Project Highlight: workspace-d

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Not so long ago, Jan Jurzitza sat down at his keyboard intent on writing a D plugin for Atom, his text editor of choice at the time. Then came disappointment.

“I was pretty unhappy with their API,” he says.

Visual Studio Code was released a short time after. He decided to give it a go and “instantly fell in love with it”. His Atom plugin was pushed aside and he started work on a new plugin for VS Code called code-d.

However, I did not want to maintain the same functionality in two plugins for two different text editors, so I thought that making a program which contains most of the plugin logic, like starting and calling dcd, dscanner, dfmt, etc., would be beneficial and would also help with including D support in more editors and IDEs in the future.

For the uninitiated, DCD (the D Completion Daemon), DScanner, and Dfmt are D-oriented tools for plugin developers, all maintained by Brian Schott. They are, respectively, a client-server based auto-completion program, a source code analyzer, and a code formatter. A number of IDE and text editor plugins employ them directly.

So Jan started work on his new tool and named it workspace-d.

With workspace-d I want to make it simple for plugin developers to integrate D functionality into their editor of choice. workspace-d is designed to work both as a standalone program through stdio and as a D library. Once I ported most of the code from my Atom extension to workspace-d, I could simply spawn it as a subprocess in code-d, which I got working with it quite quickly.

In addition to porting his Atom plugin to use workspace-d, he also created one for Sublime Text. Currently, he’s not devoting any time to either and is looking for someone else to take over maintenance of one or both. Anyone interested might start by submitting pull requests. Aside from workspace-d itself, Jan’s focus is on code-d.

He’s recently been working on version 2.0 of workspace-d, with a focus on streamlining the way it handles requests.

Using traits, templates, and CTFE (Compile-Time Function Execution), basically all D compile time magic, I was able to make an automatic wrapper for the functions for version 2.0. Basically, when a request like {"cmd":"hello"} comes in, it runs the D function hello with its default arguments. If the arguments don’t match, it responds with an error. This system automatically binds function arguments to JSON values and generates a response from the return value.

To deserialize the JSON requests, he’s using painlessjson, a third-party library available in the DUB package registry.

It works really great and I can really recommend it for some simple and easy conversions between D types and JSON. This change really cleaned up all the code and made it possible to use workspace-d as a library.

He’s also working on a new project, serve-d, that works with Microsoft’s Language Server Protocol.

serve-d is an alternative for the workspace-d command line I/O for those who prefer JSON RPC over my custom binary/JSON mix. It’s fiber based and uses workspace-d as a library, which results in really clean code. There’s an alpha version of the implementation on github already, both the server and a new branch on code-d. With the Language Server Protocol, I’m hoping for easier integration in other editors. The concept is basically the same as workspace-d’s command line interface, but, because Microsoft is such a big company, I’m hoping that more editors by big developers are going to implement this protocol.

Building and installing workspace-d should go pretty smoothly on Linux or OS X, but it’s currently a little bumpy on Windows. Because of an issue Jan has yet to resolve, it can only be built on Windows with LDC.

The auto completion didn’t work for some people on Windows because it got stuck in the std.process.execute function when creating a pipe to write to. I couldn’t find any way to reproduce it in a standalone program so I couldn’t file a bug either. So what we did to avoid this issue in the short term was to simply disallow compilation on Windows using DMD. It works just fine when compiled with LDC.

Jan’s primarily a Linux user (he doesn’t own a Mac and only runs Windows in a VM). He credits GitHub user @Andrepuel for getting it operational on OS X, and @aka-demik for finding the issue on Windows and verifying that it compiles with LDC. He’ll be grateful to anyone who can help fully resolve the Windows/DMD issue once and for all.

If you’re looking to develop a D plugin for your favorite editor, consider taking advantage of the work Jan as already done with workspace-d to save yourself some effort. And VS Code users can put it to use via code-d to get code completion and more. Visit its VS Code marketplace page to read reviews and installation instructions.

Don’t Fear the Reaper

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D, like many other programming languages in active use today, comes with a garbage collector out of the box. There are many types of software that can be written without worrying at all about the GC, taking full advantage of its benefits. But the GC does have drawbacks, and there are certainly scenarios in which garbage collection is undesirable. For those situations, the language provides the means to temporarily disable it, or even avoid it completely.

In order to maximize the positive impacts of garbage collection and minimize any negative, it’s necessary to have a good grounding in how the GC works in D. A good place to start is the Garbage Collection page at dlang.org, which outlines the rationale for D’s GC and provides some tips on working with it. This post is the first in a series intended to expand on the information provided on that page.

This time, we’ll look at the very basics, focusing on the language features that can trigger GC allocations. Future posts will introduce ways to disable the GC when necessary, as well as idioms useful in dealing with its nondeterministic nature (e.g. managing resources in the destructors of GC-managed objects).

The first thing to understand about D’s garbage collector is that it only runs during allocation, and only if there is no memory available to allocate. It isn’t sitting in the background, periodically scanning the heap and collecting garbage. This knowledge is fundamental to writing code that makes efficient use of GC-managed memory. Take the following example:

void main() {
    int[] ints;
    foreach(i; 0..100) {
        ints ~= i;
    }
}

This declares a dynamic array of int, then uses D’s append operator to append the numbers 0 to 99 in a foreach range loop. What isn’t obvious to the untrained eye is that the append operator makes use of the GC heap to allocate space for the values it adds to the array.

DRuntime’s array implementation isn’t a dumb one. In the example, there aren’t going to be one hundred allocations, one for each value. When more memory is needed, the implementation will allocate more space than is requested. In this particular case, it’s possible to determine how many allocations are actually made by making use of the capacity property of D’s dynamic arrays and slices. This returns the total number of elements the array can hold before an allocation is necessary.

void main() {
    import std.stdio : writefln;
    int[] ints;
    size_t before, after;
    foreach(i; 0..100) {
        before = ints.capacity;
        ints ~= i;
        after = ints.capacity;
        if(before != after) {
            writefln("Before: %s After: %s",
                before, after);
        }
    }
}

Executing this when compiled with DMD 2.073.2 shows the message is printed six times, meaning there were six total GC allocations in the loop. That means there were six opportunities for the GC to collect garbage. In this small example, it almost certainly didn’t. If this loop were part of a larger program, with GC allocations throughout, it very well might.

On a side note, it’s informative to examine the values of of before and after. Doing so shows a sequence of 0, 3, 7, 15, 31, 63, and 127. So by the end, ints contains 100 values and has space for appending 27 more before the next allocation, which, extrapolating from the values in the sequence, should be 255. That’s an implementation detail of DRuntime, though, and could be tweaked or changed in any release. For more details on how arrays and slices are managed by the GC, take a look at Steven Schveighoffer’s excellent article on the topic.

