Tag Archives: c++

On the novelty factor of compile-time duck typing

Or structural type systems for the pendantic, but I think most people know what I mean when I say “compile-time duck typing”.

For one reason or another I’ve read quite a few blog posts about how great the Go programming language is recently. A common refrain is that Go’s interfaces are amazing because you don’t have to declare that a type has to satisfy an interface; it just does if its structure matches (hence structural typing). I’m not sold on how great this actually is – more on that later.

What I don’t understand is how this is presented as novel and never done before. I present to you a language from 1990:

template <typename T>
void fun(const T& animal) {
    cout << "It says: " << animal.say() << endl;

struct Dog {
    std::string say() const { return "woof"; }

struct Cat {
    std::string say() const { return "meow"; }

int main() {

Most people would recognise that as being C++. If you didn’t, well… it’s C++. I stayed away from post-C++11 on purpose (i.e. Dog{} instead of Dog()). Look ma, compile-time duck typing in the 1990s! Who’d’ve thunk it?

Is it nicer in Go? In my opinion, yes. Defining an interface and saying a function only takes objects that conform to that interface is a good thing, and a lot better than the situation in C++ (even with std::enable_if and std::void_t). But it’s easy enough to do that in D (template contraints), Haskell (typeclasses), and Rust (traits), to name the languages that do something similar that I’m more familiar with.

But in D and C++, there’s currently no way to state that your type satisfies what you need it to due to an algorithm function requiring it (such as having a member function called “say” in the silly example above) and get compiler errors telling you why it didn’t satisfy it (such as  mispelling “say” as “sey”). C++, at some point in the future, will get concepts exactly to alleviate this. In D, I wrote a library to do it. Traits and typeclasses are definitely better, but in my point of view it’s good to be able to state that a type does indeed “look like” what it needs to do to be used by certain functions. At least in D you can say static assert(isAnimal!MyType); – you just don’t know why that assertion fails when it does. I guess in C++17 one could do something similar using std::void_t. Is there an equivalent for Go? I hope a gopher enlightens me.

All in all I don’t get why this gets touted as something only Go has. It’s a similar story to “you can link statically”. I can do that in other languages as well. Even ones from the 90s.

Tagged , , ,

The main function should be shunned

The main function (in languages that have it) is…. special. It’s the entry point of the program by convention, there can only be one of them in all the object files being linked, and you can’t run a program without it. And it’s inflexible.

Its presence means that the final output has to be an executable. It’s likely however, that the executable in question might have code that others might rather reuse than rewrite, but they won’t be able to use it in their own executables. There’s already a main function in there. Before clang nobody seemed to stumble on the idea that a compiler as a library would be a great idea. And yet…

This is why I’m now advocating for always putting the main function of an executable in its own file, all by itself. And also that it do the least amount of work possible for maximum flexibility. This way, any executable project is one excluded file away in the build system from being used as a library. This is how I’d start a, say, C++ executable project from scratch today:

#include "runtime.hpp"
#include <iostream>
#include <stdexcept>

int main(int argc, const char* argv[]) {
    try {
        run(argc, argv); // "real" main
        return 0;
    } catch(const std::exception& ex) {
        std::cout << "Oops: " << ex.what() << std::endl;
        return 1;

In fact, I think I’ll go write an Emacs snippet for that right now.

Tagged ,

C is not magically fast, part 2

I wrote a blog post before about how C is not magically fast, but the sentiment that C has properties lacking in other languages that make it so is still widespread. It was with no surprise at all then that a colleague mentioned something resembling that recently at lunch break, and I attempted to tell him why it wasn’t (at least always) true.

He asked for an example where C++ would be faster, and I resorted to the old sort classic: C++ sort is faster than C’s qsort because of templates and inlining. He then asked me if I’d ever measured it myself, and since I hadn’t, I did just that after lunch. I included D as well because, well, it’s my favourite language. Taking the minimum time after ten runs each to sort a random array of 10M simple structs on my laptop yielded the results below:

  • D: 1.147s
  • C++: 1.723s
  • C: 1.789s

I expected  C++ to be faster than C, I didn’t expect the difference to be so small. I expected D to be the same speed as C++, but for some reason it’s faster. I haven’t investigated the reason why for lack of interest, but maybe because of how strings are handled?

