C++ Truths

Programs need data. That's a no brainer. Programs are only as good as the data you provide them. Based on what kind of data is consumed, programs can be divided into two broad categories: (1) those that operate on regular data (a file), and (2) those that operate on other programs. The first kind of programs are abundant. Your browser, for instance, is showing you this page--its data. The second kind of programs are more interesting and they are called meta-programs. Meta-programs need data too. As with the other programs, meta-programs are only as good as the data you provide them. So what do we feed them? ... Well, In C++, more important than 'what' is 'when'. (remember Morpheus?) A C++ program is just a sequence of bits the compiler is trying to understand. So, while the compiler is trying to make sense of your program, most of it gets translated (to assembly) but some of it gets executed. Quite intriguing! We're talking about compile-time meta-programming...

It's common knowledge that Functional Programming is spreading like a wildfire in mainstream languages. Latest promoted languages: Java 8 and C++, both of which now support lambdas. So, let the lambdas begin! and may the fun be ever on your side. The same text is available in slides form on Slideshare . This blog post and the talk/slides are inspired by JSON inventor  Douglas Crockford . Write an Identity function that takes an argument and returns the same argument . auto Identity = [](auto x) { return x; }; Identity(3); // 3 Write 3 functions add, sub, and mul that take 2 parameters each and return their sum, difference, and product respectively. auto add = [](auto x, auto y) { return x + y; }; auto sub = [](auto x, auto y) { return x - y; }; int mul (int x, int y) { return x * y; }; Write a function, identityf, that takes an argument and returns an inner class object that returns that argument . auto identityf = [](auto x) { class Inner { int x; publi...

I am presenting at the SF Bay Area Association of C/C++ Users (ACCU)  meetup  on Wed, Mar 12th. Topic: Fun with Lambdas: C++14 Style. Slides and the blog will be available here so stay tuned.

Ever since C++ adopted lambda expressions, many have stumbled upon the question whether they can be recursive. IMO, if an anonymous function needs to call itself why not create a named function/functor in the first place? But I'm not here today to argue whether it is a good or bad design. So here it is: the most common way to create a recursive lambda in C++11. void test() { std::function<int(int)> fib = [&fib](int n) { return (n <= 2)? 1 : fib(n-1) + fib(n-2); }; } The way it works is quite interesting. First, I created a std::function object, fib, and captured that in the lambda by reference. When the lambda captures fib, it is uninitialized because nothing has been assigned to it yet. The compiler knows the type of fib so it does not complain. It happily creates a closure with an uninitialized std::function. Right after that, it assigns the closure to the fib object so it gets initialized. Therefore, the reference inside lambda also works automatical...

Lot has been said about effectively using move-semantics, such as return-by-value and pass sink arguments by-value to constructors (and move later). Dust seems to be settling on those issues because I see some evidence building up to support that. Not much has been said (I think) about using move-semantics for a collection of objects, however. I mean moving objects from one type of STL container to another and also moving elements from std::initializer_list. Moving STL Containers of the same type This one is simple. STL containers provide the necessary move operations: move-constructor and move-assign operator. So moving an entire vector<T> to another is pretty straight forward. But that is only one of several ways to construct a vector<T>. How about move constructing a std::vector from a vector with custom allocators? Or for that matter, from a std::list or a std::set? Moving objects from one type of STL container to another The classic way of copying object...

Slides of my Silicon Valley Code Camp (2013) talk are now available . If you attended this session in person please evaluate it. I take feedback/comments seriously! Overloading in Overdrive: A Generic Data-Centric Messaging Library for DDS from Sumant Tambe Abstract: When it comes to sending data across a network, applications send either binary or self-describing data (XML). Both approaches have merits. Data Distribution Service (DDS) combines the best of both in what’s called “data-centric messaging”. DDS shares the type description once, upfront, and later on sends binary data that meets the type description. You typically use IDL or XSD to specify the types and run them through a code generator for type-safe wrapper APIs for your application in your programming language. Simple and fast! As it turns out, however, C++11 bends the rules once again. In this presentation you will learn about a template-based C++11 messaging library that gives the DDS code generator a run f...

You probably already know that there are 21 ways of passing parameters to a C++11 function! In case you lost the count somewhere, lets count one more time: 4 variations of pass-by pointer (i.e., const, volatile, const volatile, and none i.e., no cv-qualifiers), 4 variations of pass-by reference (ditto here), 4 variations of pass-by value (ditto here too), 4 ways of passing an argument as an rvalue reference (ditto here too! But seriously, you don't want to be around people who write cv-qualified pass-by rvalue reference arguments), std::initializer_list (ditto here too! and at this point it is ok to browse away from this page), and finally, pass-by universal reference (more formally, perfect forwarding ... T&& ... I think universal references deserve their own spot in this overcrowded VIP lounge because they are really special and they don't have 4 variations). So that makes it 21. So you are still with me, hmm... You seem to tolerate me. So I'm going to submit...

