real-world software, so naturally there are a variety of approaches. If an error is detected and it cannot be handled locally in a function, the function must somehow communicate the problem to some caller. Throwing an exception is C++’s most general mechanism for that.

There are languages where exceptions are designed simply to provide an alternate mechanism for returning values. C++ is not such a language: exceptions are designed to be used to report failure to complete a given task. Exceptions are integrated with constructors and destructors to provide a coherent framework for error handling and resource management (§4.2.2, §5.3). Compilers are optimized to make returning a value much cheaper than throwing the same value as an exception. Throwing an exception is not the only way of reporting an error that cannot be handled locally.

A function can indicate that it cannot perform its allotted task by:

throwing an exception
somehow return a value indicating failure
terminating the program (by invoking a function like terminate(), exit(), or abor t())

We return an error indicator (an ‘‘error code’’) when:

urn an error indicator (an ‘‘error code’’) when: • A failure is normal and expected. For example, it is quite normal for a request to open a file to fail (maybe there is no file of that name or maybe the file cannot be opened with the permissions requested).
An immediate caller can reasonably be expected to handle the failure.

We throw an exception when:

An error is so rare that a programmer is likely to forget to check for it. For example, when did you last check the return value of printf()?
An error cannot be handled by an immediate caller. Instead, the error has to percolate back to an ultimate caller. For example, it is infeasible to have every function in an application reliably handle every allocation failure or network outage.
New kinds of errors can be added in lower-modules of an application so that higher-level modules are not written to cope with such errors. For example, when a previously singlethreaded application is modified to use multiple threads or resources are placed remotely to be accessed over a network.
The return path of a function is made more complicated or expensive by a need to pass both a value and an error indicator back (e.g., a pair; §13.4.3 ), possibly leading to the use of outparameters, non-local error-status indicators, or other workarounds.
The error has to be transmitted up a call chain to an ‘‘ultimate caller.’’ Repeatedly checking an error-code would be tedious, expensive, and error-prone.
The recovery from errors depends on the results of several function calls, leading to the need to maintain local state between calls and complicated control structures.
The function that found the error was a callback (a function argument), so the immediate caller may not even know what function was called
An error implies that some ‘‘undo action’’ is needed.

We terminate when

An error is of a kind from which we cannot recover. For example, for many – but not all – systems there is no reasonable way to recover from memory exhaustion
The system is one where error-handling is based on restarting a thread, process, or computer whenever a non-trivial error is detected.

One way to ensure termination is to add noexcept to a function so that a throw from anywhere in the function’s implementation will turn into a terminate(). Note that there are applications that can’t accept unconditional terminations, so alternatives must be used.

Unfortunately, these conditions are not always logically disjoint and easy to apply. The size and complexity of a program matters. Sometimes the tradeoffs change as an application evolves. Experience is required. When in doubt, prefer exceptions because their use scales better, and don’t require external tools to check that all errors are handled.

Don’t believe that all error codes or all exceptions are bad; there are clear uses for both. Furthermore, do not believe the myth that exception handling is slow; it is often faster than correct handling of complex or rare error conditions, and of repeated tests of error codes.

RAII (§4.2.2, §5.3) is essential for simple and efficient error-handling using exceptions. Code littered with tr y-blocks often simply reflects the worst aspects of error-handling strategies conceived for error codes.

Contracts

There is currently no general and standard way of writing optional run-time tests of invariants, preconditions, etc. A contract mechanism is proposed for C++20 [Garcia,2016] [Garcia,2018]. The aim is to support users who want to rely on testing to get programs right – running with extensive run-time checks – but then deploy code with minimal checks. This is popular in high-performance applications in organizations that rely on systematic and extensive checking.

For now, we hav e to rely on ad hoc mechanisms. For example, we could use a command-line macro to control a run-time check:

double& Vector::operator[](int i)
{
if (RANGE_CHECK && (i<0 || size()<=i))
throw out_of_rang e{"Vector::operator[]"};
return elem[i];
}

The standard library offers the debug macro, asser t(), to assert that a condition must hold at run time. For example:

void f(const char∗ p)
{
assert(p!=nullptr); // p must not be the nullptr
// ...
}

If the condition of an asser t() fails in ‘‘debug mode,’’ the program terminates. If we are not in debug mode, the asser t() is not checked. That’s pretty crude and inflexible, but often sufficient.