I used the same compiler backend for all 3 so that wouldn’t be an influence: LLVM. I also seeded all of them with the same number and used the same random number generator: the awful srand from C’s standard library. It’s terrible, but it’s the only easy way to do it in standard C and the same function is available from the other two languages. I also only timed the sort, not counting init code.

The code for all 3 implementations:

// sort.c
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <sys/time.h>
#include <sys/resource.h>

typedef struct {
    int i;
    char* s;
} Foo;

double get_time() {
    struct timeval t;
    struct timezone tzp;
    gettimeofday(&t, &tzp);
    return t.tv_sec + t.tv_usec*1e-6;

int comp(const void* lhs_, const void* rhs_) {
    const Foo *lhs = (const Foo*)lhs_;
    const Foo *rhs = (const Foo*)rhs_;
    if(lhs->i < rhs->i) return -1;
    if(lhs->i > rhs->i) return 1;
    return strcmp(lhs->s, rhs->s);

int main(int argc, char* argv[]) {
    if(argc < 2) {
        fprintf(stderr, "Must pass in number of elements\n");
        return 1;

    const int size = atoi(argv[1]);
    Foo* foos = malloc(size * sizeof(Foo));
    for(int i = 0; i < size; ++i) {
        foos[i].i = rand() % size;
        foos[i].s = malloc(100);
        sprintf(foos[i].s, "foo%dfoo", foos[i].i);

    const double start = get_time();
    qsort(foos, size, sizeof(Foo), comp);
    const double end = get_time();
    printf("Sort time: %lf\n", end - start);

    return 0;

// sort.cpp
#include <iostream>
#include <algorithm>
#include <string>
#include <vector>
#include <chrono>
#include <cstring>

using namespace std;
using namespace chrono;

struct Foo {
    int i;
    string s;

    bool operator<(const Foo& other) const noexcept {
        if(i < other.i) return true;
        if(i > other.i) return false;
        return s < other.s;


template<typename CLOCK, typename START>
static double getElapsedSeconds(CLOCK clock, const START start) {
    //cast to ms first to get fractional amount of seconds
    return duration_cast<milliseconds>(clock.now() - start).count() / 1000.0;

#include <type_traits>
int main(int argc, char* argv[]) {
    if(argc < 2) {
        cerr << "Must pass in number of elements" << endl;
        return 1;

    const int size = stoi(argv[1]);
    vector<Foo> foos(size);
    for(auto& foo: foos) {
        foo.i = rand() % size;
        foo.s = "foo"s + to_string(foo.i) + "foo"s;

    high_resolution_clock clock;
    const auto start = clock.now();
    sort(foos.begin(), foos.end());
    cout << "Sort time: " << getElapsedSeconds(clock, start) << endl;

// sort.d
import std.stdio;
import std.exception;
import std.datetime;
import std.algorithm;
import std.conv;
import core.stdc.stdlib;

struct Foo {
    int i;
    string s;

    int opCmp(ref Foo other) const @safe pure nothrow {
        if(i < other.i) return -1;
        if(i > other.i) return 1;
        return s < other.s
            ? -1
            : (s > other.s ? 1 : 0);

void main(string[] args) {
    enforce(args.length > 1, "Must pass in number of elements");
    immutable size = args[1].to!int;
    auto foos = new Foo[size];
    foreach(ref foo; foos) {
        foo.i = rand % size;
        foo.s = "foo" ~ foo.i.to!string ~ "foo";

    auto sw = StopWatch();
    writeln("Elapsed: ", cast(Duration)sw.peek);

Tagged , ,

The C++ GSL in Practice

At CppCon 2015, we heard about the CppCoreGuildelines and a supporting library for it, the GSL. There were several talks devoted to this, including two of the keynotes, and we were promised a future of zero cost abstractions that were also safe. What’s not to like?

Me being me, I had to try this out for myself. And what better way than when rewriting my C++ implementation of an MQTT broker from scratch. Why from scratch? The version I had didn’t perform well, required extensive refactoring to do so and I’m not crazy enough to post results from C++ that lose by a factor of 3 to any other language.

It was a good fit as well: the equivalent D and Rust code was using slices, so this seemed like the perfect change to try out gsl::span (née gsl::array_view).

