- •Thinking in C++ 2nd edition Volume 2: Standard Libraries & Advanced Topics
- •Preface
- •What’s new in the second edition
- •What’s in Volume 2 of this book
- •How to get Volume 2
- •Prerequisites
- •Learning C++
- •Goals
- •Chapters
- •Exercises
- •Exercise solutions
- •Source code
- •Language standards
- •Language support
- •The book’s CD ROM
- •Seminars, CD Roms & consulting
- •Errors
- •Acknowledgements
- •Library overview
- •1: Strings
- •What’s in a string
- •Creating and initializing C++ strings
- •Initialization limitations
- •Operating on strings
- •Appending, inserting and concatenating strings
- •Replacing string characters
- •Concatenation using non-member overloaded operators
- •Searching in strings
- •Finding in reverse
- •Finding first/last of a set
- •Removing characters from strings
- •Stripping HTML tags
- •Comparing strings
- •Using iterators
- •Iterating in reverse
- •Strings and character traits
- •A string application
- •Summary
- •Exercises
- •2: Iostreams
- •Why iostreams?
- •True wrapping
- •Iostreams to the rescue
- •Sneak preview of operator overloading
- •Inserters and extractors
- •Manipulators
- •Common usage
- •Line-oriented input
- •Overloaded versions of get( )
- •Reading raw bytes
- •Error handling
- •File iostreams
- •Open modes
- •Iostream buffering
- •Seeking in iostreams
- •Creating read/write files
- •User-allocated storage
- •Output strstreams
- •Automatic storage allocation
- •Proving movement
- •A better way
- •Output stream formatting
- •Internal formatting data
- •Format fields
- •Width, fill and precision
- •An exhaustive example
- •Formatting manipulators
- •Manipulators with arguments
- •Creating manipulators
- •Effectors
- •Iostream examples
- •Code generation
- •Maintaining class library source
- •Detecting compiler errors
- •A simple datalogger
- •Generating test data
- •Verifying & viewing the data
- •Counting editor
- •Breaking up big files
- •Summary
- •Exercises
- •3: Templates in depth
- •Nontype template arguments
- •Typedefing a typename
- •Using typename instead of class
- •Function templates
- •A string conversion system
- •A memory allocation system
- •Type induction in function templates
- •Taking the address of a generated function template
- •Local classes in templates
- •Applying a function to an STL sequence
- •Template-templates
- •Member function templates
- •Why virtual member template functions are disallowed
- •Nested template classes
- •Template specializations
- •A practical example
- •Pointer specialization
- •Partial ordering of function templates
- •Design & efficiency
- •Preventing template bloat
- •Explicit instantiation
- •Explicit specification of template functions
- •Controlling template instantiation
- •Template programming idioms
- •Summary
- •Containers and iterators
- •STL reference documentation
- •The Standard Template Library
- •The basic concepts
- •Containers of strings
- •Inheriting from STL containers
- •A plethora of iterators
- •Iterators in reversible containers
- •Iterator categories
- •Input: read-only, one pass
- •Output: write-only, one pass
- •Forward: multiple read/write
- •Bidirectional: operator--
- •Random-access: like a pointer
- •Is this really important?