Static Assertions

Exceptions report errors found at run time. If an error can be found at compile time, it is usually preferable to do so. That’s what much of the type system and the facilities for specifying the interfaces to user-defined types are for. Howev er, we can also perform simple checks on most

properties that are known at compile time and report failures to meet our expectations as compiler error messages. For example:

static_asser t(4<=sizeof(int), "integers are too small"); // check integer size

This will write integ ers are too small if 4<=siz eof(int) does not hold; that is, if an int on this system does not have at least 4 bytes. We call such statements of expectations assertions. The static_asser t mechanism can be used for anything that can be expressed in terms of constant expressions (§1.6). For example:

constexpr double C = 299792.458; // km/s
void f(double speed)
{
constexpr double local_max = 160.0/(60∗60); // 160 km/h == 160.0/(60*60) km/s
static_asser t(speed<C,"can't go that fast"); // error : speed must be a constant
static_asser t(local_max<C,"can't go that fast"); // OK
// ...
}

In general, static_asser t(A,S) prints S as a compiler error message if A is not true. If you don’t want a specific message printed, leave out the S and the compiler will supply a default message:

static_asser t(4<=sizeof(int)); // use default message

The default message is typically the source location of the static_asser t plus a character representation of the asserted predicate. The most important uses of static_asser t come when we make assertions about types used as parameters in generic programming (§7.2, §13.9).

Function Arguments and Return Values

The primary and recommended way of passing information from one part of a program to another is through a function call. Information needed to perform a task is passed as arguments to a function and the results produced are passed back as return values. For example:

int sum(const vector<int>& v)
{
int s = 0;
for (const int i : v)
s += i;
return s;
}
vector fib = {1,2,3,5,8,13,21};
int x = sum(fib); // x becomes 53

There are other paths through which information can be passed between functions, such as global variables (§1.5), pointer and reference parameters (§3.6.1), and shared state in a class object (Chapter 4). Global variables are strongly discouraged as a known source of errors, and state should typically be shared only between functions jointly implementing a well-defined abstraction (e.g., member functions of a class; §2.3).

Given the importance of passing information to and from functions, it is not surprising that there are a variety of ways of doing it. Ke y concerns are:

Is an object copied or shared?
If an object is shared, is it mutable?
Is an obejct moved, leaving an “empty obejct” behind?

The default behiavior for both argument passing and value return is “copy”, but some copies can implicitly be optimizaed to mvoes.

In the sum() example, the resulting int is copied out of sum() but it would be inefficient and pointless to copy potentially very large vector into sum(), so the argument is passed by reference

The sum() has no reason to modify its argument. THis immutability is indicated by declearing the vector argument const. so the vector is passed by const-refernce.

Argument Passing

FIrst consider how to get values into a function. By default we copy(“pass-by-value”) and if we want to refer to an object int the caller’s enviroment, we use a reference(“pass-by-reference”).

For Example:

void test(vector<int> v, vector<int>& rv) // v is passed by value; rv is passed by reference
{
    v[1] = 99; //modify v(a local variable)
    rv[2] = 66; //modify whatever rv refers to
}

int main()
{
    vector fib = {1,2,3,5,8,13,21};
    test(fib,fib);
    cout<<fib[1]<<''<<fib[2]<<'\n'; //prints 2 66
}

When we care about performance, we usually pass small values by-value and lager ones by-reference. Here “small “ means “something that’s really cheap to copy” Exactly what “small”meas depends on machine architecture, but “the size of two or three pointers or less” is a good rule of thumb.

If we want to pass by reference for performance reasons but don’t need to modify the argument, we pass-by-const-refernce as in the sum() example. This is by far the most common case in ordinary good code: it is fast and not errorpprone.

