Why const Doesn't Make C Code Faster

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In a post a few months back I said it’s a popular myth that const is helpful for enabling compiler optimisations in C and C++. I figured I should explain that one, especially because I used to believe it was obviously true, myself. I’ll start off with some theory and artificial examples, then I’ll do some experiments and benchmarks on a real codebase: Sqlite.

Data Still Dominates

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Here’s a quote from Linus Torvalds in 2006:

I’m a huge proponent of designing your code around the data, rather than the other way around, and I think it’s one of the reasons git has been fairly successful… I will, in fact, claim that the difference between a bad programmer and a good one is whether he considers his code or his data structures more important. Bad programmers worry about the code. Good programmers worry about data structures and their relationships.

Which sounds a lot like Eric Raymond’s “Rule of Representation” from 2003:

Fold knowledge into data, so program logic can be stupid and robust.

Which was just his summary of ideas like this one from Rob Pike in 1989:

Data dominates. If you’ve chosen the right data structures and organized things well, the algorithms will almost always be self-evident. Data structures, not algorithms, are central to programming.

Which cites Fred Brooks from 1975:

Representation is the Essence of Programming

Beyond craftmanship lies invention, and it is here that lean, spare, fast programs are born. Almost always these are the result of strategic breakthrough rather than tactical cleverness. Sometimes the strategic breakthrough will be a new algorithm, such as the Cooley-Tukey Fast Fourier Transform or the substitution of an n log n sort for an n2 set of comparisons.

Much more often, strategic breakthrough will come from redoing the representation of the data or tables. This is where the heart of your program lies. Show me your flowcharts and conceal your tables, and I shall be continued to be mystified. Show me your tables, and I won’t usually need your flowcharts; they’ll be obvious.

So, smart people have been saying this again and again for nearly half a century: focus on the data first. But sometimes it feels like the most famous piece of smart programming advice that everyone forgets.

Let me give some real examples.

Analysing D Code with KLEE

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KLEE is symbolic execution engine that can rigorously verify or find bugs in software. It’s designed for C and C++, but it’s just an interpreter for LLVM bitcode combined with theorem prover backends, so it can work with bitcode generated by ldc2. One catch is that it needs a compatible bitcode port of the D runtime to run normal D code. I’m still interested in getting KLEE to work with normal D code, but for now I’ve done some experiments with -betterC D.

Profiling D's Garbage Collection with Bpftrace

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Recently I’ve been playing around with using bpftrace to trace and profile D’s garbage collector. Here are some examples of the cool stuff that’s possible.

D as a C Replacement

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Sircmpwn (the main developer behind the Sway Wayland compositor) recently wrote a blog post about how he thinks Rust is not a good C replacement. I don’t know if he’d like the D programming language either, but it’s become a C replacement for me.

Hello World Marketing (or, How I Find Good, Boring Software)

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Back in 2001 Joel Spolsky wrote his classic essay “Good Software Takes Ten Years. Get Used To it”. Nothing much has changed since then: software is still taking around a decade of development to get good, and the industry is still getting used to that fact. Unfortunately, the industry has investors who want to see hockey stick growth rates on software that’s a year old or less. The result is an antipattern I like to call “Hello World Marketing”. Once you start to notice it, you see it everywhere, and it’s a huge red flag when choosing software tools.

Some Presentation Slides

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Here are the slide decks to a couple of talks I’ve given recently.

Being Self-Employed in Australia (at JAIT)

Because this talk is based on my own experiences, it’s particularly relevant to service businesses in Australia. But if you’re interested in being your own boss, anywhere or anyhow, you could find it useful. As I said in the talk, there’s a lot of stuff that feels obvious to me now, but I ended up learning the hard way.

Introduction to Infrastructure as Code (at RORO Sydney)

Here’s a common story: Devs write an app, and do all the right things like using source control and writing automated test suites. Then it comes to deploy the code, and they have to figure out all these things like DNS and server infrastructure. They hack something together using web UIs, but six months later no one can remember the deployment process any more.

This presentation was a really quick introduction to the tools you can use to get more app dependencies into source control.

Why Sorting is O(N log N)

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Any decent algorithms textbook will explain how fast sorting algorithms like quicksort and heapsort are, but it doesn’t take crazy maths to prove that they’re as asymptotically fast as you can possibly get.

D in the Browser with Emscripten, LDC and bindbc-sdl (translation)

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Here’s a tutorial about using Emscripten to run D code in a normal web browser. It’s uses a different approach from the Dscripten game demo and the dscripten-tools toolchain that’s based on it.

LDC has recently gained support for compiling directly to WebAssembly, but (unlike the Emscripten approach) that doesn’t automatically get you libraries.

You can find the complete working code on Github. ./run.sh starts a shell in a Docker image that contains the development environment. dub build --build=release generates the HTML and JavaScript assets and puts them into the dist/ directory.

This tutorial is translated from a Japanese post by outlandkarasu, who deserves all the credit for figuring this stuff out.

Unfortunately, Garbage Collection isn't Enough

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Here’s a little story of some mysterious server failures I had to debug a year ago. The servers would run okay for a while, then eventually start crashing. After that, trying to run practically anything on the machines failed with “No space left on device” errors, but the filesystem only reported a few gigabytes of files on the ~20GB disks.