As has been reported in a few places, Boost is transitioning from Subversion to Git. The Boost Steering Committee has voted to “push the button” which amounts to shutting down the SVN repository and making a final run of the conversion script. There are a lot of details available on the Boost wiki.
The motivating issue for this transition is not just to see Boost move to a repository system that has become the de facto standard for open source projects, but to support better modularity for the Boost Libraries. Boost policy has been to encourage developers to depend on existing Boost libraries rather than to “re-invent the wheel.” But this leads to a lot of intra-library dependencies that discourage users that may be interested in only a small number of libraries.
Moving to Git doesn’t solve this problem, but it does move in the direction of modularity which is more and more important as the number of Boost libraries grows. (When I first visited boost.org, there were four libraries. Now I count one hundred twenty-six libraries.)
I want to make a big shout out to everyone that has worked to make this transition possible. I wish I new all the names, but some of the ones that I do know are: Dave Abrahams, Daniel Pfeifer, John Wiegley, and Beman Dawes. If you know someone who helped with this transition, please add a comment.
My goal is to update this blog every Tuesday, but next Tuesday I’ll be having major surgery so it is unlikely that I’ll online for awhile. If I don’t have something up by Monday night, it will likely be a while.
C++11 introduced a new member function called shrink_to_fit() for the three sequence containers vector, deque, and string. Before shrink_to_fit() there was no member to reduce capacity on these containers, not even erase(). In fact, the standard made it very unlikely that any implementation would reduce capacity with any call. The standard provides the guarantee that if reserve() is called, then any subsequence addition to the container will not invalidate iterators (until an addition increases the size of the container above the reserve() point.
Since this guarantee is not relaxed even if the user calls erase(), a implementation that chose to reduce capacity would be required to track whether or not reserve had previously been called. It would be theoretically possible for an implementation to add this extra state to the container implementation, but in practice no implementation is going to do that.
Perhaps this lack of attention to minimizing capacity isn’t surprising. In most modern code, our concern is usually time performance rather than space requirements. But C++ is the language of choice for demanding situations and sometimes this means minimizing space requirements.
Scott Meyers
So what can users do if they want to reduce the capacity of a container? Is this not possible? It turns out that it is possible. In Item 17 of Scott Meyer’s Effective STL, Scott explains that there is a “Swap Trick” that we can use to reduce capacity.
Here is the quick synopsis of the Swap trick:
Container(begin(c), end(c)).swap(c);
where “c” is a container whose capacity we want to reduce and Container is it’s type.
What is happening is that we are creating a temporary container as a copy of our original container using the iterator range constructor and then swapping the contents of the our temporary container with our original container. This works because most implementations will implement the iterator range constructor to not make the capacity any larger than necessary. The reserve() guarantee is swapped to the other container with the call to swap().
In practice we’d almost certainly want to write this something like this:
if (c.capacity() > c.size())
{
Container(begin(c), end(c)).swap(c);
}
or:
if (c.capacity() > (c.size() + some_value))
{
Container(begin(c), end(c)).swap(c);
}
Because this trick involves copying all the items in the container, we don’t want to do it unless it saves enough space to be worthwhile. (In C++11 we could use moves instead of copies. This would make the technique less expensive, but we really only want to do this if the moves are no_except. This is a beyond the scope of what I want to discuss in this post.)
Meyers’ Swap Trick was state of the art, at least until C++11 where we can now do this:
if (c.capacity() > c.size())
{
c.shrink_to_fit);
}
assuming type of c is vector, deque, or string. For vector and string the standard says “… request to reduce capacity() to size().” (We’ll consider the ellipse shortly.) For deque the standard says “… request to reduce memory use.”
Why is deque’s description different than vector and string? Because deque doesn’t have a capacity() member function. The point of the capacity member function is tell us how much we can grow the number of items in the container before an addition would invalidate iterators. This concept doesn’t make much sense for deque, so there is no such call as deque::capacity().
So let’s look at what I left out just now when I quoted the standard. What it really says for vector and string is “shrink_to_fit is a non-binding request to reduce capacity() to size().” The emphasis is mine. The standard has made shrink_to_fit() non-binding. (Also true for deque.) It can be implemented as a no-op!
Why would the committee do such a thing? The standard gives an answer: “[Note: The request is non-binding to allow latitude for implementation-specific optimizations. — end note ]” What this means is that the committee knows that there are implementations where doing the right thing might not result in size() == capacity().
Consider the “short string” optimization. A string is an allocated array and a straight-forward implementation would allocation an array even for a string that was only one character long. One character long strings are not particularly common, but short strings are. So an library might choose to implement the string class so that the class itself has (data member) space for “short” strings so that no allocation is necessary until the size of the string is no longer “short” for some value of “short.” Given this implementation how would capacity() be implemented? In particular would capacity() ever return a value less than the “short” string limit? No because we can always expand the string to the “short” string limit without invalidating iterators (assuming the current size() is less than this limit).