I think I liked it. I say I think because the benefits it provided (slices in C++!) are something I’m used to now by programming in D, and of course there were a few things that didn’t work out so well, namely:


First of all, there was this bug I filed. This is a new one to shoot oneself in one’s foot and we were not amused. Had I just declared a function taking const std::string& as usual, I wouldn’t have hit the bug. The price of early adoption, I guess. The worst part is that it failed silently and was hard to detect: the strings printed out the same, but one had a silent terminating null char. I ended up having to declare an overload that took const char* and did the conversion appropriately.

Also, although I know why, it’s still incredibly annoying to have to use empty angle brackets for the default case.

Rvalues need not apply

Without using the GSL, I can do this:

void func(const std::vector<unsigned char>&);
func({2, 3, 4}); //rvalues are nice

With the GSL, it has to be this:

void func(gsl::span<const unsigned char>&);
const std::vector<unsigned char> bytes{2, 3, 4};

It’s cumbersome and I can’t see how it’s protecting me from anything.


I had to refer to the unit tests (fortunately included) and Neil MacIntosh’s presentation at CppCon 2015 multiple times to figure out how to use it. It wasn’t always obvious.


I still think this is a good thing for C++, but the value of something like gsl::not_null is… null without the static analysis tool they mentioned. It could be easier to use as well. My other concern is how and if gsl::span will work with the ranges proposal / library.


Tagged , ,

Rust impressions from a C++/D programmer, part 1

Discussion on programming reddit

Discussion on Rust reddit

C++ and D aren’t the only languages I know, I labeled myself that way in the title because as far as learning Rust is concerned, I figured they would be the most relevant in terms of the audience knowing where I’m coming from.

Since two years ago, my go-to task for learning a new programming language is to implement an MQTT broker in it. It was actually my 3rd project in D, but my first in Haskell and now that I have some time on my hands, it’s what I’m using to learn Rust. I started last week and have worked on it for about 3 days. As expected, writing an MQTT broker is a great source of insight into how a language really is. You know, the post-lovey-dovey phase. It’s like moving in together straight away instead of the first-date-like “here’s how you write a Scheme interpreter”.

I haven’t finished the project yet, I’m probably somewhere around the 75% mark, which isn’t too shabby for 3 days of work. Here are my impressions so far:

The good

The borrow checker. Not surprising since this is basically the whole point of the language. It’s interesting how much insight it gave me in how broken the code I’m writing elsewhere might be.  This will be something I can use when I write in other systems languages, like how learning Haskell makes you wary of doing IO.

Cargo. Setting up, getting started, using someone’s code and unit testing what you write as you go along is painless and just works. Tests in parallel by default? Yes, please. I wonder where I’ve seen that before…

Traits. Is there another language other than D and Rust that make it this easy to use compile-time polymorphism? If there is, please let me know which one. Rust has an advantage here: as in Dylan (or so I read), the same trait can be used for runtime polymorphism.

Warnings. On by default, and I only had to install flycheck-rust in Emacs for syntax highlighting to just work. Good stuff.

Productivity. This was surprising, given the borrow checker’s infamy. It _does_ take a while to get my code to compile, but overall I’ve been able to get a good amound done with not that much time, given these are the first lines of Rust I’ve ever written.

Algebraic types and pattern matching. Even though I didn’t use the former.

Slices. Non-allocating views into data? Yes, please. Made the D programmer in me feel right at home.

Immutable by default. Need I say more?

Debugging. rust-gdb makes printing out values easy. I couldn’t figure out how to break on certain functions though, so I had to use the source file and line number instead.

No need to close a socket due to RAII. This was nice and even caught a bug for me. The reason being that I expected my socket to close because it was dropped, but my test failed. When I looked into it, the reference count was larger than 1 because I’d forgotten to remove the client’s subscriptions. The ref count was 0, the socket was dropped and closed, and the test passed. Nice.