So, six allocations, six opportunities for the GC to initiate one of its pauses of unpredictable length even in that simple little loop. In the general case, that could become an issue depending on if the loop is in a hot part of code and how much total memory is allocated from the GC heap. But even then, it’s not necessarily a reason to disable the GC in that part of the code.

Even with languages that don’t come with a stock GC out of the box, like C and C++, most programmers learn at some point that it’s better for overall performance to allocate as much as possible up front and minimize allocations in the inner loops. It’s one of the many types of premature optimization that are not actually the root of all evil, something we tend to call best practice. Given that D’s GC only runs when memory is allocated, the same strategy can be applied as a simple way to mitigate any potential impact it could have on performance. Here’s one way to rewrite the example:

void main() {
    int[] ints = new int[](100);
    foreach(i; 0..100) {
        ints[i] = i;
    }
}

Now we’ve gone from six allocations down to one. The only opportunity the GC has to run is before the inner loop. This actually allocates space for at least 100 values and initializes them all to 0 before entering the loop. The array will have a length of 100 after new, but will almost certainly have additional capacity.

There’s an alternative to new for arrays: the reserve function:

void main() {
    int[] ints;
    ints.reserve(100);
    foreach(i; 0..100) {
        ints ~= i;
    }
}

This allocates memory for at least 100 values, but the array is still empty (its length property will return 0) when it returns, so nothing is default initialized. Given that the loop only appends 100 values, it’s guaranteed not to allocate.

In addition to new and reserve, it’s possible to call GC.malloc directly for explicit allocation.

import core.memory;
void* intsPtr = GC.malloc(int.sizeof * 100);
auto ints = (cast(int*)intsPtr)[0 .. 100];

Array literals will usually allocate.

auto ints = [0, 1, 2];

This is also true when an array literal enum is used.

enum intsLiteral = [0, 1, 2];
auto ints1 = intsLiteral;
auto ints2 = intsLiteral;

An enum exists only at compile time and has no memory address. Its name is a synonym for its value. Everywhere you use one, it’s like copying and pasting its value in place of its name. Both ints1 and ints2 trigger allocations exactly as if they were declared like so:

auto ints1 = [0, 1, 2];
auto ints2 = [0, 1, 2];

Array literals do not allocate when the target is a static array. Also, string literals (strings in D are arrays under the hood) are an exception to the rule.

int[3] noAlloc1 = [0, 1, 2];
auto noAlloc2 = "No Allocation!";

The concatenate operator will always allocate:

auto a1 = [0, 1, 2];
auto a2 = [3, 4, 5];
auto a3 = a1 ~ a2;

D’s associative arrays have their own allocation strategy, but you can expect them to allocate when items are added and potentially when removed. They also expose two properties, keys and values, which both allocate arrays and fill them with copies of the respective items. When its desirable to modify the underlying associative array during iteration, or when the items need to be sorted or otherwise manipulated independently of the associative array, these properties are just what the doctor ordered. Otherwise, they’re needless allocations that put undue pressure on the GC.

When the GC does run, the total amount of memory it needs to scan is going to determine how long it takes. The smaller, the better. Avoiding unnecessary allocations isn’t going to hurt anyone and is another good mitigation strategy. D’s associative arrays provide three properties that help do just that: byKey, byValue, and byKeyValue. These each return forward ranges that can be iterated lazily. They do not allocate because they actually refer to the items in the associative array, so it should not be modified while iterating them. For more on ranges, see the chapters titled Ranges and More Ranges in Ali Çehreli’s Programming in D.

Closures, which are delegates or function literals that need to carry around a pointer to the local stack frame, may also allocate. The last allocating language feature listed on the Garbage Collection page is the assertion. An assertion will allocate when it fails because it needs to throw an AssertError, which is part of D’s class-based exception hierarchy (we’ll look at how classes interact with the GC in a future post).

Then there’s Phobos, D’s standard library. Once upon a time, much of Phobos was implemented with little concern for GC allocations, making it difficult to use in situations where they were undesirable. However, a massive effort was initiated
to make it more conservative in its GC usage. Some functions were made to work with lazy ranges, others were rewritten to take buffers supplied by the caller, and some were reimplemented to avoid unnecessary allocations internally. The result is a standard library more amenable to GC-free code (though there are still probably some corners of the library that have not yet been renovated — PRs welcome).

Now that we’ve seen the basics of using the GC, the next post in this series will look at the tools the language and the compiler provide for turning the GC off and making sure specific sections of code are GC-free.

Thanks to Guillaume Piolat and Steven Schveighoffer for their help with this article.

Editable and Runnable Doc Examples on dlang.org

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Sebastian Wilzbach was a GSoC student for the D Language Foundation in 2016 and has since become a regular contributor to Phobos, D’s standard library, and dlang.org.


This article explains the steps that were needed to have editable and runnable examples in the documentation on dlang.org. First, let’s begin with the building blocks.

Unit testing in D

One of D’s coolest features is its unittest block, which allows the insertion of testable code anywhere in a program. It has become idiomatic for a function to be followed directly by its tests. For example, let’s consider a simple function add which is accompanied by two tests:

auto add(int a, int b)
{
    return a + b;
}

unittest
{
    assert(2.add(2) == 4);
    assert(3.add(4) == 7);
}

By default, all unittest blocks will be ignored by the compiler. Specifying -unittest on the compiler’s command line will cause the unit tests to be included in the compiled binary. Combined with -main, tests in D can be directly executed with:

rdmd -main -unittest add.d

If a unittest block is annotated with embedded documentation, a D documentation generator can also display the tests as examples in the generated documentation. The DMD compiler ships with a built-in documentation generator (DDoc), which can be run with the -D flag, so executing:

dmd -D -main add.d

would yield the documentation of the add function above with its tests displayed as examples, as demonstrated here:

Please note that the documentation on dlang.org is generated with DDoc. However, in case you don’t like DDoc, there are several other options.

Executing code on the web

Frequent readers of the D Blog might remember Damian Ziemba’s DPaste – an online compiler for the D Programming language. In 2012, he made the examples on the front page of D’s website runnable via his service. Back in those old days, the website of the D Programming language looked like this:

As a matter of fact, until 2015, communication with DPaste was done in XML.

Putting things together

So D has a unit test system that allows placing executable unit tests next to the functions they test, the tests can also be rendered as examples in the generated documentation, and there exists a service, in the form of DPaste, that allows D code to be executed on the web. The only thing missing was to link them together to produce interactive documentation for a compiled language.

There was one big caveat that needed to be addressed before that could happen. While D’s test suite, which is run on ten different build machines, ensures that all unit tests compile & run without errors, an extracted test might contain symbols that were imported at module scope and thus wouldn’t be runnable on dlang.org. A unittest block can only be completely independent of the module in which it is declared if all of its symbols are imported locally in the test’s scope. The solution was rather simple: extract all tests from Phobos, then compile and execute them separately to ensure that a user won’t hit a “missing import” error on dlang.org. Thanks to D’s ultra-fast frontend, this step takes less than a minute on a typical machine in single-core build mode.

