- •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
int main() { vector<Inventory> vi;
generate_n(back_inserter(vi), 15, InvenGen()); print(vi, "vi");
vector<float> disc; generate_n(back_inserter(disc), 15, DiscGen()); print(disc, "Discounts:");
vector<Inventory> discounted; transform(vi.begin(),vi.end(), disc.begin(),
back_inserter(discounted), Discounter()); print(discounted, "discounted");
} ///:~
Discounter is a function object that, given an Inventory object and a discount percentage, produces a new Inventory with the discounted price. DiscGen just generates random discount values between 1 and 10 percent to use for testing. In main( ), two vectors are created, one for Inventory and one for discounts. These are passed to transform( ) along with a
Discounter object, and transform( ) fills a new vector<Inventory> called discounted.
Numeric algorithms
These algorithms are all tucked into the header <numeric>, since they are primarily useful for performing numerical calculations.
<numeric>
T accumulate(InputIterator first, InputIterator last, T result); T accumulate(InputIterator first, InputIterator last, T result,
BinaryFunction f);
The first form is a generalized summation; for each element pointed to by an iterator i in [first, last), it performs the operation result = result + *i, where result is of type T. However, the second form is more general; it applies the function f(result, *i) on each element *i in the range from beginning to end. The value result is initialized in both cases by resultI, and if the range is empty then resultI is returned.
Note the similarity between the second form of transform( ) and the second form of accumulate( ).
<numeric>
T inner_product(InputIterator1 first1, InputIterator1 last1, InputIterator2 first2, T init);
Tinner_product(InputIterator1 first1, InputIterator1 last1, InputIterator2 first2, T init
BinaryFunction1 op1, BinaryFunction2 op2);
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Calculates a generalized inner product of the two ranges [first1, last1) and [first2, first2 + (last1 - first1)). The return value is produced by multiplying the element from the first sequence by the “parallel” element in the second sequence, and then adding it to the sum. So if you have two sequences {1, 1, 2, 2} and {1, 2, 3, 4} the inner product becomes:
(1*1) + (1*2) + (2*3) + (2*4)
Which is 17. The init argument is the initial value for the inner product; this is probably zero but may be anything and is especially important for an empty first sequence, because then it becomes the default return value. The second sequence must have at least as many elements as the first.
While the first form is very specifically mathematical, the second form is simply a multiple application of functions and could conceivably be used in many other situations. The op1 function is used in place of addition, and op2 is used instead of multiplication. Thus, if you applied the second version of inner_product( ) to the above sequence, the result would be the following operations:
init = op1(init, op2(1,1)); init = op1(init, op2(1,2)); init = op1(init, op2(2,3)); init = op1(init, op2(2,4));
Thus it’s similar to transform( ) but two operations are performed instead of one.
<numeric>
OutputIterator partial_sum(InputIterator first, InputIterator last, OutputIterator result);
OutputIterator partial_sum(InputIterator first, InputIterator last, OutputIterator result, BinaryFunction op);
Calculates a generalized partial sum. This means that a new sequence is created, beginning at result, where each element is the sum of all the elements up to the currently selected element in [first, last). For example, if the original sequence is {1, 1, 2, 2, 3} then the generated sequence is {1, 1 + 1, 1 + 1 + 2, 1 + 1 + 1 + 2 + 2, 1 + 1 + 1 + 2 + 2 + 3}, that is, {1, 2, 4, 6, 9}.
In the second version, the binary function op is used instead of the + operator to take all the “summation” up to that point and combine it with the new value. For example, if you use multiplies<int>( ) as the object for the above sequence, the output is {1, 1, 2, 4, 12}. Note that the first output value is always the same as the first input value.
The return value is the end of the output range [result, result + (last - first) ).
<numeric>
OutputIterator adjacent_difference(InputIterator first, InputIterator last, OutputIterator result);
OutputIterator adjacent_difference(InputIterator first, InputIterator last, OutputIterator result, BinaryFunction op);
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Calculates the differences of adjacent elements throughout the range [first, last). This means that in the new sequence, the value is the value of the difference of the current element and the previous element in the original sequence (the first value is the same). For example, if the original sequence is {1, 1, 2, 2, 3}, the resulting sequence is {1, 1 – 1, 2 – 1, 2 – 2, 3 – 2}, that is: {1, 0, 1, 0, 1}.
The second form uses the binary function op instead of the – operator to perform the “differencing.” For example, if you use multiplies<int>( ) as the function object for the above sequence, the output is {1, 1, 2, 4, 6}.
The return value is the end of the output range [result, result + (last - first) ).
Example
This program tests all the algorithms in <numeric> in both forms, on integer arrays. You’ll notice that in the test of the form where you supply the function or functions, the function objects used are the ones that produce the same result as form one so the results produced will be exactly the same. This should also demonstrate a bit more clearly the operations that are going on, and how to substitute your own operations.
//: C05:NumericTest.cpp #include "PrintSequence.h" #include <numeric> #include <algorithm> #include <iostream> #include <iterator> #include <functional> using namespace std;
int main() {
int a[] = { 1, 1, 2, 2, 3, 5, 7, 9, 11, 13 }; const int asz = sizeof a / sizeof a[0]; print(a, a + asz, "a", " ");
int r = accumulate(a, a + asz, 0); cout << "accumulate 1: " << r << endl; // Should produce the same result:
r = accumulate(a, a + asz, 0, plus<int>()); cout << "accumulate 2: " << r << endl;
int b[] = { 1, 2, 3, 4, 1, 2, 3, 4, 1, 2 }; print(b, b + sizeof b / sizeof b[0], "b", " "); r = inner_product(a, a + asz, b, 0);
cout << "inner_product 1: " << r << endl; // Should produce the same result:
r= inner_product(a, a + asz, b, 0, plus<int>(), multiplies<int>());
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