No parens for match, if, for, …

The bad

The syntax. How many times can one write an ampersand in one’s source code? You’ll break new records. Speaking of which…

Explicit borrows. I really dislike the fact that I have to tell the compiler that I’m the function I’m calling is borrowing a parameter when the function signature itself only takes borrows. It won’t compile otherwise (which is good), but… since I can’t get it wrong what’s the point of having to express intent? In C++:

void fun(Widget& w);
auto w = Widget();
fun(w); //NOT fun(&w) as in Rust

In Rust:

fn fun(w: &mut Widget);
let w = Widget::new();
fun(&mut w); //fun(w) doesn't compile but I still need to spell out &mut. Sigh.

Display vs Debug. Printing out integers and strings with {} is fine, but try and do that with a Vec or HashMap and you have to use the weird {:?}. I kept getting the order of the two symbols wrong as well. It’s silly. Even the documentation for HashMap loops over each entry and prints them out individually. Ugh.

Having to rethink my code. More than once I had to find a different way to do the thing I wanted to do. 100% of the time it was because of the borrow checker. Maybe I couldn’t figure out the magical incantation that would get my code to compile, but in one case I went from “return a reference to an internal object, then call methods on it” to “find object and call method here right now”. Why? So I wouldn’t have to borrow it mutably twice. Because the compiler won’t let me. My code isn’t any safer and it was just annoying.

Rc<RefCell<T>> and Arc<Mutex<T>>. Besides the obvious “‘Nuff said”, why do I have to explicitly call .clone on Rc? It’s harder to use than std::shared_ptr.

Slices. Writing functions that slices and passing them vectors works well enough. I got tired of writing &var[..] though. Maybe I’m doing something wrong. Coming from D I wanted to avoid vectors and just slice arrays instead. Maybe that’s not Rusty. What about appending together some values to pass into a test? No Add impl for Vecs, so it’s massive pain. Sigh.

Statements vs Expressions. I haven’t yet made the mistake of forgetting/adding a semicolon, but I can see it happening.

No function overloading.

Serialization. There’s no way to do it well without reflection, and Rust is lacking here. I just did everything by hand, which was incredibly annoying. I’m spoiled though, in D I wrote what I think is a really good serialization library. Good in the lazy sense, I pretty much never have to write custom serialization code.

The ugly

Hashmaps. The language has operator overloading, but HashMap doesn’t use it. So it’s a very Java-like map.insert(key, value). If you want to create a HashMap with a literal… you can’t. There’s no equivalent macro to vec. You could write your own, but come on, this is a basic type from the standard library that will get used a lot. Even C++ does better!

Networking / concurrent IO. So I took a look at what my options were, and as far as my googling took me, it was to use native threads or a library called mio. mio’s API was… not the easiest to use so I punted and did what is the Rust standard library way of writing a server and used threads instead. I was sure I’d have performance problems down the road but it was something to worry about later. I went on writing my code, TDDed an implementation of a broker that wasn’t connected to the outside world and everything. At one point I realised that holding on to a mutable reference for subscribers wasn’t going to work so I used Rc<RefCell<Subscriber>> instead. It compiled, my tests passed, and all was good in the world. Then I tried actually using the broker from my threaded server. Since it’s not safe to use Rc<RefCell<>> in threads, this failed to compile. “Good!”, I thought, I changed Rc to Arc and RefCell to Mutex. Compile, run, …. deadlock. Oops. I had to learn mio after all. It wasn’t as bad as boost::asio but it wasn’t too far away either.

Comparing objects for identity. I just wanted to compare pointers. It was not fun. I had to write this:

fn is_same<T>(lhs: &T, rhs: &T) -> bool {
    lhs as *const T == rhs as *const T;
fn is_same_subscriber<T: Subscriber>(lhs: Rc<RefCell<T>>, rhs: Rc<RefCell<T>>) -> bool {
    is_same(&*lhs.borrow, &*rhs.borrow());



I thought I’d like Rust more than I actually do at this point. I’m glad I’m taking the time to learn it, but I’m not sure how likely I’ll choose to use it for any future project. Currently the only real advantage it has for me over D is that it has no runtime and could more easily be used on bare metal projects. But I’m unlikely to do any of those anytime soon.

I never thought I’d say this a few years back but…I like being able to fall back on a mark-and-sweep GC. I don’t have to use it in D either, so if it ever becomes a performance or latency problem I know how to deal with it. It seems to me to be far easier than getting the borrow checker to agree with me or having to change how I want to write my code.

We’ll see, I guess. Optimising the Rust implementation to be competitive with the D and Java ones is likely to be interesting.