Moreover, to prevent any regressions, this has been integrated into Phobos’s test suite and is run for every PR via CircleCi. As Phobos has extensive coverage with unit tests, we started this transition with a blacklist and, step-by-step, removed modules for which all extracted tests compile. With continuous checking in place, we were certain that none of the exposed unit tests would throw any errors when executed in the documentation, so we could do the flip and replace the syntax-highlighted unit test examples with an interactive code editor.

Going one step further

With this setup in place, hitting the “Run” button would merely show the users “All tests passed”. While that’s always good feedback, it conveys less information than is usually desirable.

Documentation that supports runnable examples tends to send any output to stdout. This allows the reader to take the example and modify it as needed while still seeing useful output about the modifications. So, for example, instead of using assertions to validate the output of a function, which is idiomatic in D unit tests and examples:

assert(myFun() == 4);

Other documentation usually prints to stdout and shows the expected output in a comment. In D, that would look like this:

writeln(myFun()); // 4

I initially tried to do such a transformation with regular expressions, but I was quickly bitten by the complexity of a context-free language. So I made another attempt using Brian Schott’s libdparse, a library to parse and lex D source code. libdparse allows one to traverse the abstract syntax tree (AST) of a D source file. During the traversal of the AST, the transformation tool can rewrite all AssertExpressions into writeln calls, similar to the way other documentation displays examples. To speak in the vocabulary of compiler devs: we are lowering AssertExpressions into the more humanly digestible writeln calls!

Once the AST has been traversed and modified, it needs to be transformed into source code again. This led to improvements in libdparse’s formatting capabilities (1, 2).

The future

As of now, there are still a small number of functions in Phobos that don’t have a nice public example that is runnable on dlang.org. Tooling to check for this has recently been activated in Phobos. So now you can use this tool (make -f posix.mak has_public_example) to find functions lacking public tests and remove those modules from the blacklist.

Another target for improvement is DPaste. For example, it currently doesn’t cache incoming requests, which could improve the performance of executed examples on dlang.org. However, due to the fast compilation speed of the DMD compiler, this “slow-down” isn’t noticeable and is more of a perfectionist wish.

I hope you enjoy the new “Run” button on the documentation and have as much fun playing with it as I do. Click here to get started.

Project Highlight: vibe.d

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Since the day Sönke Ludwig first announced vibe.d on the D Forums, the project has been a big hit in the D community. It’s the exclusive subject of one book, has a chapter of its own in another, and has been proven in production both commercially and otherwise. As so many projects do, it all started out of frustration.

I was dissatisfied with existing network web libraries (in particular with Node.js, which was the new big thing back then, because it was also built on an asynchronous I/O model). D 2.0 gained cross platform fiber support through the integration of DRuntime, which seemed like a perfect opportunity to avoid the shortcomings of Node.js’s programming model (“callback hell”). Together with D’s strong type checking and the high performance of natively compiled applications this had the ideal preconditions for creating a network framework.

From the initial release, work progressed on adding web and REST interface generators (vibe.web.web and vibe.web.rest, respectively).

This was made possible by D’s advanced meta programming facilities, string mixins and compile-time reflection in particular. The eventual addition of user-defined attributes to the language enabled some important advances later on, such as the recently added authorization framework.

Vibe.d is at its core an I/O and concurrency framework that makes heavy use of fibers which run in a quasi-parallel framework.

Every time an operation (e.g. reading from a socket) needs to wait, the fiber yields execution, so another fiber can run instead. Each fiber uses up very little memory compared to a full thread and switching between fibers is very cheap. This enables highly scalable applications that behave like normal multithreaded applications (save for the low-level issues associated with real multithreading).

At a higher level, it can serve as a web framework for backend development and provides functionality for protocols like HTTP and SMTP, database connectivity, and the parsing of data formats. A number of third-party packages that extend or complement vibe.d can be found in the DUB repository (Sönke is also the creator and maintainer of DUB, the D build tool and package manager).

Big changes are currently afoot with the project. Beginning with the release of vibe.d 0.7.27 in February 2016, work began on splitting the monolithic project into independent DUB packages. One goal is to make it possible to use one vibe.d component without pulling them all in, reducing build times in the process.

Another goal is to employ modern D idioms where possible and to improve memory usage and performance as far as possible. It is surprising how much D evolved in just the short amount of time that vibe.d has been alive!

Diet-NG, vibe.d’s template engine based on Jade, was the first to be granted independence. It went through a complete rewrite that adds a strong test suite, makes use of D’s ranges where possible, provides a more flexible API, and eliminates dependencies on other vibe.d packages. Now he’s working on the core package.

The vibe-core package encapsulates the whole event and fiber logic, including I/O, tasks, concurrency primitives and general operating system abstraction. The original design was based heavily on classes and interfaces and had a very high level operating system abstraction layer, resulting in several downsides. For example, there was a dependence on the GC and virtual function calls could be an issue on certain platforms. One of the main goals was to minimize performance overhead in the new implementation.

As part of his experimentation with different API idioms and slimming down the code base, he produced the eventcore library.

The API follows a proactor pattern, meaning that a callback gets invoked whenever a certain asynchronous operation finishes. This is in contrast to the reactor pattern that is exposed by the non-blocking Posix APIs. It was chosen mainly so that asynchronous I/O APIs, such as Windows overlapped I/O and POSIX AIO, could be supported.

On top of eventcore, the fiber logic was implemented in a completely general way, using a central fiber scheduler and a generic asyncAwait function. This means that lots of corner cases are handled in a much more robust way now and that improvements in all areas can be made much faster and with fewer chances of breaking anything.

Next on the list for independence is the HTTP package. Sönke plans to completely rebuild the package from the ground up, adding HTTP/2 support and making it possible to enable allocation-free request/response processing.

Other obvious candidates are MongoDB and Redis clients, JSON and BSON support, the serialization framework, and the Markdown parser. The goal for each of these packages is always to take a look at the code and employ modern D idioms during the process.

If you’ve never taken D for a spin, vibe.d is a fun playground in which to do so. It’s not difficult to get up and running, and easier still if you have experience with such frameworks in other languages. It’s also ready to put into production in its current state, despite the leading zero in the version number. As Sönke makes progress on breaking it up into separate packages, it will almost certainly become an even more integral part of the growing D community.

Snowflake Strings

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Walter Bright is the BDFL of the D Programming Language and founder of Digital Mars. He has decades of experience implementing compilers and interpreters for multiple languages, including Zortech C++, the first native C++ compiler. He also created Empire, the Wargame of the Century.