It is not uncommon for a function arguemnt to have default value; that is , a value that is considered prefered or just hte most common. We can specify such a adefailt by a default function argument. For Example:

void print(int value , int base =10); // pr int value in base "base"
print(x,16); // hexadecimal
print(x,60); // sexagesimal (Sumerian)
print(x); // use the dafault: decimal

This is a notationally simpler alternative to overloading:

void print(int value , int base); // pr int value in base "base"
void print(int value) // pr int value in base 10
{
print(value ,10);
}

Value Return

Once we have computed a result, we need to get it out of the function and back to the caller. Again, the default for value return is to copy and for small objects that’s ideal. We return ‘‘by reference’’ only when we want to grant a caller access to something that is not local to the function. For example:

class Vector {
public:
// ...
double& operator[](int i) { return elem[i]; } // retur n reference to ith element
private:
double∗ elem; // elem points to an array of sz
// ...
};

The ith element of a Vector exists independently of the call of the subscript operator, so we can return a reference to it. On the other hand, a local variable disappears when the function returns, so we should not return a pointer or reference to it:

int& bad()
{
int x;
// ...
return x; // bad: return a reference to the local var iable x
}

Fortunately, all major C++ compilers will catch the obvious error in bad(). Returning a reference or a value of a ‘‘small’’ type is efficient, but how do we pass large amounts of information out of a function? Consider:

Matrix operator+(const Matrix& x, const Matrix& y)
{
Matrix res;
// ... for all res[i,j], res[i,j] = x[i,j]+y[i,j] ...
return res;
}
Matrix m1, m2;
// ...
Matrix m3 = m1+m2; // no copy

A Matrix may be very large and expensive to copy even on modern hardware. So we don’t copy, we give Matrix a move constructor (§5.2.2) and very cheaply move the Matrix out of operator+(). We do not need to regress to using manual memory management:

Matrix∗ add(const Matrix& x, const Matrix& y) // complicated and error-prone 20th century style
{
Matrix∗ p = new Matrix;
// ... for all *p[i,j], *p[i,j] = x[i,j]+y[i,j] ...
return p;
}
Matrix m1, m2;
// ...
Matrix∗ m3 = add(m1,m2); // just copy a pointer
// ...
delete m3; // easily forgotten

Unfortunately, returning large objects by returning a pointer to it is common in older code and a major source of hard-to-find errors. Don’t write such code. Note that operator+() is as efficient as add(), but far easier to define, easier to use, and less error-prone. If a function cannot perform its required task, it can throw an exception (§3.5.1). This can help avoid code from being littered with error-code tests for ‘‘exceptional problems.’’ The return type of a function can be deduced from its return value. For example:

auto mul(int i, double d) { return i∗d; } // here, "auto" means "deduce the return type"

This can be convenient, especially for generic functions (function templates; §6.3.1) and lambdas (§6.3.3), but should be used carefully because a deduced type does not offer a stable interface: a change to the implementation of the function (or lambda) can change the type.

Structured Binding

A function can return only a single value, but that value can be a class object with many members. This allows us to efficiently return many values. For example:

struct Entry {
string name;
int value;
};

Entry read_entry(istream& is) // naive read function (for a better version, see §10.5)
{
string s;
int i;
is >> s >> i;
return {s,i};
}
auto e = read_entry(cin);
cout << "{ " << e.name << " , " << e.value << " }\n";

Here, {s,i} is used to construct the Entr y return value. Similarly, we can ‘‘unpack’’ an Entr y’s members into local variables:

auto [n,v] = read_entry(is);
cout << "{ " << n << " , " << v << " }\n";

The auto [n,v] declares two local variables n and v with their types deduced from read_entr y()’s return type. This mechanism for giving local names to members of a class object is called structured binding. Consider another example:

map<string,int> m;
// ... fill m ...
for (const auto [key,value] : m)
cout << "{" << key "," << value << "}\n";

As usual, we can decorate auto with const and &. For example

void incr(map<string,int>& m) // increment the value of each element of m
{
for (auto& [key,value] : m)
++value;
}

When structured binding is used for a class with no private data, it is easy to see how the binding is done: there must be the same number of names defined for the binding as there are nonstatic data members of the class, and each name introduced in the binding names the corresponding member. There will not be any difference in the object code quality compared to explicitly using a composite object; the use of structured binding is all about how best to express an idea. It is also possible to handle classes where access is through member functions. For example:

complex<double> z = {1,2};
auto [re,im] = z+2; // re=3; im=2

A complex has two data members, but its interface consists of access functions, such as real() and imag(). Mapping a complex to two local variables, such as re and im is feasible and efficient, but the technique for doing so is beyond the scope of this book.

Modularity 3