Lambda the Ultimate

cf. this coverity thread, i'm wondering what your favourite thing / biggest hope is for PLT applied to programming-in-the-large. what are some quantitative things (random e.g. more better typing maybe e.g. dependent or effect)? what are some qualitative things (random e.g. formal methods)? perhaps in other words, what interview questions would you use to suss if somebody knew good p-i-t-l? i'd be curious to know what you think the limits of PLT are here; what about large systems is a non language issue (e.g. managing a large team of people)?

From the title Can a Biologist Fix a Radio? — or, What I Learned while Studying Apoptosis(Y. Lazebnik 2004) would seem pretty off topic for LtU. It starts with a humorous take on how biologist might try to understand the workings of a radio, but it ends in a plea for (computer aided) formal languages and quantitative modeling of biological systems.

The question is how to facilitate this change, which is not exactly welcomed by many experimental biologists, to put it mildly. Learning computer programming was greatly facilitated by BASIC, a language that was not very useful to solve complex problems, but was very efficient in making one comfortable with using a computer language and demonstrating its analytical power. Similarly, a simple language that experimental scientists can use to introduce themselves to formal descriptions of biological processes would be very helpful in overcoming a fear of long forgotten mathematical symbols. Several such languages have been suggested but they are not quantitative, which limits their value. Others are designed with modeling in mind but are too new to judge as to whether they are user friendly. However, I hope that it is only a question of time before a user friendly and flexible formal language will be taught to biology students, as it is taught to engineers, as a basic requirement for their future studies. My advice to experimental biologists is to be prepared.

Further, at a meta-level, the issues he raises seem to directly mirror the challenges software developers and researchers face in trying to understand and design complex computing systems. If nothing else it's good to know we're not alone.

And it doesn't hurt at all that it's a fun read.