- •Predefined iterators
- •IO stream iterators
- •Manipulating raw storage
- •Basic sequences: vector, list & deque
- •Basic sequence operations
- •vector
- •Cost of overflowing allocated storage
- •Inserting and erasing elements
- •deque
- •Converting between sequences
- •Cost of overflowing allocated storage
- •Checked random-access
- •list
- •Special list operations
- •list vs. set
- •Swapping all basic sequences
- •Robustness of lists
- •Performance comparison
- •A completely reusable tokenizer
- •stack
- •queue
- •Priority queues
- •Holding bits
- •bitset<n>
- •vector<bool>
- •Associative containers
- •Generators and fillers for associative containers
- •The magic of maps
- •A command-line argument tool
- •Multimaps and duplicate keys
- •Multisets
- •Combining STL containers
- •Creating your own containers
- •Summary
- •Exercises
- •5: STL Algorithms
- •Function objects
- •Classification of function objects
- •Automatic creation of function objects
- •Binders
- •Function pointer adapters
- •SGI extensions
- •A catalog of STL algorithms
- •Support tools for example creation
- •Filling & generating
- •Example
- •Counting
- •Example
- •Manipulating sequences
- •Example
- •Searching & replacing
- •Example
- •Comparing ranges
- •Example
- •Removing elements
- •Example
- •Sorting and operations on sorted ranges
- •Sorting
- •Example
- •Locating elements in sorted ranges
- •Example
- •Merging sorted ranges
- •Example
- •Set operations on sorted ranges
- •Example
- •Heap operations
- •Applying an operation to each element in a range
- •Examples
- •Numeric algorithms
- •Example
- •General utilities
- •Creating your own STL-style algorithms
- •Summary
- •Exercises
- •Perspective
- •Duplicate subobjects
- •Ambiguous upcasting
- •virtual base classes
- •The "most derived" class and virtual base initialization
- •"Tying off" virtual bases with a default constructor
- •Overhead
- •Upcasting
- •Persistence
- •MI-based persistence
- •Improved persistence
- •Avoiding MI
- •Mixin types
- •Repairing an interface
- •Summary
- •Exercises
- •7: Exception handling
- •Error handling in C
- •Throwing an exception
- •Catching an exception
- •The try block
- •Exception handlers
- •Termination vs. resumption
- •The exception specification
- •Better exception specifications?
- •Catching any exception
- •Rethrowing an exception
- •Uncaught exceptions
- •Function-level try blocks
- •Cleaning up
- •Constructors
- •Making everything an object
- •Exception matching
- •Standard exceptions
- •Programming with exceptions
- •When to avoid exceptions
- •Not for asynchronous events
- •Not for ordinary error conditions
- •Not for flow-of-control
- •You’re not forced to use exceptions
- •New exceptions, old code
- •Typical uses of exceptions
- •Always use exception specifications
- •Start with standard exceptions
- •Nest your own exceptions
- •Use exception hierarchies
- •Multiple inheritance
- •Catch by reference, not by value
- •Throw exceptions in constructors
- •Don’t cause exceptions in destructors
- •Avoid naked pointers
- •Overhead
- •Summary
- •Exercises
- •8: Run-time type identification
- •The “Shape” example
- •What is RTTI?
- •Two syntaxes for RTTI
- •Syntax specifics
- •Producing the proper type name
- •Nonpolymorphic types
- •Casting to intermediate levels
- •void pointers
- •Using RTTI with templates
- •References
- •Exceptions
- •Multiple inheritance
- •Sensible uses for RTTI
- •Revisiting the trash recycler
- •Mechanism & overhead of RTTI
- •Creating your own RTTI
- •Explicit cast syntax
- •Summary
- •Exercises
- •9: Building stable systems
- •Shared objects & reference counting
- •Reference-counted class hierarchies
- •Finding memory leaks
- •An extended canonical form
- •Exercises
- •10: Design patterns
- •The pattern concept
- •The singleton
- •Variations on singleton
- •Classifying patterns
- •Features, idioms, patterns
- •Basic complexity hiding
- •Factories: encapsulating object creation
- •Polymorphic factories
- •Abstract factories
- •Virtual constructors
- •Destructor operation
- •Callbacks
- •Observer
- •The “interface” idiom
- •The “inner class” idiom
- •The observer example
- •Multiple dispatching
- •Visitor, a type of multiple dispatching
- •Efficiency
- •Flyweight
- •The composite
- •Evolving a design: the trash recycler
- •Improving the design
- •“Make more objects”
- •A pattern for prototyping creation
- •Trash subclasses
- •Parsing Trash from an external file
- •Recycling with prototyping
- •Abstracting usage
- •Applying double dispatching
- •Implementing the double dispatch
- •Applying the visitor pattern
- •More coupling?
- •RTTI considered harmful?
