What Makes Code Readable: Not What You Think

This is a nice post considering the interaction between language complexity, readability, and learnability.  It could have been made stronger by including some of the empirical data.  Thomas Green in his empirical research on language features didn’t just find that explicit BEGIN IF…END IF blocks were easier to read by novices, he found that they were TEN TIMES easier for novices to read.  Being less succinct is not just easier for novices, it may be so much easier that it’s the difference between success and giving up.

My point is, the larger the vocabulary you have, the more succinctly ideas can be expressed, thus making them more readable, BUT only to those who have a mastery of that vocabulary and grammar.

If we made the English language smaller, and reduced the complex rules of grammar to a more much simple structure, we’d make it much easier to learn, but we’d make it harder to convey information.

via What Makes Code Readable: Not What You Think | Making the Complex Simple.

Computer Science as a great target for Science Careers

Nice interview with Ed Lazowska of U-W in Science about the state of computer science education and research.  The below section is getting picked up elsewhere as an argument for CS as a great choice for students interested in a career in science.

I would have to say “about right.” Ph.D. production in computer science is far lower than in fields with far fewer employment opportunities. And Ph.D.s in computer science have a broad range of employment opportunities that take full advantage of their training. In most other STEM [science, technology, engineering, and mathematics] fields, the vast majority of graduates at all levels take jobs unrelated to their field of study. In computer science, the opposite is true: The vast majority of graduates at all levels take jobs that are in their “sweet spot.” Google hires roughly the same number of graduate students as undergraduate students from the University of Washington. Microsoft also hires a large number of our best Ph.D. students, both for Microsoft Research [MSR] and for the development organization.

I do think we need to be cautious. We need to avoid the overproduction—and, honestly, exploitation—that characterizes other fields. Hopefully we’ll be smart enough to learn from their behavior.

via “We Are the World” | Science Careers.