Beautiful Code | The Observation Deck

So my copy of Beautiful Code showed up last week. Although I am one of the (many) authors and I have thus had access to the entire book online for some time, I do all of my pleasure reading in venues that need the printed page (e.g. the J Church) and have therefore waited for the printed copy to start reading.

Although I have only read the first twelve chapters or so, it’s already clear (and perhaps not at all surprising) that there are starkly different definitions of beauty here: the book’s greatest strength – and, frankly, its greatest weakness – is that the chapters are so incredibly varied. For one chapter, beauty is a small and titilating act of recursion; for the next, it’s that a massive and complicated integrated system could be delivered quickly and cheaply. (I might add that the definition of beauty in my own chapter draws something from both of these poles: that in software, the smallest and most devilish details can affect the system at the largest and most basic levels.)

If one can deal with the fact that the chapters are widely divergent, and that there is not even a token attempt to weave them together into a larger tapestry, this book (at least so far, anyway) is (if nothing else) exceptionally thought provoking; if Oprah were a code cranking propeller head, this would be the ideal choice for her book club.

Now in terms of some of my specific thoughts that have been provoked: as I mentioned, quite a few of my coauthors are enamored with the elegance of recursion. While I confess that I like writing a neatly recursive routine, I also find that I frequently end up having to unroll the recursion when I discover that I must deal with data structures that are bigger than I anticipated – and that my beautiful code is resulting (or can result) in a stack overflow. (Indeed, I spent several unpleasant days last week doing exactly this when I discovered that pathologically bad input could cause blown stacks in some software that I’m working on.)

To take a concrete example, Brian Kernighan has a great chapter in Beautiful Code about some tight, crisp code written by Rob Pike to perform basic globbing. And the code is indeed beautiful. But it’s also (at least in a way) busted: it overflows the stack on some categories of bad input. Admittedly, one is talking about very bad input here – strings that consist of hundreds of thousands of stars in this case – but this highlights exactly the problem I have with recursion: it leaves you with edge conditions that on the one hand really are edge conditions (deeply pathological input), but with a failure mode (a stack overflow) that’s just too nasty to ignore.

Now, there are ways to deal with this. If one can stomach it, the simplest way to deal with this is to setup a sigaltstack and then siglongjmp out of a SIGSEGV/SIGBUS signal handler. You have to be very careful about doing this: the signal handler should look at the si_addr field in the siginfo and comparing it to the stack bounds to confirm that it’s a stack overflow, lest it end up siglongjmp‘ing out of a non-recursion induced SIGSEGV (which, needless to say, would make a bad problem much worse). While an alternative signal stack solution may sound hideous to some, at least the recursion doesn’t have to go under the knife in this approach. If having a SIGSEGV handler to catch this condition feels uncomfortably brittle (as well it might), or if one’s state cannot be neatly unwound after an arbitrary siglongjmp (as well it might not), the code will have to change: either a depth counter will have to be passed down and failure propagated when depth exceeds a reasonable maximum, or the recursion will have to be unrolled into iteration. For most aesthetic senses, none of these options is going to make the code more beautiful – but they will make it indisputably more correct.

I was actually curious about where exactly the Pike/Kernighan code would blow up, so I threw together a little program that uses sigaltstack along with sigsetjmp/siglongjmp to binary search to find the shortest input that induces the failure. My program, which (naturally) includes the Pike/Kernighan code, is here.

Here are the results of running my program on a variety of Solaris platforms, with each number denoting the maximum string length that can be processed by the Pike/Kernighan code without the possibility of stack overflow.

	x86		SPARC
	32-bit	64-bit	32-bit	64-bit
Sun cc, unoptimized	403265	187225	77649	38821
gcc, unoptimized	327651	218429	69883	40315
Sun cc, optimized	327651	327645	174723	95303
gcc, optimized	582489	524227	149769	87367

As can be seen, there is a tremendous range here, even across just two different ISAs, two different data models and two different compilers: from 38,821 on 64-bit SPARC using Sun cc without optimization to 582,489 on 32-bit x86 using gcc with optimization – an order of magnitude difference. So while recursion is a beautiful technique, it is one that ends up with the ugliest of implicit dependencies: on the CPU architecture, on the data model and on the compiler. And while recursion is still beautiful to me personally, it will always be a beauty that is more superficial than profound…