Tagged , , , ,

Haskell actually does change the way you think

Last year I started trying to learn Haskell. There have been many ups and downs, but my only Haskell project so far is on hold while I work on other things. I’m not sure yet if I’d choose to use Haskell in production. The problems I had (and the time it’s taken so far) writing a simple server make me think twice, but that’s a story for another blog post.

The thing is, the whole reason I decided to learn Haskell were the many reports that it made me you think differently. As much as I like D, learning it was easy and essentially I’m using it as a better C++. There are things I routinely do in D that I wouldn’t have thought of or bother in C++ because they’re easier. But it’s not really changed my brain.

I didn’t think Haskell had either, until I started thinking of solutions to problems I was having in D in Haskell ways. I’m currently working on a build system, and since the configuration language is D, it has to be compiled. So I have interesting problems to solve with regards to what runs when: compile-time or run-time. Next thing I know I’m thinking of lazy evaluation, thunks, and the IO monad. Some things aren’t possible to be evaluated at compile-time in D. So I replaced a value with a function that when run (i.e. at run-time) would produce that value. And (modulo current CTFE limitations)… it works! I’m even thinking of making a wrapper type that composes nicely… (sound familiar?)

So, thanks Haskell. You made my head hurt more than anything I’ve tried learning since Physics, but apparently you’ve made me a better programmer.

Tagged , , , , , ,

The craziest code I ever wrote

A few years ago at work my buddy Jeff was as usual trying to do something in Go. I can’t remember why, but he wanted to arrange text strings in memory so that they were all contiguous. I said something about C++ and he remarked that the only thing C++11 could do that Go couldn’t would be perhaps to do this work at compile-time. I hadn’t learned D yet (which would have made the task trivial), so I spent the rest of the day writing the monstrosity below for “teh lulz”. It ended up causing my first ever question on Stackoverflow. “Enjoy” the code:

//Arrange strings contiguously in memory at compile-time from string literals.
//All free functions prefixed with "my" to faciliate grepping the symbol tree
//(none of them should show up).

#include <iostream>

using std::size_t;

//wrapper for const char* to "allocate" space for it at compile-time
template<size_t N>
struct String {
    //C arrays can only be initialised with a comma-delimited list
    //of values in curly braces. Good thing the compiler expands
    //parameter packs into comma-delimited lists. Now we just have
    //to get a parameter pack of char into the constructor.
    template<typename... Args>
    constexpr String(Args... args):_str{ args... } { }
    const char _str[N];

//takes variadic number of chars, creates String object from it.
//i.e. myMakeStringFromChars('f', 'o', 'o', '') -> String<4>::_str = "foo"
template<typename... Args>
constexpr auto myMakeStringFromChars(Args... args) -> String<sizeof...(Args)> {
    return String<sizeof...(args)>(args...);

//This struct is here just because the iteration is going up instead of
//down. The solution was to mix traditional template metaprogramming
//with constexpr to be able to terminate the recursion since the template
//parameter N is needed in order to return the right-sized String<N>.
//This class exists only to dispatch on the recursion being finished or not.
//The default below continues recursion.
template<bool TERMINATE>
struct RecurseOrStop {
    template<size_t N, size_t I, typename... Args>
    static constexpr String<N> recurseOrStop(const char* str, Args... args);

//Specialisation to terminate recursion when all characters have been
//stripped from the string and converted to a variadic template parameter pack.
struct RecurseOrStop<true> {
    template<size_t N, size_t I, typename... Args>
    static constexpr String<N> recurseOrStop(const char* str, Args... args);

//Actual function to recurse over the string and turn it into a variadic
//parameter list of characters.
//Named differently to avoid infinite recursion.
template<size_t N, size_t I = 0, typename... Args>
constexpr String<N> myRecurseOrStop(const char* str, Args... args) {
    //template needed after :: since the compiler needs to distinguish
    //between recurseOrStop being a function template with 2 paramaters
    //or an enum being compared to N (recurseOrStop < N)
    return RecurseOrStop<I == N>::template recurseOrStop<N, I>(str, args...);

