There is one kind of leak that neither RAII nor garbage collection can fix, it’s abstraction leaks. The idea was coined by Joel Spolsky back in 2002 and remains one of my favourite computer science article.

The law of leaky abstractions by Joel Spolsky is one of the first technical article I encountered after I got my engineering degree and it remains one of the most influential to me.

It’s been published almost 15 ago years and it’s well past due time I shared it with you in case you missed it.

## What’s a abstraction?

Abstraction is one of the most fundamental concept in computer science. As the saying goes: “Any problem in computer science can be solved by adding another layer of indirection”.

The idea is quite simple: you decompose your problem in layers in which each layer handles a separate concern. Every layer as a clear goal and focus, which can be reasoned about independently of the rest. This reduces coupling, enables testing and of course allows for better portability.

For example, when you write C++, your machine cannot understand it. So you use a compiler to translate that code to assembly. But assembly itself is just a text representation of machine binary code, so an assembler is needed to translate that. Now say you are using a x86 machine like the laptop I’m using to write this article, your CPU doesn’t even operate with the x86 CISC instruction set at its core. Instead, it translates those instructions into simpler ones and dispatch them to RISC pipelines. Then, those are again just an abstraction of basic logical OR, AND, XOR and NOT operations. Which in turn are abstractions build upon transistors that combine two electrical inputs into one.

You can find similar constructs in any part of computer science, such as networking, filesystems, graphics, you name it.

## Leaky abstractions

In his article, Joel Spolsky postulates that all abstractions are, to some degree, leaky.

What it means is that perfect abstractions do not exist and some quirks do show up from time to time: one layer leaks into another. Let’s take a simple example:

std::ifstream ifs("/some/file.txt");
std::string text(std::istream_iterator(ifs), std::istream_iterator());


This simple code reads the content of text file /some/file.txt into a std::string called text. It uses the STL’s abstraction of file streams which in turn relies on the operating system file i/o abstraction.

In a perfect world, the owner of this code wouldn’t have to think about what std::ifstream does. It would behave the same way whatever the circumstance. But a filesystem is an abstraction of various storage devices and so reading from a file could mean fetching blocks from a physical hard drive, a RAID disk, a network drive, a memory image or even a floppy disk1. And depending on that, the access time will differ by possibly an order of magnitude.

Let’s say you have to read and crunch some data from many files. If your CPU has multiple cores, it might make sense to have a several threads processing different files at once. If a filesystem abstraction was perfect, you could simply write an algorithm that does just that. But in practice, depending on the storage of each file, it might be better to have only one reader thread (at the risk of starving your calculation threads) or to have each thread read and compute their files (at the risk of I/O contention).

Another easy example:

int sumXY(int* array, int X, int Y) {
int sum = 0;
for (int x = 0; x < X; ++x)
for (int y = 0; y < Y; ++y)
sum += array[y * X + x];
return sum;
}

int sumYX(int* array, int X, int Y) {
int sum = 0;
for (int y = 0; y < Y; ++y)
for (int x = 0; x < X; ++x)
sum += array[y * X + x];
return sum;
}


If you ask a mathematician, he will answer that those two functions are exactly the same. Indeed, summing by column or by row doesn’t change anything in mathematical terms.

But what does the reality says? sumYX is much faster that sumXY. Why is that? Because a C++ program is an imperfect abstraction of how a real machine work, and does not account for locality of reference which make array traversal by row much faster than by column.

## Corollary

Since all non-trivial abstractions are imperfect and will leak in one way or another, this means any serious programmer should always have at least a minimal knowledge of the abstractions he uses. This usually means knowing a bit about how your CPU works, how your network protocols work, how your kernel works and so on and so forth.

I’ve seen talks about Javascript that stop midway to explain how x86 protected mode work, I’ve worked with financial application engineers that patched wifi routers firmwares on weekends and I’m pretty convinced this is the way to go.

So don’t be shy. On the contrary, be curious. Tear down the thing you’re using the most and see how it works behinds the scene. It’ll help you one day or another, trust me.

1 For my youngest readers, a floppy disk is a giant 3D print of a save button.

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