Consider the following D code in file.d:

int foo(int i) {
    assert(i < 3);
    return i;
}

This is equivalent to the C code:

#include <assert.h>

int foo(int i) {
    assert(i < 3);
    return i;
}

The assert() in the D code is “lowered” (i.e. rewritten by the compiler) to the following:

(i < 3 || _d_assertp("file.d", 2))

We’re interested in how the compiler writes that string literal, "file.d" to the generated object file. The most obvious implementation is to write the characters into the data section and push the address of that to call _d_assertp().

Indeed, that does work, and it’s tempting to stop there. But since we’re professional compiler nerds obsessed with performance, details, etc., there’s a lot more oil in that olive (to borrow one of Andrei’s favorite sayings). Let’s put it in a press and start turning the screw, because assert()s are used a lot.

First off, string literals are immutable (they were originally mutable in C and C++, but are no longer, and D tries to learn from such mistakes). This suggests the string can
be put in read-only memory. What advantages does that deliver?

  • Read-only memory is, well, read only. Attempts to write to it are met with a seg fault exception courtesy of the CPUs memory management logic. Seg faults are a bit graceless, like a cop pulling you over for driving on the wrong side of the road, but at least there wasn’t a head-on collision or corruption of the program’s memory.
  • Read-only pages are never swapped out by the virtual memory system; they never get marked as “dirty” because they are never written to. They may get discarded and reloaded, but that’s much less costly.
  • Read-only memory is safe from corruption by malware (unless the malware infects the MMU, sigh).
  • Read-only memory in a shared library is shared – copies do not have to be made for each user of the shared library.
  • Read-only memory does not need to be scanned for pointers to the heap by the garbage collection system (if the application does GC).

Essentially, shoving as much as possible into read-only memory is good for performance, size and safety. There’s the first drop of oil.

The next issue crops up as soon as there’s more than one assert:

int foo(int i, int j) {
    assert(i < 3);
    assert(j & 1);
    return i + j;
}

The compiler emits two copies of "file.d" into the object file. Since they’re identical, and read-only, it makes sense to only emit one copy:

string TMP = "file.d";
int foo(int i, int j) {
    (i < 3 || _d_assertp(TMP, 2))
    (j & 1 || _d_assertp(TMP, 3))
    return i + j;
}

This is called string pooling and is fairly simple to implement. The compiler maintains a hash table of string literals and their associated symbol names (TMP in this case).

So far, this is working reasonably well. But when asserts migrate into header files, macros, and templates, the same string can appear in lots of object files, since the compiler doesn’t know what is happening in other object files (the separate compilation model). Other string literals can exhibit this behavior, too, when generic coding practices are used. There needs to be some way to present these in the object file so the linker can pool identical strings.

The dmd D compiler currently supports four different object file formats on different platforms:

  • Elf, for Linux and FreeBSD
  • Mach-O, for OSX
  • MS-COFF, for Win64
  • OMF, for Win32

Each does it in a different way, with different tradeoffs. The methods tend to be woefully under documented, and figuring this stuff out is why I get paid the big bucks.

Elf

Elf turns out to have a magic section just for this purpose. It’s named .rodata.strM.N where N is replace by the number of bytes a character has, and M is the alignment. For good old char strings, that would be .rodata.str1.1. The compiler just dumps the strings into that section, and the Elf linker looks through it, removing the redundant strings and adjusting the relocations accordingly. It’ll handle the usual string types – char, wchar, and dchar – with aplomb.

There’s just a couple flaws. The end of a string is determined by a nul character. This means that strings cannot have embedded nuls, or the linker will regard them as multiple strings and shuffle them about in unexpected ways. One cannot have relocations in those sections, either. This means it’s only good for C string literals, not other kinds of data.

This poses a problem for D, where the strings are length-delineated strings, not nul-terminated ones. Does this mean D is doomed to being unable to take advantage of the C-centric file formats and linker design? Not at all. The D compiler simply appends a nul when emitting string literals. If the string does have an embedded nul (allowed in D), it is not put it in these special sections (and the benefit is lost, but such strings are thankfully rare).

Mach-O

Mach-O uses a variant of the Elf approach, a special section named __cstring. It’s more limited in that it only works with single byte chars. No wchar_ts for you! If there ever was confirmation that UTF-16 and UTF-32 are dead end string types, this should be it.

MS-COFF

Microsoft invented MS-COFF by extending the old Unix COFF format. It has many magic sections, but none specifically for strings. Instead, it uses what are called COMDAT sections, one for each string. COMDATs are sections tagged with a unique name, and when the linker is faced with multiple COMDATs with the same name, one is picked and all references to the other COMDATs are rewritten to refer to the Anointed One. COMDATs first appeared in object formats with the advent of C++ templates, since template code generation tends to generate the same code over and over in separate files.

(Isn’t it interesting how object file formats are driven by the needs of C and C++?)

The COMDAT for "hello" would look something like this:

??_C@_05CJBACGMB@hello?$AA@:
db 'h', 'e', 'l', 'l', 'o', 0

The tty noise there is the mangled name of the COMDAT which is generated from the string literal’s contents. The algorithm must match across compilation units, as that is how the linker decides which ones are the same (experimenting with it will show that the substring CJBACGMB is some sort of hash). Microsoft’s algorithm for the mangling and hash is undocumented as far as I can determine, but it doesn’t matter anyway, it only has to have a 1:1 mapping between name and string literal. That screams “MD5 hash” to me, so that’s what dmd does. The name is an MD5 hash of the string literal contents, which also has the nice property that no matter how large the string gets, the identifier doesn’t grow.

COMDATs can have anything stuffed in them, so this is a feature that is usable for a lot more than just strings.

The downside of the COMDAT scheme is the space taken up by all those names, so shipping a program with the debug symbols in it could get much larger.

OMF

The caboose is OMF, an ancient format going back to the early 80’s. It was extended with a kludgy COMDAT system to support C++ just before most everyone abandoned it. DMD still emits it for Win32 programs. We’re stuck with it because it’s the only format the default linker (OPTLINK) understands, and so we find a way to press it into service.

Since it has COMDATs, that’s the mechanism used. The wrinkle is that COMDATs are code sections or data sections only; there are no other options. We want it to be read-only, so the string COMDATs are emitted as code sections (!). Hey, it works.

Conclusion

I don’t think we’ve pressed all the oil out of that olive yet. It may be like memcpy, where every new crop of programmers thinks of a way to speed it up.

I hope you’ve enjoyed our little tour of literals, and may all your string literals be unique snowflakes.

Thanks to Mike Parker for his help with this article.

A New Import Idiom

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Daniel Nielsen is an Embedded Software Engineer. He is currently using D in his spare time for an unpublished Roguelike and warns that he “may produce bursts of D Evangelism”.