//implementation of the declaration above
//add a character to the end of the parameter pack and recurse to next character.
template<bool TERMINATE>
template<size_t N, size_t I, typename... Args>
constexpr String<N> RecurseOrStop<TERMINATE>::recurseOrStop(const char* str,
                                                            Args... args) {
    return myRecurseOrStop<N, I + 1>(str, args..., str[I]);

//implementation of the declaration above
//terminate recursion and construct string from full list of characters.
template<size_t N, size_t I, typename... Args>
constexpr String<N> RecurseOrStop<true>::recurseOrStop(const char* str,
                                                       Args... args) {
    return myMakeStringFromChars(args...);

//takes a compile-time static string literal and returns String<N> from it
//this happens by transforming the string literal into a variadic paramater
//pack of char.
//i.e. myMakeString("foo") -> calls myMakeStringFromChars('f', 'o', 'o', '');
template<size_t N>
constexpr String<N> myMakeString(const char (&str)[N]) {
    return myRecurseOrStop<N>(str);

//Simple tuple implementation. The only reason std::tuple isn't being used
//is because its only constexpr constructor is the default constructor.
//We need a constexpr constructor to be able to do compile-time shenanigans,
//and it's easier to roll our own tuple than to edit the standard library code.

//use MyTupleLeaf to construct MyTuple and make sure the order in memory
//is the same as the order of the variadic parameter pack passed to MyTuple.
template<typename T>
struct MyTupleLeaf {
    constexpr MyTupleLeaf(T value):_value(value) { }
    T _value;

//Use MyTupleLeaf implementation to define MyTuple.
//Won't work if used with 2 String<> objects of the same size but this
//is just a toy implementation anyway. Multiple inheritance guarantees
//data in the same order in memory as the variadic parameters.
template<typename... Args>
struct MyTuple: public MyTupleLeaf<Args>... {
    constexpr MyTuple(Args... args):MyTupleLeaf<Args>(args)... { }

//Helper function akin to std::make_tuple. Needed since functions can deduce
//types from parameter values, but classes can't.
template<typename... Args>
constexpr MyTuple<Args...> myMakeTuple(Args... args) {
    return MyTuple<Args...>(args...);

//Takes a variadic list of string literals and returns a tuple of String<> objects.
//These will be contiguous in memory. Trailing '' adds 1 to the size of each string.
//i.e. ("foo", "foobar") -> (const char (&arg1)[4], const char (&arg2)[7]) params ->
//                       ->  MyTuple<String<4>, String<7>> return value
template<size_t... Sizes>
constexpr auto myMakeStrings(const char (&...args)[Sizes]) -> MyTuple<String<Sizes>...> {
    //expands into myMakeTuple(myMakeString(arg1), myMakeString(arg2), ...)
    return myMakeTuple(myMakeString(args)...);

//Prints tuple of strings
template<typename T> //just to avoid typing the tuple type of the strings param
void printStrings(const T& strings) {
    //No std::get or any other helpers for MyTuple, so intead just cast it to
    //const char* to explore its layout in memory. We could add iterators to
    //myTuple and do "for(auto data: strings)" for ease of use, but the whole
    //point of this exercise is the memory layout and nothing makes that clearer
    //than the ugly cast below.
    const char* const chars = reinterpret_cast<const char*>(&strings);
    std::cout << "Printing strings of total size " << sizeof(strings);
    std::cout << " bytes:\n";
    std::cout << "-------------------------------\n";

    for(size_t i = 0; i < sizeof(strings); ++i) {
        chars[i] == '' ? std::cout << "\n" : std::cout << chars[i];

    std::cout << "-------------------------------\n";
    std::cout << "\n\n";

int main() {
        constexpr auto strings = myMakeStrings("foo", "foobar",
                                               "strings at compile time");

        constexpr auto strings = myMakeStrings("Some more strings",
                                               "just to show Jeff to not try",
                                               "to challenge C++11 again :P",
                                               "with more",
                                               "to show this is variadic");

    std::cout << "Running 'objdump -t |grep my' should show that none of the\n";
    std::cout << "functions defined in this file (except printStrings()) are in\n";
    std::cout << "the executable. All computations are done by the compiler at\n";
    std::cout << "compile-time. printStrings() executes at run-time.\n";
Tagged , , , , , , ,

Haskell monads for C++ programmers

I’m not going to get into the monad tutorial fallacy. Also, I think this blog about another monad fallacy sums it up nicely: the problem isn’t understanding what monads are, but rather understanding how they can be used. Understanding the monad laws isn’t hard. Understanding how to use the Maybe monad isn’t hard either. But things get tricky pretty fast and there’ s a kind of monads that are similar to each other that took me a while to understand how to use. That is, until I recognised what they actually were: C++ template metaprogramming. I guess it’s the opposite realisation that Bartoz Milewski had.

