I wanted to write a manifesto-ish sort of piece about what compilers are supposed to look like in the future. Nuno was the obvious coauthor since I’ve talked to him about this topic so much that I’m overall not really sure which parts started out as his ideas and which were mine. The article didn’t […]
Category Archives: Computer Science
How LLVM Optimizes a Function
An optimizing, ahead-of-time compiler is usually structured as: A frontend that converts source code into an intermediate representation (IR). A target-independent optimization pipeline: a sequence of passes that successively rewrite the IR to eliminate inefficiencies and forms that cannot be readily translated into machine code. Sometimes called the “middle end.” A target-dependent backend that generates […]
How Clang Compiles a Function
I’ve been planning on writing a post about how LLVM optimizes a function, but it seems necessary to first write about how Clang translates C or C++ into LLVM. This is going to be fairly high-level: rather than looking at Clang’s internals, I’m going to focus on how Clang’s output relates to its input we’re […]
Software Engineering Takeaways
I had a great time this spring teaching a software engineering course for a new professional masters degree program created by my department. Since I didn’t use slides or hand out lecture notes, some students were asking if maybe I could write up a summary of what I wanted them to learn in the course. […]
Paths to External Engagement in Computer Science Research
The other day I wrote a post imploring academic computer scientists to at least occasionally break out of their research bubbles and engage with real engineering problems where their research matters. That post was, admittedly, a bit facile about how one might make this engagement happen. This piece suggests some ways. I don’t claim any […]
Closing the Loop: The Importance of External Engagement in Computer Science Research
Computer scientists tend to work by separating the essence of a problem from its environment, solving it in an abstract form, and then figuring out how to make the abstract solution work in the real world. For example, there is an enormous body of work on solving searching and sorting problems and in general it […]
The Basic Toolbox
This post is aimed at computer science students. In the software engineering course I’m teaching this spring, I often find myself saying things like “you need to know a scripting language” or “everyone should be able to run a code coverage tool.” Finally, the other day, a student stopped me and asked for the whole […]
Trust Boundaries in Software Systems
One of the big things that has changed in computer science education over the last 20 years is that it is now mandatory to prepare students for writing software that lives in a hostile environment. This content can’t be limited to a computer security course, it has to be spread throughout the curriculum. My experience, […]
Stories Behind Papers: Integer Overflow
A couple months ago Jean Yang and Vijay Chidambaram had a Twitter discussion about the stories behind research efforts that you might hear over coffee, but that usually don’t get written up. Vijay started a series of posts containing these. I thought I’d write up a couple of them myself. Alas, none will be particularly […]
A Conversation about Teaching Software Engineering
For better or worse, my impressions of software engineering as a field were shaped by a course I took as an undergrad that I thought was mostly not very interesting or useful. We spent a lot of time on waterfalls and stuff, while not covering testing in any detail. For the final project in the […]