I remember one day in my youth, before the dawn of Internet, telling my teachers about “my” new algorithm, only to learn it had been discovered by the ancient Greeks in ~300 BC. This is the story of my life and probably of many who are reading this. It is easy to “invent” something; being the first, not so much!

Anyway, this is what all the fuss is about this time:

template from(string moduleName)
{
  mixin("import from = " ~ moduleName ~ ";");
}

The TL;DR version: A new idiom to achieve even lazier imports.

Before the C programmers start running for the hills, please forget you ever got burned by C++ templates. The above snippet doesn’t look that complicated, now does it? If you enjoy inventing new abstractions, take my advice and give D a try. Powerful, yet an ideal beginner’s language. No need to be a template archwizard.

Before we proceed further, I’d like to call out Andrei Alexandrescu for identifying that there is a problem which needs solving. Please see his in depth motivation in DIP 1005. Many thanks also to Dominikus Dittes Scherkl, who helped trigger the magic spark by making his own counter proposal and questioning if there really is a need to change the language specification in order to obtain Dependency-Carrying Declarations (DIP 1005).

D, like many modern languages, has a fully fledged module system where symbols are directly imported (unlike the infamous C #include). This has ultimately resulted in the widespread use of local imports, limiting the scope as much as possible, in preference to the somewhat slower and less maintainable module-level imports:

// A module-level import
import std.datetime;
  
void fun(SysTime time)
{
  import std.stdio; // A local import
  ...
}

Similar lazy import idioms are possible in other languages, for instance Python.

The observant among you might notice that because SysTime is used as the type of a function parameter, std.datetime must be imported at module level. Which brings us to the point of this blog post (and DIP 1005). How can we get around that?

void fun(from!"std.datetime".SysTime time)
{
  import std.stdio;
  ...
}

There you have it, the Scherkl-Nielsen self-important lookup.

In order to fully understand what’s going on, you may need to learn some D-isms. Let’s break it down.

  1. When instantiating a template (via the ! operator), if the TemplateArgument is one token long, the parentheses can be omitted from the template parameters. So from!"std.datetime" is the same as from!("std.datetime"). It may seem trivial, but you’d be surprised how much readability is improved by avoiding ubiquitous punctuation noise.
  2. Eponymous templates. The declaration of a template looks like this:
    template y() {
        int x;
    }

    With that, you have to type y!().x in order to reach the int. Oh, ze horror! Is that a smiley? Give me x already! That’s exactly what eponymous templates accomplish:

    template x() {
        int x;
    }

    Now that the template and its only member have the same name, x!().x can be shortened to simply x.

  3. Renamed imports allow accessing an imported module via a user-specified namespace. Here, std.stdio is imported normally:
    void printSomething(string s) {
        import std.stdio;
        writeln(s);           // The normal way
        std.stdio.writeln(s)  // An alternative using the fully qualified 
                              // symbol name, for disambiguation
    }

    Now it’s imported and renamed as io:

    void printSomething(string s) {
        import io = std.stdio;
        io.writeln(s);         // Must be accessed like this.
        writeln(s);            // Error
        std.stdio.writeln(s);  // Error
    }

    Combining what we have so far:

    template dt() {
        import dt = std.datetime; 
    }
    void fun(dt!().SysTime time) {}

    It works perfectly fine. The only thing which remains is to make it generic.

  4. String concatenation is achieved with the ~ operator.
    string hey = "Hello," ~ " World!";
    assert(hey == "Hello, World!");
  5. String mixins put the power of a compiler writer at your fingertips. Let’s generate code at compile time, then compile it. This is typically used for domain-specific languages (see Pegged for one prominent use of a DSL in D), but in our simple case we only need to generate one single statement based on the name of the module we want to import. Putting it all together, we get the final form, allowing us to import any symbol from any module inline:
    template from(string moduleName)
    {
      mixin("import from = " ~ moduleName ~ ";");
    }

In the end, is it all really worth the effort? Using one comparison made by Jack Stouffer:

import std.datetime;
import std.traits;

void func(T)(SysTime a, T value) if (isIntegral!T)
{
    import std.stdio : writeln;
    writeln(a, value);
}

Versus:

void func(T)(from!"std.datetime".SysTime a, T value)
    if (from!"std.traits".isIntegral!T)
{
    import std.stdio : writeln;
    writeln(a, value);
}

In this particular case, the total compilation time dropped to ~30% of the original, while the binary size dropped to ~41% of the original.

What about the linker, I hear you cry? Sure, it can remove unused code. But it’s not always as easy as it sounds, in particular due to module constructors (think __attribute__((constructor))). In either case, it’s always more efficient to avoid generating unused code in the first place rather than removing it afterwards.

So this combination of D features was waiting there to be used, but somehow no one had stumbled on it before. I agreed with the need Andrei identified for Dependency-Carrying Declarations, yet I wanted even more. I wanted Dependency-Carrying Expressions. My primary motivation comes from being exposed to way too much legacy C89 code.

void foo(void)
{
#ifdef XXX /* needed to silence unused variable warnings */
  int x;
#endif
... lots of code ...
#ifdef XXX
  x = bar();
#endif
}

Variables or modules, in the end they’re all just symbols. For the same reason C99 allowed declaring variables in the middle of functions, one should be allowed to import modules where they are first used. D already allows importing anywhere in a scope, but not in declarations or expressions. It was with this mindset that I saw Dominikus Dittes Scherkl’s snippet:

fun.ST fun()
{
   import someModule.SomeType;
   alias ST = SomeType;
   ...
}

Clever, yet for one thing it doesn’t adhere to the DRY principle. Still, it was that tiny dot in fun.ST which caused the spark. There it was again, the Dependency-Carrying Expression of my dreams.

Criteria:

  • It must not require repeating fun, since that causes problems when refactoring
  • It must be lazy
  • It must be possible today with no compiler updates

Templates are the poster children of lazy constructs; they don’t generate any code until instantiated. So that seemed a good place to start.

Typically when using eponymous templates, you would have the template turn into a function, type, variable or alias. But why make the distinction? Once again, they’re all just symbols in the end. We could have used an alias to the desired module (see Scherkl’s snippet above); using the renamed imports feature is just a short-cut for import and alias. Maybe it was this simplified view of modules that made me see more clearly.

Now then, is this the only solution? No. As a challenge to the reader, try to figure out what this does and, more importantly, its flaw. Can you fix it?

static struct STD
{
  template opDispatch(string moduleName)
  {
    mixin("import opDispatch = std." ~ moduleName ~ ";");
  }
}

 

Project Highlight: DPaste

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DPaste is an online compiler and collaboration tool for the D Programming Language. Type in some D code, click run, and see the results. Code can also be saved so that it can be shared with others. Since it was first announced in the forums back in 2012, it has become a frequently used tool in facilitating online discussions in the D community. But Damian Ziemba, the creator and maintainer of DPaste, didn’t set out with that goal in mind.