- •Summary
- •Exercises
- •11: Tools & topics
- •The code extractor
- •Debugging
- •Trace macros
- •Trace file
- •Abstract base class for debugging
- •Tracking new/delete & malloc/free
- •CGI programming in C++
- •Encoding data for CGI
- •The CGI parser
- •Testing the CGI parser
- •Using POST
- •Handling mailing lists
- •Maintaining your list
- •Mailing to your list
- •A general information-extraction CGI program
- •Parsing the data files
- •Summary
- •Exercises
- •General C++
- •My own list of books
- •Depth & dark corners
- •Design Patterns
- •Index
Associative containers
The set, map, multiset and multimap are called associative containers because they associate keys with values. Well, at least maps and multimaps associate keys to values, but you can look at a set as a map that has no values, only keys (and they can in fact be implemented this way), and the same for the relationship between multiset and multimap. So, because of the structural similarity sets and multisets are lumped in with associative containers.
The most important basic operations with associative containers are putting things in, and in the case of a set, seeing if something is in the set. In the case of a map, you want to first see if a key is in the map, and if it exists you want the associated value for that key to be returned. Of course, there are many variations on this theme but that’s the fundamental concept. The following example shows these basics:
//: C04:AssociativeBasics.cpp
// Basic operations with sets and maps #include "Noisy.h"
#include <iostream> #include <set> #include <map>
using namespace std;
int main() {
Noisy na[] = { Noisy(), Noisy(), Noisy(), Noisy(), Noisy(), Noisy(), Noisy() };
// Add elements via constructor:
set<Noisy> ns(na, na+ sizeof na/sizeof(Noisy));
//Ordinary insertion: Noisy n;
ns.insert(n); cout << endl;
//Check for set membership:
cout << "ns.count(n)= " << ns.count(n) << endl; if(ns.find(n) != ns.end())
cout << "n(" << n << ") found in ns" << endl; // Print elements:
copy(ns.begin(), ns.end(), ostream_iterator<Noisy>(cout, " "));
cout << endl;
cout << "\n-----------\n"; map<int, Noisy> nm;
for(int i = 0; i < 10; i++)
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nm[i]; // |
Automatically makes pairs |
|
cout << |
"\n |
-----------\n"; |
for(int |
j = |
0; j < nm.size(); j++) |
cout << "nm[" << j <<"] = " << nm[j] << endl;
cout |
<< "\n----------- |
\n"; |
nm[10] = n; |
|
|
cout |
<< "\n----------- |
\n"; |
nm.insert(make_pair(47, n));
cout |
<< |
"\n |
-----------\n"; |
cout |
<< |
"\n |
nm.count(10)= " |
<<nm.count(10) << endl; cout << "nm.count(11)= "
<<nm.count(11) << endl;
map<int, Noisy>::iterator it = nm.find(6); if(it != nm.end())
cout << "value:" << (*it).second
<<" found in nm at location 6" << endl; for(it = nm.begin(); it != nm.end(); it++)
cout << (*it).first << ":"
<<(*it).second << ", ";
cout << "\n----------- |
\n"; |
} ///:~ |
|
The set<Noisy> object ns is created using two iterators into an array of Noisy objects, but there is also a default constructor and a copy-constructor, and you can pass in an object that provides an alternate scheme for doing comparisons. Both sets and maps have an insert( ) member function to put things in, and there are a couple of different ways to check to see if an object is already in an associative container: count( ), when given a key, will tell you how many times that key occurs (this can only be zero or one in a set or map, but it can be more than one with a multiset or multimap). The find( ) member function will produce an iterator indicating the first occurrence (with set and map, the only occurrence) of the key that you give it, or the past-the-end iterator if it can’t find the key. The count( ) and find( ) member functions exist for all the associative containers, which makes sense. The associative containers also have member functions lower_bound( ), upper_bound( ) and
equal_range( ), which actually only make sense for multiset and multimap, as you shall see (but don’t try to figure out how they would be useful for set and map, since they are designed for dealing with a range of duplicate keys, which those containers don’t allow).
Designing an operator[ ] always produces a little bit of a dilemma because it’s intended to be treated as an array-indexing operation, so people don’t tend to think about performing a test before they use it. But what happens if you decide to index out of the bounds of the array? One option, of course, is to throw an exception, but with a map “indexing out of the array” could mean that you want an entry there, and that’s the way the STL map treats it. The first for loop after the creation of the map<int, Noisy> nm just “looks up” objects using the operator[ ], but this is actually creating new Noisy objects! The map creates a new key-value
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pair (using the default constructor for the value) if you look up a value with operator[ ] and it isn’t there. This means that if you really just want to look something up and not create a new entry, you must use count( ) (to see if it’s there) or find( ) (to get an iterator to it).