This means that if we currently have a string whose size() is less than the “short” string limit, a “request to reduce capacity() to size()” is going to fail. So the standard doesn’t want to say that the implementation must reduce capacity() to size().
But in my opinion the committee has let us down. While I’m all for giving implementers latitude for their implementations, I think the committee has underspecified this call. It is acceptable to say that the implementation need not reduce capacity() all the way to size(), but it should say that it will reduce capacity at least as far as the Swap Trick would have.
Since the Swap Trick is potentially expensive in time, it is likely only used in situations where users are very serious about reducing excess capacity. Given this, and faced with the fact that shrink_to_fit() may be a no-op, I think conscientious coders will choose to skip the new shrink_to_fit() and continue to use the Swap Trick.
And that is a shame. With shrink_to_fit() the user is very explicitly stating the desired outcome, so this has the potential to allow implementers to exploit interesting optimizations. This should be better than the somewhat obscure looking Swap Trick. But clarity and interesting optimizations aren’t of much use if users don’t use the new call. And they may avoid it because the old way gives them guarantees that the committee didn’t see fit to apply to the new call.
I want to talk about a couple of the lesser known member functions of the best known STL container: reserve() and shrink_to_fit(). These members manipulate the vector’s capacity. The reserve() member is original and I discuss it in this post. New with C++11 is shrink_to_fit(). I’ll talk about it in a future post.
Note: The use of kittens in explaining C++ is patented by STL. This image used without permission.The vector class stores data in an allocated array whose allocation the class handles for us. Each call to push_back() does a check to see if the array has space for the new item. If not, the class must perform a reallocation. This involves allocating a larger array and copying all existing items into the new array before destroying the originals in the old array and releasing the old array. This is expensive, but the cost is amortized so that order of push_back() is amortized constant time.
How can it be constant time when copying all existing items will take time proportional to the number of existing items? The trick is that when push_back() triggers a reallocation, the new array is not a constant size increase of the existing array, but is proportional to the existing array (e.g. doubling in size). This approach means that although each reallocation is more expensive (due the increased number of exiting items), the allocations end up being required exponentially less often. The result works out to average (or amortized) constant time.
This is a great way to deal with allocations when we don’t know how many items we will need the vector to hold. But what if we do know how many items will be required? Suppose we know in advance that our vector will need to hold a thousand items. If vector initially allocates enough space for eight items and allocates an array twice as large as the existing one with each reallocation, we’ll need seven reallocations (and copies of all existing items) before we are finished adding our thousand items. This may be optimal if we have no idea how many items we’ll need to handle, but it is wasteful if we know in advance that we will need to hold a thousand items. We’d like a way to tell vector upfront that we need to hold a thousand items so it can create this space with one allocation and avoid needlessly copying items.
One way to do this to pre-fill our vector. If we are working with a vector of ints we can do something like this:
#include <iostream>
#include <vector>
using Ints = std::vector<int>;
// some how we know the upper bound of our storage requirement
const int vector_limit(1000);
int main()
{
Ints v(vector_limit); // pre-fill a thousand ints
std::cout << v.size() << std::endl;
std::cout << v.capacity() << std::endl;
}
1000some value >= 1000, likely 1000
The drawback to this approach is that we’ve not just changed the vector’s capacity, but its content as well. If we know we need to store a thousand ints, pre-filling the vector may not be a problem, but consider some other cases. Suppose we know only the upper bound of the number of items, but not the exact number and the item type has an expensive constructor. Or no default constructor. In these cases, pre-filling the vector is problematic.
What we need is a way to increase a vector’s capacity without changing it’s size.
Enter reserve(). reserve() takes a parameter that tells the vector class how many items we expect to hold. In our example we can call reserve() with the value one thousand before pushing back any items. This would trigger a single allocation and since we haven’t added any items to the vector, there are no existing items that need to be copied. Big win.
#include <iostream>
#include <vector>
using Ints = std::vector<int>;
// some how we know the upper bound of our storage requirement
const int vector_limit(1000);
int main()
{
Ints v; // creates an empty vector
v.reserve(vector_limit); // increase capacity only
std::cout << v.size() << std::endl;
std::cout << v.capacity() << std::endl;
}
0some value >= 1000, likely 1000
One of the reasons that I wanted to discuss reserve() is because of a discussion I had with some very experienced and knowledgable C++ programmers. I was surprised to learn that they believed that reserve() is only an optimization-enabling hint to the library and that the library has the option of implementing it as a no-op. This is wrong on two counts. The standard does not allow reserve() to be a no-op (unless the passed values is already less than or equal to the vector’s current capacity).