The analogy is only valid for a few monads. The ones I’ve seen that this applies to are IO, State, and Get from Data.Binary. These are the monads that are referred to as computations, which sounds really abstract, but really functions that return these monads return mini-programs. These mini-programs don’t immediately do anything, they need to be executed first. In IO’s case that’s done by the runtime system, for State the runState does that for you (I’m stretching here – only IO really does anything, even runState is pure).

It’s similar to template metaprogramming in C++: at compile-time the programmer has access to a functional language with no side-effects that returns a function that at runtime (i.e. when executed) actually does something. After that realisation I got a lot better at understanding how and why to use them.

The monad issue doesn’t end there, unfortunately. There are many other monads that aren’t like C++ templates at all. But the ones that are – well, at least you’ll be able to recognise them now.

Tagged , , ,

Computer languages: ordering my favourites

This isn’t even remotely supposed to be based on facts, evidence, benchmarks or anything like that. You could even disagree with what are “scripting languages” or not. All of the below just reflect my personal preferences. In any case, here’s my list of favourite computer languages, divided into two categories: scripting and, err… I guess “not scripting”.


My favourite scripting languages, in order:

  1. Python
  2. Ruby
  3. Emacs Lisp
  4. Lua
  5. Powershell
  6. Perl
  7. bash/zsh
  8. m4
  9. Microsoft batch files
  10. Tcl


I haven’t written enough Ruby yet to really know. I suspect I’d like it more than Python but at the moment I just don’t have enough experience with it to know its warts. Even I’m surprised there’s something below Perl here but Tcl really is that bad. If you’re wondering where PHP is, well I don’t know because I’ve never written any but from what I’ve seen and heard I’d expect it to be (in my opinion of course) better than Tcl and worse than Perl. I’m surprised how high Perl is given my extreme dislike for it. When I started thinking about it I realised there’s far far worse.


My favourite non-scripting languages, in order:

  1. D
  2. C++
  3. Haskell
  4. Common Lisp
  5. Rust
  6. Java
  7. Go
  8. Objective C
  9. C
  10. Pascal
  11. Fortran
  12. Basic / Visual Basic

I’ve never used Scheme, if that explains where Common Lisp is. I’m still learning Haskell so not too sure there. As for Rust, I’ve never written a line of code in it and yet I think I can confidently place it in the list, especially with respect to Go. It might place higher than C++ but I don’t know yet.


Tagged , , , , , , , , , , , , ,

Adding Java and C++ to the MQTT benchmarks or: How I Learned to Stop Worrying and Love the Garbage Collector

This is a followup to my first post, where I compared different MQTT broker implementations written in D, C, Erlang and Go. Then my colleague who wrote the Erlang version decided to write a Java version too, and I felt compelled to do a C+11 implementation. This was only supposed to simply add the results of those two to the benchmarks but unfortunately had problems with the C++ version, which led to the title of this blog post. More on that later. Suffice it to say for now that the C++ results should be taken with a large lump of salt. Results:

loadtest (throughput - bigger is better)
Connections:         500            750            1k
D + vibe.d:          166.9 +/- 1.5  171.1 +/- 3.3  167.9 +/- 1.3
C (Mosquitto):       122.4 +/- 0.4   95.2 +/- 1.3   74.7 +/- 0.4
Erlang:              124.2 +/- 5.9  117.6 +/- 4.6  117.7 +/- 3.2
Go:                  100.1 +/- 0.1   99.3 +/- 0.2   98.8 +/- 0.3
Java:                105.1 +/- 0.5  105.8 +/- 0.3  105.8 +/- 0.5
C++11 + boost::asio: 109.6 +/- 2.0  107.8 +/- 1.1  108.5 +/- 2.6