The for loop that prints out the values of the container using operator[ ] has a number of problems. First, it requires integral keys (which we happen to have in this case). Next and worse, if all the keys are not sequential, you’ll end up counting from 0 to the size of the container, and if there are some spots which don’t have key-value pairs you’ll automatically create them, and miss some of the higher values of the keys. Finally, if you look at the output from the for loop you’ll see that things are very busy, and it’s quite puzzling at first why there are so many constructions and destructions for what appears to be a simple lookup. The answer only becomes clear when you look at the code in the map template for operator[ ], which will be something like this:
mapped_type& operator[] (const key_type& k) { value_type tmp(k,T());
return (*((insert(tmp)).first)).second;
}
Following the trail, you’ll find that map::value_type is:
typedef pair<const Key, T> value_type;
Now you need to know what a pair is, which can be found in <utility>:
template <class T1, class T2> struct pair {
typedef T1 first_type; typedef T2 second_type; T1 first;
T2 second; pair();
pair(const T1& x, const T2& y)
:first(x), second(y) {}
//Templatized copy-constructor: template<class U, class V>
pair(const pair<U, V> &p);
};
It turns out this is a very important (albeit simple) struct which is used quite a bit in the STL. All it really does it package together two objects, but it’s very useful, especially when you want to return two objects from a function (since a return statement only takes one object). There’s even a shorthand for creating a pair called make_pair( ), which is used in
AssociativeBasics.cpp.
So to retrace the steps, map::value_type is a pair of the key and the value of the map – actually, it’s a single entry for the map. But notice that pair packages its objects by value, which means that copy-constructions are necessary to get the objects into the pair. Thus, the
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creation of tmp in map::operator[ ] will involve at least a copy-constructor call and destructor call for each object in the pair. Here, we’re getting off easy because the key is an int. But if you want to really see what kind of activity can result from map::operator[ ], try running this:
//: C04:NoisyMap.cpp
// Mapping Noisy to Noisy #include "Noisy.h" #include <map>
using namespace std;
int main() {
map<Noisy, Noisy> mnn; Noisy n1, n2;
cout << "\n--------\n"; mnn[n1] = n2;
cout << "\n--------\n"; cout << mnn[n1] << endl; cout << "\n--------\n";
} ///:~
You’ll see that both the insertion and lookup generate a lot of extra objects, and that’s because of the creation of the tmp object. If you look back up at map::operator[ ] you’ll see that the second line calls insert( ) passing it tmp – that is, operator[ ] does an insertion every time. The return value of insert( ) is a different kind of pair, where first is an iterator pointing to the key-value pair that was just inserted, and second is a bool indicating whether the insertion took place. You can see that operator[ ] grabs first (the iterator), dereferences it to produce the pair, and then returns the second which is the value at that location.
So on the upside, map has this fancy “make a new entry if one isn’t there” behavior, but the downside is that you always get a lot of extra object creations and destructions when you use map::operator[ ]. Fortunately, AssociativeBasics.cpp also demonstrates how to reduce the overhead of insertions and deletions, by not using operator[ ] if you don’t have to. The insert( ) member function is slightly more efficient than operator[ ]. With a set you only hold one object, but with a map you hold key-value pairs, so insert( ) requires a pair as its argument. Here’s where make_pair( ) comes in handy, as you can see.
For looking objects up in a map, you can use count( ) to see whether a key is in the map, or you can use find( ) to produce an iterator pointing directly at the key-value pair. Again, since the map contains pairs that’s what the iterator produces when you dereference it, so you have to select first and second. When you run AssociativeBasics.cpp you’ll notice that the iterator approach involves no extra object creations or destructions at all. It’s not as easy to write or read, though.
If you use a map with large, complex objects and discover there’s too much overhead when doing lookups and insertions (don’t assume this from the beginning – take the easy approach
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