Further, the standard guarantees that adding items to the vector up to the reserve() limit, will not only not cause a reallocation, but that iterators will not be invalidated. This is not just an optimization, but is an important guarantee because in general, we always assume that push_back() and insert() will invalidate iterators. (You can verify that these calls will not invalidate iterators for a specific call by checking the current capacity before the call.)
Because of this guarantee we can be confident that iterators (and references and pointers) are not invalidated as long as don’t increase the size of our vector beyond our reserve.
#include <cassert>
#include <iostream>
#include <vector>
using Ints = std::vector<int>;
// some how we know the upper bound of our storage requirement
const int vector_limit(1000);
int main()
{
Ints v; // creates an empty vector
v.reserve(vector_limit); // increase capacity only
// add a single element and remember its address
v.push_back(0);
const int* start_of_allocated_array(&v[0]);
// fill the vector to our limit
for (int i(1); i < vector_limit; ++i) v.push_back(i);
// verify no invalidation of iterators, pointers, or references
assert(start_of_allocated_array == &v[0]);
}
What if we want to maintain stable access to items in the face of iterator invalidation (where we are adding items beyond the vector's capacity)? The trick is to use index values instead of iterators, pointers, or references. The Nth item in the vector will still be the Nth items after a reallocation.
The other reason I wanted to discuss reserve() is because of a nasty performance bug that some of my co-workers found within the last few days. Proper use of reserve() can be a nice performance win, but there is a gotcha scenario. In the bug, the code was calculating how many items needed to be added to the vector and then calling reserve() before adding them. This seems like a good use, until you realize that this code is being called in a loop. So what is happening is, each time through the loop we find that we need to add a few more items so we call reserve() which has the result of copying all existing items. What leads to this result is one of the characteristic of reserve() that isn't mandated by the standard, but it is usually the way that it is implemented. Let me explain.
As I said before, when a reallocation happens, the new size of the array is some proportion, usually double, of the old size of the array. The standard doesn't mandate any particular ratio. It also doesn't provide an upper limit on the capacity after a call to reserve(). An implementation is free to allocate an array double the value of the reserve() parameter. But that isn't what users would usually want or what most implementations provide. Usually reserve() will create a capacity exactly equal to the value passed. The passed value is a very good hint about the upper bound of the vector's size, and implementations take advantage of this hint.
Consider the implication of this on our performance bug. Without the call to reserve(), the push_back() in the loop would have added items with amortized constant time. But by calling reserve() in the loop, each reserve() resulted in copying every item in the vector every time through the loop and also pinning the capacity to exactly the reserve() value rather than a proportionally larger value, with disastrous performance consequences.
reserve() is a great tool for optimizing vector performance, but keep in mind the optimal use case for it. We want to call reserve() once when we can determine the upper bound on the vector's size requirement before we have added any values to the vector. There are many cases were we can't predict the size requirement upper bound, so we can't implement this optimal strategy and we may have to modify it. But calling reserve() several times with increasing estimates of the required capacity is not a strategy likely to yield success.
The C++Now Call for Submissions for 2014 is out. You might think that after releasing it, we just sit back and wait for all the great submissions to come rolling it. I hope it looks that easy to the outside world, but truth is that encouraging potential speakers to submit sessions is a year-round job that just gets more intense after the Call the Submissions. We are constantly looking for people with interesting things to say about C++ and asking them if they’d like to share at C++Now.
In 2012, when we changed the conference name from BoostCon to C++Now, we also added a third track of presentations. We wanted to create space for tutorials, specifically tutorials on the new language and library features. For this track, we are not just looking for good speakers, we also are looking for coverage of specific topics.
This year Scott Schurr is leading the effort to make certain that we are presenting an excellent tutorial track. I’ve his permission to share some of the ideas that we are pursuing.
Scott Schurr
Although some of the talks have been proposed with specific presenters in mind, most of these talks are “unclaimed” by any particular presenter. Why am I sharing them? Boost is an open-source library and I thought we could experiment with adding some transparency to our conference planning.
I’m also hoping that this list might be inspirational. Perhaps it will inspire you to claim one of these topics for yourself and make a submission of it or a completely different topic (the deadline is December 8th). If you have any ideas or questions about making a submission, you can contact the program committee. If you’d just like to comment on the list, you can do that at google plus or redit.
“How and Why to Implement Value Semantics in C++”.” This talk might start out with an introduction to the ideas behind value semantics. A talk that discusses moving, deleting, defaulting, explicit conversion functions and delegating construction would be very valuable.
“The Libraries That You Should Know About.” Consider the “optional” library (no longer in C++14), “flat_set”, and reference wrappers. Consider about 5 minutes each on twelve small libraries. This could include standardized but under-appreciated libraries as well as Boost and Adobe Source Libraries.
“Unicode Support in Standard C++.” A lot of work has gone on here. What can you do with Unicode and just standard C++ in real-life situations?