Actually it was quite spontaneous and random. I was hanging out on the #D IRC channel at freenode. I was quite amazed at how active this channel was. People were dropping by asking questions, lots of code snippets were floating around. One of the members created an IRC bot that was able to compile code snippets, but it was for his own language that he created with D. Someone else followed and created the same kind of bot, but with the ability to compile code in D, though it didn’t last long as it was run on his own PC. So I wrote my own, purely in D, that was compiling D snippets. It took me maybe 4-5 hours to write both an IRC support lib and the logic itself. Then some server hardening where the bot was running and voila, we had nazbot @ #D, which was able to evaluate statements like ^stmt import std.stdio; writeln("hello world"); and would respond with, "hello world".

Nazbot became popular and people started floating new ideas. That ultimately led Damian to take a CMS he had already written in PHP and repurpose it to use as a frontend for what then became DPaste.

The frontend is written in PHP and uses MySQL for storage. It acts as a web interface (using a Bootstrap HTML template and jQuery) and API provider for 3rd Parties. The backend is responsible for actual compilation and execution. It’s possible to use multiple backends. The frontend is a kind of load-balancer when it comes to choosing a backend. The frontend and the backend may live on different machines.

DPaste is primarily used through the web interface, but it’s also used by dlang.org.

Once dpaste.dzfl.pl was well received, the idea popped up that maybe we could provide runnable examples on the main site. So it was implemented. The next idea, proposed by Andrei Alexandrescu, was to enable runnable examples on all of the Phobos documentation. I got swallowed by real life and couldn’t contribute at the time, but eventually Sebastian Wilzbach took it up and finished the implementation. So today we have interactive examples in the Phobos documentation.

When Damian first started work on DPaste in 2011, the D ecosystem looked a bit different than it does today.

There weren’t as many 3rd party libraries as we have now; there was no DUB, there was no vibe.d, etc. I wish I’d had vibe.d back then. I would have implemented the frontend in D instead of PHP.

What I enjoy the most about D is just how “nice” to the eye the language is (compared to C and C++, which I work with on a daily basis) and how easy it is to express what’s in your mind. I’ve never had to stop and think, “how the hell can I implement this”, which is quite common with C++ in my case. In the current state, what is also amazing is how D is becoming a “batteries-included” package. Whatever you need, you just dub fetch it.

He’s implemented DPaste such that it requires very little in terms of maintenance costs. It automatically updates itself to the latest compiler release and also knows how to restart itself if the backend hangs for some reason. He says the only real issue he’s had to deal with over the past five years is spam, which has forced him to reimplement the captcha mechanism several times.

As for the future? He has a few things in mind.

I plan to rewrite the backend from scratch, open source it and use a docker image so anybody can easily pick up development or host his own backend (which is almost done). Functionally, I want to maintain different compiler versions like DMD 2.061.0, DMD 2.062.1, DMD 2.063.0, LDC 0.xx, GDC x.xx.xx, etc., and connect more architectures as backends (currently x86, arm and aarch64 are planned).

I also want to rewrite the frontend in D using vibe.d, websockets, and angular.js. In general, I would like to make the created applications more interactive. So, for example, you could use the output from your code snippet in realtime as it is produced. I would like also to split a middle end off from the frontend. The middle end would provide communication with backends and offer both a REST API and websockets. Then the frontend would be responsible purely for user interaction and nothing else.

He would also like to see DPaste become more official, perhaps through making it a part of dlang.org. And for a point further down the road, Damian has an even grander plan.

I hope to make a full blown online IDE for dlang.org with workspaces, compilers to chose, and so on.

That would be cool to see!

Testing In The D Standard Library

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Jack Stouffer is a member of the Phobos team and contributor to dlang.org. You can check out more of his writing on his blog.


In the D standard library, colloquially named Phobos, we take a multi-pronged approach to testing and code review. Currently, there are five different services any addition has to go through:

  1. The whole complier chain of tests: DMD’s and DRuntime’s test suite, and Phobos’s unit tests
  2. A documentation builder
  3. Coverage analysis
  4. A style checker
  5. And a community project builder/test runner

Using these, we’re able to automatically catch the vast majority of common problems that we see popping up in PRs. And we make regressions much less likely using the full test suite and examining coverage reports.

Hopefully this will provide some insight into how a project like a standard library can use testing in order to increase stability. Also, it can spark some ideas on how to improve your own testing and review process.

Unit Tests

In D, unit tests are an integrated part of the language rather than a library
feature:

size_t sum(int[] a)
{
    size_t result;

    foreach (e; a)
    {
        result += e;
    }

    return result;
}

unittest
{
    assert(sum([1, 2, 3]) == 6);
    assert(sum([0, 50, 100]) == 150);
}

void main() {}

Save this as test.d and run dmd -unittest -run test.d. Before your main function is run, all of the unittest blocks will be executed. If any of the asserts fail, execution is terminated and an error is printed to stderr.

The effect of putting unit tests in the language has been enormous. One of the main ones we’ve seen is tests no longer have the “out of sight, out of mind” problem. Comprehensive tests in D projects are the rule and not the exception. Phobos dogfoods inline unittest blocks and uses them as its complete test suite. There are no other tests for Phobos than the inline tests, meaning for a reviewer to check their changes, they can just run dmd -main -unittest -run std/algorithm/searching.d (this is just for quick and dirty tests; full tests are done via make).

Every PR onto Phobos runs the inline unit tests, DMD’s tests, and the DRuntime tests on the following platforms:

  • Windows 32 and 64 bit
  • MacOS 32 and 64 bit
  • Linux 32 and 64 bit
  • FreeBSD 32 and 64 bit

This is done by Brad Roberts‘s auto-tester. As a quick aside, work is currently progressing to make bring D to iOS and Android.

Idiot Proof

In order to avoid pulling untested PRs, we have three mechanisms in place. First, only PRs which have at least one Github review by someone with pull rights can be merged.

Second, we don’t use the normal button for merging PRs. Instead, once a reviewer is satisfied with the code, we tell the auto-tester to merge the PR if and only if all tests have passed on all platforms.

Third, every single change to any of the official repositories has to go through the PR review process. This includes changes made by the BDFL Walter Bright and the Language Architect Andrei Alexandrescu. We have even turned off pushing directly to the master branch in Github to make sure that nothing gets around this.

Unit Tests and Examples

Unit tests in D solve the perennial problem of out of date docs by using the unit test code itself as the example code in the documentation. This way, documentation examples are part of the test suite rather than just some comment which will go out of date.

With this format, if the unit test goes out of date, then the test suite fails. When the tests are updated, the docs change automatically.

