Through me you pass into the city of woe:
Through me you pass into eternal pain:
Through me among the people lost for aye.

— Dante Alighieri

I recently listened to a talk about somebody’s experience as a computer science researcher. The argument was that research is ultra-competitive, because you fight against people that are smarter than you and work harder than you (think nights and weekends) for very few available positions. Therefore, you have to consider yourself as a professional athlete, i.e. choosing a lifestyle that serves your only purpose in life: succeeding. Also, professional athletes throw up when they train really hard but then they train even harder. So much for elegance.

Needless to say, this vision of life is disgusting from every point of view. Ok, in academic research the hours are long and the pay is low, but what about the joys one could find in science? There was nothing about the beauty of a proof, the elegance of a piece of code or the fun of technology. Apparently there is nothing more to life than getting a better position, and to me this is about as un-inspirational as it gets.

These techniques seem to work, since I stumble quite frequently upon them in papers accepted at important venues:

• misleading claim — come up with your own definition of a widely accepted term, preferably in a way inconsistent with the intuition and the general understanding of the term. Then claim spectacular results that happen to be true only with respect to your definition.
• marketing pitch — use data irrelevant to the scientific discussion. Bonus: cite a dubious, hard-to-verify source with a non-existent methodology. Ex: “Problem X costs more than Y gazillion $$$ per year (hence our work is of epic importance)”.
• over-sophistication —  use overly sophisticated terms for techniques or ideas that would otherwise be simple to understand (especially if it makes them look better). Ex: “heuristics” [1] sounds a lot better than “hack”.
• no limitations — there are no limitations to your work, only things that are either out-of-scope or left for future work.
• outsourcing problems — outsource large portions of the hard problems in your area by “leveraging” (see over-sophistication) existing work from a different domain with a complex literature, just to make sure that nobody can grasp all the dependencies of your paper.
• biased evaluation — perform experimental evaluation designed to make others look bad. Even better if the evaluation is not reproducible, because you fail to disclose your source code, detailed algorithm or input set.

[1] heuristics (noun — hyu’-ris-tik): algorithm that does not work.

When you look at software engineering as a research field, you can see some pretty serious progress there. There are amazing projects like PyPy and LLVM, massive optimizations in gcc and JIT compilers (HotSpot, Psyco, TraceMonkey). Compared to that, I have the impression that the reverse engineering community did not produce any significant results. What we have is disassemblers, that is to say parsers.

To make things even worse, the more advanced tools used in RE have been created for a totally different purpose (think Pin, VEX, QEMU, Bochs, virtualization…). Some nice works are being performed by folks like Sean Heelan, Silvio Cesare, the Sogeti R&D team (metasm, fuzzgrind) and the BitBlaze team (TEMU, Vine). But overall I can see no open, community-driven, formally sound approach. The tools are either not FOSS, limited in scope, or just not-that-reusable.

There is a number of potential factors to explain the situation:

• reversers are not developers (this, I think, is a big factor)
• reversers are solitary, basement programmers (not to mention cheese pops and japanese tentacle porn)
• the complexity of x86 + Windows makes the entry cost too high for academics

We are therefore left with a research niche with virtually no academics, little to no developer community, that still pumps some big bucks. The only player left is the security industry, i.e. corporations which have absolutely no incentive to solve the problem.

Did I miss something, or is the picture really that grim?