pingtest (throughput constrained by latency - bigger is better)
parameters:          400p 20w       200p 200w      100p 400w
D + vibe.d:          50.9 +/- 0.3   38.3 +/- 0.2   20.1 +/- 0.1
C (Mosquitto):       65.4 +/- 4.4   45.2 +/- 0.2   20.0 +/- 0.0
Erlang:              49.1 +/- 0.8   30.9 +/- 0.3   15.6 +/- 0.1
Go:                  45.2 +/- 0.2   27.5 +/- 0.1   16.0 +/- 0.1
Java:                63.9 +/- 0.8   45.7 +/- 0.9   23.9 +/- 0.5
C++11 + boost::asio: 50.8 +/- 0.9   44.2 +/- 0.2   21.5 +/- 0.4

In loadtest the C++ and Java implementations turned out to be in the middle of the pack with comparable performance between the two. Both of them are slightly worse than Erlang and D is still a good distance ahead. In pingtest it gets more interesting: Java mostly matches the previous winner (the C version) and beats it in the last benchmark, so it’s now the clear winner. The C++ version matches both of those in the middle benchmark, does well in the last one but only performs as well as the D version in the first one. A win for Java.

Now about my C++ woes: I brought it on myself a little bit, but the way I approached it was by trying to minimise the amount of work I had to do. After all, writing C++ takes a long while at the best of times so I went and ported it from my D version by translating it by hand. I gleaned a few insights from doing so:

  • Using C++11 made my life a lot easier since it closes the gap with D considerably.  const and immutable became const auto, auto remained the same except when used as a return value, etc.
  • Having also written both C++ and D versions of the serialisation libraries I used as well as the unit-testing ones made things a lot easier, since I used the same concepts and names.
  • I’m glad I took the time to port the unit tests as well. I ended up introducing several bugs in the manual translation.
  • A lot of those bugs were initialisation errors that simply don’t exist in D. Or Java. Or Go. Sigh.
  • I hate headers with a burning passion. Modules should be the top C++17 priority IMHO since there’s zero chance of them making into C++14.
  • I missed slices. A lot. std::vector and std::deque are poor substitutes.
  • Trying to port code written in a garbage collected language and trying to simply introduce std::unique_ptr and std::shared_ptr where appropriate was a massive PITA. I’m not even sure I got it right, more on that below.

The C++ implementation is incomplete and will continue to be like that, since I’m now bored of it, tired, and just want to move on. It’s also buggy. All of the loadtest benchmarks were done with only 1000 messages instead of the values at the top since it crashes if left to run for long enough. I’m not going to debug it because it’s not going to be any fun and nobody is paying me to do it.

It’s not optimised either. I never even bothered to run a profiler. I was going to do it as soon as I fixed all the bugs but I gave up long before that. I know it’s doing excessive copying because copying vectors of bytes around was the easiest way I could get it to compile after copying the D code using slices. It was on my TODO list to remove and replace with iterators, but, as I mentioned, it’s not going to happen.

I reckon a complete version would probably do as well as Java at pingtest but have a hunch that D would probably still win loadtest. This is, of course, pure speculation. So why did I bother to include the C++ results? I thought it would still be interesting and give a rough idea of how it would compare. I wish I had the energy to finish it, but I just wasn’t having fun anymore and I don’t see the point. Writing it from scratch in C++ would have been a better idea, but it definitely would have taken a longer amount of time. It would’ve looked similar to what I have now anyway (I’d still be the author), but I have the feeling it would have fewer bugs. Thinking about memory management from the start is very different from trying to apply smart pointers to an already existing design that depended on a garbage collector.

My conclusion from all of this is that I really don’t want to write C++ again unless I have to. And that for all the misgivings I had about a garbage collector, it saves me time that I would’ve used tracking down memory leaks, double frees and all of those other “fun” activities. And, at least for this exercise, it doesn’t even seem to make a dent in performance. Java was the pingtest winner after all, but its GC is a lot better than D’s. To add insult to C++’s injury, that Java implementation took Patrick a morning to write from scratch, and an afternoon to profile and optimise. It took me days to port an existing working implementation from the closest language there is to C++ and ended up with a crashing binary. It just wasn’t worth the time and effort, but at least now I know that.

Tagged , , , , , , , , , , , , , , , , ,