“Intro to Functional Programming in C++.” What’s the point of functional programming. Don’t I have to do that in Haskell? Is functional programming an all-or-nothing thing? Can I benefit from making my C++ “more functional”? If so, how would I do that?
“Intro to Concurrency.” Obviously this could span two or three sessions and would make a terrific workshop.
“A Survey of Algorithms.” If you haven’t seen Sean Parent’s talks at Going Native, stop reading this and go watch them. (http://channel9.msdn.com/Events/GoingNative/2013/Cpp-Seasoning and http://channel9.msdn.com/Events/GoingNative/2013/Inheritance-Is-The-Base-Class-of-Evil) One reaction to these talks is that “we” don’t really know what algorithms are available to us. Another point is that even if we know the available algorithms we don’t necessarily recognize them in the wild. Sean recognized a particular operation as a kind of rotate. Insights into how to recognize algorithms would be invaluable. If this topic were restricted to std, then it might be a short talk, but if we include Boost and the Adobe Source Library there could be real gems.
“How To Do Random Numbers Right (and How Not To Do Them).” We should ask STL to do his talk from Going Native as a tutorial.
“RegEx in C++.” STL did a great tutorial on this at Going Native. We could ask STL for a repeat, or we could ask someone else to give their take on it.
“Building Great Hashing Functions.” Perhaps this could be combined with bucket size/rehashing strategies for unordered containers.
“Fixed Size Arrays.”
“Alignment Control in C++11.” Most programmers don’t think about alignment. This talk could start with an introduction to alignment including where the requirement comes from. From there the talk could go into aligneof, alignas, aligned_storage. It could finish up with a discussion of over aligned data types (see N3396) and how to manage them.
“How To Build a Perfect Function Wrapper.” Suppose I want to do “something.” (I always use the example of timing how long we spend inside an API. This is conceptually very simple. You just start timing when you are about to make an API call and stop when you finish.) But you want to be able to wrap arbitrary calls. So you need to use variadic template parameters and perfect forwarding. This may be too simple to justify a complete session. Maybe it could be combined with a tutorial on bind, function, and lambda. (Or a tutorial on the time library.)
“Managing Object Lifetimes.” Start with RAII, move on to smart pointers, then show how the combination gives you 90% of the exception-safety that you want. Finish up with a discussion on passing parameters – how to make your APIs be more explicit about ownership and lifetimes.
“Compilation Errors: The Best Kind of Errors.” When I’ve tried talking to typical programmers about compile-time error checking they lift their noses and suggest that it couldn’t be useful. But with careful design many kinds of errors (admittedly not all) can be hoisted to compile-or link-time. We need to promote finding programming errors early.
“SFINAE Boot Camp.” This is a really important technique that is more of a black art than a science. If someone can present rhyme and reason for how to use SFINAE in a variety of circumstances I think a lot of people would benefit from that.
“Understanding &&.” You’ve no doubt noticed that && in a signature does not act like & or * in a signature. A session that helps folks develop an intuition for && and its effects would be great. All the experts already have this nailed, but this could be a valuable topic for mid-level programmers. Perhaps this topic could incorporate the first topic, “Moving Well.”
“New Features in C++14.” Surely we ought to cover this topic.
“C++11/14 Glossary.” C++11 extends rvalues and lvalues to include a total of five different values categories. PODs used to be important, but now aggregates, trivial classes, and standard-layout classes carry more of the semantic load. The volatile keyword has a new meaning in C++11 that it didn’t have in C++98. A deep dive into some of these vocabulary changes (and others) could be useful for many mid-level programmers.
“What’s My Value?” To mix it up a bit, we could do C++ related questions in some sort of game show format. Imagine 45 minutes of glossary followed by a 45 minute game show format presentation with questions about the preceding material. This could also be applied to a talk about the memory model followed by game show style questions.
“Building a Boost Reference Application.” Boost could have a reference application (or maybe several) which uses many Boost libraries to do something useful. The reference application would be an example of how to use Boost libraries in the real world.
Clean C++ – throw down the gauntlet against software entropy!
Generic Programming for the rest of us
Efficient Team Development for C++ Projects
Presentations on tools C++ developers typically use or might want to
“Presentations on tools C++ developers typically use or might want to use: Git, CMake, Quickbook (and how to use the tool chain to generate documentation) etc.
Workshop to organize “review teams” (probably easier than finding individuals who have to do all the work 🙂 which start working their way through the libraries in the review queue (“Review manager in a week” instead of “Library in a week”? 😉
“Google Summer of Code.” This is a successful program. Can we leverage it into a useful tutorial topic?
“C++11/14 Overview: Core Language Features”
C++ Timeline
Goals for C++11
The Simpler Core Language Features
auto, decltype, trailing return types
nullptr
Range for
>> in template specializations
static_assert
noexcept
extern template
constexpr
“C++11/14 Overview: Features Specific to Class Design”