Here’s an example:

/**
 * Sums an array of `int`s.
 * 
 * Params:
 *      a = the array to sum
 * Returns:
 *      The sum of the array.
 */
size_t sum(int[] a)
{
    size_t result;

    foreach (e; a)
    {
        result += e;
    }

    return result;
}

///
unittest
{
    assert(sum([1, 2, 3]) == 6);
    assert(sum([0, 50, 100]) == 150);
}

// only tests with a doc string above them get included in the
// docs
unittest
{
    assert(sum([100, 100, 100]) == 300);
}

void main() {}

Run dmd -D test.d and it generates the following un-styled HTML:

Phobos uses this to great effect. The vast majority of examples in the Phobos documentation are from unittest blocks. For example, here is the documentation for std.algorithm.find and here is the unit test that generates that example.

This is not a catch all approach. Wholesale example programs, which are very useful when introducing a complex module or function, still have to be in comments.

Protecting Against Old Bugs

Despite our best efforts, bugs do find their way into released code. When they do, we require the person who’s patching the code to add in an extra unit test underneath the buggy function in order to protect against future regressions.

Docs

For Phobos, the documentation pages which were changed are generated on a test server for every PR. Developed by Vladimir Panteleev, the DAutoTest allows reviewers to compare the old page and the new page from one location.

For example, this PR changed the docs for two structs and their member functions. This page on DAutoTest shows a summary of the changed pages with links to view the final result.

Coverage

Perfectly measuring the effectiveness of a test suite is impossible, but we can get a good rough approximation with test coverage. For those unaware, coverage is a ratio which represents the number of lines of code that were executed during a test suite vs. lines that weren’t executed.

DMD has built-in coverage analysis to work in tandem with the built-in unit tests. Instead of dmd -unittest -run main.d, do dmd -unittest -cov -run main.d and a file will be generated showing a report of how many times each line of code was executed with a final coverage ratio at the end.

We generate this report for each PR. Also, we use codecov in order to get details on how well the new code is covered, as well as how coverage for the whole project has changed. If coverage for the patch is lower than 80%, then codecov marks the PR as failed.

At the time of writing, of the 77,601 lines of code (not counting docs or whitespace) in Phobos, 68,549 were covered during testing and 9,052 lines were not. This gives Phobos a test coverage of 88.3%, which is increasing all of the time. This is all achieved with the built in unittest blocks.

Project Tester

Because test coverage doesn’t necessarily “cover” all real world use cases and combinations of features, D uses a Jenkins server to download, build, and run the tests for a select number of popular D projects with the master branches of Phobos, DRuntime, and DMD. If any of the tests fail, the reviewers are notified.

Style And Anti-Pattern Checker

Having a code style set from on high stops a lot of pointless Internet flame wars (tabs vs spaces anyone?) dead in their tracks. D has had such a style guide for a couple of years now, but its enforcement in official code repos was spotty at best, and was mostly limited to brace style.

Now, we use CircleCI in order to run a series of bash scripts and the fantastically helpful dscanner which automatically checks for all sorts of things you shouldn’t be doing in your code. For example, CircleCI will give an error if it finds:

  • bad brace style
  • trailing whitespace
  • using whole module imports inside of functions
  • redundant parenthesis

And so on.

The automation of the style checker and coverage reports was done by Sebastian Wilzbach. dscanner was written by Brian Schott.

Closing Thoughts

We’re still working to improve somethings. Currently, Sebastian is writing a script to automatically check the documentation of every function for at least one example. Plus, the D Style Guide can be expanded to end arguments over the formatting of template constraints and other contested topics.

Practically speaking, other than getting the coverage of Phobos up to >= 95%, there’s not too much more to do. Phobos is one of the most throughly tested projects I’ve ever worked on, and it shows. Just recently, Phobos hit under 1000 open bugs, and that’s including enhancement requests.

The D Language Foundation Google Summer of Code 2016 Postmortem

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Craig Dillabaugh was first drawn to D by its attractive syntax and Walter Bright’s statement that D is “a programming language, not a religion”. He maintains bindings to the geospatial libraries shapelib and gdal, volunteered to manage the GSoC 2015 & 2016 efforts for D, and has taken it on again for 2017. He lives near Ottawa, Canada, and works for a network monitoring/security company called Solana Networks.


The 2016 Google Summer of Code (GSoC) proved to be a great success for the D Language Foundation. Not only did we have, for us, a record number of slots allotted (four) and all projects completed successfully, perhaps most important of all we attracted four excellent students who will hopefully be long time contributors to the D Language and its community. This report serves as a review for the community of our GSoC efforts this past summer, and tries to identify some ways we can make 2017 an equal, or better, success.

Background

Back in 2011 and 2012, Digital Mars applied to participate in, and was accepted to, Google Summer of Code. In each of those years we were awarded three slots and had successful projects. Additionally, a number of long time D contributors, including David Nadlinger, Alex Bothe, and Dmitry Olshansky, were involved as students. Sadly, in the succeeding two years we were not awarded any slots. After 2014’s unsuccessful bid, Andrei asked on the forums if anyone wanted to take the lead for the 2015 GSoC, as he had too many things on his plate. This is when I decided to volunteer for the job.

I prepared for the 2015 GSoC and worked on getting some solid items for our Ideas page. I even prepared what I thought was a beautifully typeset document in LaTeX for our final submission. Needless to say, I was very disappointed when I had to copy/paste each section into the simple web form that Google provided for submissions. Sadly, that year we were rejected once more, though I felt our list of ideas was solid.

We applied again in 2016 for the first time as The D Language Foundation. Again, the community contributed lots of solid suggestions for the Ideas page and we were accepted for the first time in four years. I think that perhaps getting accepted involves a bit of luck, as our ideas were similar to, or repeated from, those that were not accepted in 2015. However, more effort was put into polishing up the page, so perhaps that helped.

The Selection Process

Once we were accepted as a mentoring organization, the process of receiving student proposals began. We received interest from a large number of students from all over the world (about 35). In the end, a total of 23 proposals were officially submitted, ranging from very short–obviously last minute–pieces, to several excellent efforts, including Sebastian Wilzbach’s 20-page document.

Our selection process was, I felt, very rigorous. We had seven of our potential admins/mentors screen the initial proposals. This involved reading all 23 proposals, which was a significant amount of work. From this initial screening we identified eight students/proposals that we thought could become successful projects. We then had all mentors individually rank each of the shortlisted proposals, another significant time commitment on their part.

Finally, interviews were arranged with all eight students. In most cases, two mentors interviewed each student, and the interviews were fairly intense, job-style interviews that involved coding exercises. A number of our mentors were involved in this process, but I think Amaury Sechet interviewed all of the students. It is no small feat to arrange and then conduct interviews with students in so many different time zones, so a huge thanks to all the mentors, but Amaury in particular. Those involved in the screening/interview process included Andrei Alexandrescu, Ilya Yaroshenko, Adam Ruppe, Adam Wilson, Dragos Carp, Russel Winder, Robert Schadek, Amaury, and myself.