I'm not the only one who agrees that C++ is the awesomest language for network programming . Raw network programming, however, is very low-level and leads to many distractions that reduce productivity. Networking middlewares provide higher-level network programming models while taking care of many accidental complexities that would otherwise likely to plague your distributed system. One such standards-based networking middleware is Data Distribution Service (DDS) and now there is a modern C++ binding for programming high-performance distributed real-time systems using DDS. The API is now finalized by the Object Management Group (OMG) and is known as the DDS-PSM-Cxx standard. I have two upcoming talks on the DDS-PSM-Cxx. One is in the San Francisco Bay Area and another in Aspen (Yes, C++ Now'13!) . Find out what DDS-PSM-Cxx is about and what will be covered in the talks in this new blog post on  DDS Programming using Modern C++ .

Happy New Year!! Many projects use libraries developed by different teams, organizations, and open-source communities. It is not rare to see one project using dozens of external libraries where some libraries use return codes for reporting errors and others use exceptions.  When you find yourself in such a mix, what is the best way forward as far as error handling is concerned? Should you mix return codes and exceptions freely in your code? Should you choose one particular scheme over the other?  Issues like this are faced by the users of the RTI Connext Request/Reply API, which I helped create. Visit this new blog post on Mixing Return Codes and Exceptions in C++ for my 2 cents.

The slides for my C++11 Idioms talk @ 2012 Silicon Valley Code Camp are now available. If you attended the talk please evaluate  it. The slides for  many other talks in the C++/C++11 track are also available. C++11 Idioms @ Silicon Valley Code Camp 2012 from Sumant Tambe

For the first time in 7 years, 2012  Silicon Valley Code Camp will have a track dedicated to C++ and C++11 . Code Camp is a conference of developers, by developers, for developers. Attendance is free! This year, the number of attendees is expected to exceed 2200 to attend 223 sessions on a variety of topics related to software technology. Code Camp will be held @ Foothill College on Oct. 6th and 7th (weekend) in Silicon Valley. C++ is clearly one of the big things at Code Camp this year. The track has sessions on exception-safe coding, generic programming, logic programming, Windows 8 development, and the Clang compiler. There are sessions focused on C++11 too. Purely on the language side, two sessions on rvalue references, move semantics, perfect forwarding, and modern idioms of using them in your programs should whet the appetite of any C++11 programmer. On the standard library side, how about C++11 threading library! On Sunday, I'll present two sessions : "C++11 I...

C++11 offers a great new feature called Perfect Forwarding , which is enabled via the use of rvalue references. Perfect forwarding allows a function template to pass its arguments through to another function while retaining the original lvalue/rvalue nature of the function arguments. It avoids unnecessary copying and avoids the programmer having to write multiple overloads for different combinations of lvalue and rvalue references. A class can use perfect forwarding with variadic templates to "export" all possible constructors of a member object at the parent's level. class Blob { std::vector<std::string> _v; public: template<typename... Args> Blob(Args&&... args) : _v(std::forward<Args>(args)...) { } }; int main(void) { const char * shapes[3] = { "Circle", "Triangle", "Square" }; Blob b1(5, "C++ Truths"); Blob b2(shapes, shapes+3); } The Blob class above contains a std::vecto...

I've seen a recurring mistake made by well-versed C++03 programmers when they set out to use rvalue references for the first time. In fact, as it turns out, better you are at C++03, easier it is to fall in the trap of rvalue reference anti-pattern I'm gonna talk about. Consider the following C++03 class: class Book { public: Book(const std::string & title, const std::vector<std::string> & authors, const std::string & pub, size_t pub_day const std::string & pub_month, size_t pub_year) : _title(title), _authors(authors), _publisher(pub), _pub_day(pub_day), _pub_month(pub_month), _pub_year(pub_year) {} // .... // .... private: std::string _title; std::vector<std::string> _authors; std::string _publisher; size_t _pub_day; std::string _pub_month; size_t _pub_year; }; The Book class above is as dull as it can be. Now lets C++11'fy it!...

Question often comes up whether tuples can have traditional iterators? In general, the answer is: No! They cannot. That's because tuples typically contain different types and traditional iterators, which are modeled after pointers, can not dereference to objects of multiple types. However, homogeneous tuples can have iterators. So I thought it would be a fun exercise to write one. I wonder why one would use a homogeneous tuples instead of just plain arrays. But lets do it anyways because we can. Although this exercise sounds rather naive and unnecessary, I stumbled upon two very interesting topics along the way. A need for new iterator concepts to separate the notions of element access from iterator traversal. Yes! iterators for homogeneous tuples can't be modeled accurately using conventional iterator categories. Don't believe me? Please read on... How inherited constructors may be simulated on compilers that don't support them today. From this point onward a tuple i...

Memoization is a widely known optimization technique used primarily to speed up computer programs by having function calls avoid repeating the calculation of results for previously processed inputs. Repeated calculations are avoided by reusing previously computed results, which must be cached such that look-up is faster than recomputing. Consider a simple fibonacci program unsigned long fibonacci(unsigned n) { return (n < 2) ? n : fibonacci(n - 1) + fibonacci(n - 2); } This algorithm is a frustratingly slow way of computing the Nth fibonacci number (N starting at 0). It does a lot of redundant recomputations. But the beauty of this program is that it is really simple. To speed it up without changing its logic significantly, we could use memoization. Using some clever C++11 techniques, it is possible to memoize this function, which looks like below. unsigned long fibonacci(unsigned n) { return (n < 2) ? n : memoized_recursion(fibonacci)(n - 1) + memoized_recurs...