Awarding of Slots

The next step for our organization was to decide how many slots we would request from Google. I really had no idea what to expect, but I was hoping we might get two slots awarded to us, as there were many good organizations vying for a limited number of slots. We felt that most of the short-listed projects could have been successful, but decided to not be too greedy and requested just four slots. As it turned out, perhaps we should have asked for more; we were awarded all four. We then selected our top four ranked students from the interview process. They were, in no particular order:

  • Sebastian Wilzbach: Science for D – a non-uniform RNG (Ilya Yaroshenko mentor)
  • Lodovico Giaretta: Phobos: std.xml (Robert Schadek mentor)
  • Wojciech Szeszol: Improvements to DStep (Russel Winder mentor)
  • Jeremy DeHaan: Precise Garbage Collector (Adam Wilson mentor)

Summer of Code

Once the projects were awarded, I must say that most of my work was done. From there on the mentors and students got down to work. I tried to keep tabs on progress and asked for regular updates from both the mentors and the students. These were, in most cases, promptly provided.

While there were some challenges, and a few projects had to be modified slightly in some instances, everyone progressed steadily throughout the summer, so there were no emergencies to deal with. All of our students passed their mid-term evaluations and by the end of the summer all four projects were completed (although Jeremy has some on-going work on his precise GC). As a result, everyone got paid and, I presume, everyone was happy.

In addition to our original mentors, thanks are due to Jacob Carlborg (DStep) and Joseph Rushton Wakeling (RNG) for providing additional expertise.

Mentor Summit

Google offered money for students to attend academic conferences and present results based on their GSoC work. Google also offered to pay travel costs for two mentors to travel to the mentor summit in California. Regrettably, none of our students had the time to take advantage of the conference money, but Robert Schadek was able to attend the Mentor Summit from Oct 28th to 30th in Sunnyvale, California. There he was able mingle with, and learn from, mentors from the other organizations that participated.

Looking Forward

It is hard to believe, but the process starts all over again in a few short months. The success of this past year will create expectations for 2017, and I hope that we can replicate that success. A number of lessons were learned from this past year that we can carry forward into the next round. So in this section, I will try to distill some of what we learned to help guide our efforts in the coming year.

The Ideas Page and Advertising

Most of the work of identifying projects was carried out through the D Forums, with the odd email to past mentors. This was generally successful, but a number of proposals from previous years ended up being recycled. While it may be inevitable, it seemed that many of the proposal ideas were added at the last minute. Since a number of our best ideas from the 2016 page are now completed projects, we will need to replenish the Ideas page for 2017.
Recommendations

  1. We should post a PDF version of one of the successful proposals on our Ideas page to give students an example of what we expect. Although it was excellent, we likely shouldn’t use Sebastian Wilzbach’s treatise, as that may scare some people off.
  2. Try to get a decent set of solid proposals with committed mentors earlier in the process. In 2016 a number of the mentors were signed up at the last minute. The earlier the proposals are posted the more time we have to polish them and make them look more attractive.

Interview and Selection Process

The selection process went well, but was a lot of work. Having input from a number of different mentors/individuals was invaluable.
Recommendations

  1. Streamline the selection process, but reuse much of what was done last year. Having a rigorous selection process was a key contributor to 2016’s success.
  2. Start the interview portion of the selection process earlier so that we have more time to set up and carry out the interviews.

Project Progress and Mentoring

Much of the success of an individual project involves having a good relationship and work plan between the student and mentor. From this perspective, the organization isn’t heavily involved. Since all of our students worked well with their mentors, even less organizational administration was required. This is a byproduct of good screening and a solid set of ideas, and being fortunate enough to get good students.

However, there are areas where we could have run things a bit better. Students and mentors were asked to regularly provide updates on their progress, and they generally did this well, but there was no formal reporting process. Also, it would be worthwhile to have a centralized collection of project timelines/milestones where administrators and others involved in the projects (we had a few individuals working in advisory roles) can keep an eye on project progress.

Recommendations

  1. We should keep a centralized version of project timelines somewhere (ie. Google Docs Spreadsheet) where we can check on project milestones. This should be shared with all individuals involved in a project (student/mentors/advisors/admins).
  2. Have a more formalized process for students and mentors reporting on their progress. This would involve weekly student updates and biweekly mentor updates.

Summary

The 2016 GSoC was a great success, and with any luck will be a good foundation for our successful participation in the year to come. We were fortunate that everything seemed to fall nicely into place, from our being awarded all four projects, to having all of our students complete their projects. Perhaps Sebastian, Lodovico, Wojciech or Jeremy will be involved again as students (or even mentors), and in any case continue to contribute to the D Language.

The D Blog in 2016: Seven Months of Page Views

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The D Blog was born at DConf 2016 and the first post was published on June 3rd. There were 27 more posts between then and the end of the year, most of which were shared on the usual social media sites. In case some of you in DLand are curious about such things, a year-end stats post is a fun way to kick off the new year.

First, we welcomed 39,471 visitors who viewed a total of 53,013 pages. The top five referrers in terms of page views:

  1. 16,604 — Reddit
  2.  3,698 — The D Forums
  3.  3,123 — Hacker News
  4.  2,847 — Twitter
  5.  1,759 — Facebook

The top five countries in terms of page views:

  1. 17,244 — United States
  2.  4,427 — Germany
  3.  3,349 — United Kingdom
  4.  2,251 — Canada
  5.  1,598 — France

Several posts included links to D projects at GitHub. Counting both projects and profiles, the top five most-clicked were:

  1. dlangui
  2. atrium
  3. Timur Gafurov
  4. voxelman
  5. dlib

The single most-clicked page was the DLangUI screenshot page.

Finally, the top six posts in terms of page views:

  1. 5,865 — Find Was Too Damn Slow, So We Fixed It
  2. 5,602 — Ruminations on D: An Interview with Walter Bright
  3. 4,267 — Project Highlight: DLangUI
  4. 2,704 — Programming in D: A Happy Accident
  5. 2,579 — Project Highlight: Timur Gafarov
  6. 2,257 — Project Highlight: Voxelman

The list of posts was intended to be a top-five, but it was interesting that Voxelman was posted only on December 30th and managed to become the sixth most-viewed post on the site.

2016 was the time for the blog to find its sea legs. The coming year will see more Project Highlights and more guest posters (including Andrei and Walter). We’re also looking to expand the scope somewhat, so keep your eyes open for new types of content.

If you would like to write for the D blog, please go and contact the fellow who owns this GitHub profile, where he’s showing his email address for the world to see. He would be happy to discuss posts about your D projects, idioms you like to use, tutorials you’d like to share, or anything related to the D Programming Language.

Thanks for tuning in, and Happy 2017!