SIGPLAN-M is SIGPLAN’s international long-term mentoring program. Initiated in late 2020 by Talia Ringer, it now has over 200 mentors and over 300 mentees. Everybody in the community — from aspiring undergraduate to experienced faculty — is welcome to take part either as a mentor or as a mentee (or both). For this edition of People of PL, John Wickerson met three of SIGPLAN-M’s mentors to find out about their experiences.
Should the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI) publish its proceedings in the Proceedings of the ACM on Programming Languages (PACM-PL) journal? Please fill out this short survey to help us decide.
Real programming languages are living things, changing and evolving. As with any production code, most of their designer’s time is spent on bug fixing and small improvements, rather than on the radical new features. One of the unique things about Kotlin is that it has been evolving in the use-case and community-driven fashion for years, starting way before it went to the stable 1.0 release in 2016, even for some time before it went public in 2011. Language design in the real world is a maintenance of a complex system and it runs into novel research questions with respect to type systems, feature interactions, usability, real-life code patterns in big code, etc.
To create a single polynomial approximation that produces correct results for multiple representations and rounding modes, we propose to generate a polynomial that generates the correctly rounded result of f(x) using the non-standard round-to-odd rounding mode with 2 additional precision bits compared to the largest floating point representation that we wish to support. We provide a proof that this method produces correctly rounded results for multiple representations and for all the standard rounding modes. More detailed explanation of our approach can be found in our POPL 2022 distinguished paper.
We all need to step up and start working to improve gender equality in computer science and engineering. This is the second of two blog posts about this fascinating and frustrating problem, in which I provide three suggestions for how to get started.
We all need to step up and start working to improve gender equality in computer science and engineering. In two blog posts, I give my view of this fascinating and frustrating problem. I provide three suggestions for how to get started.
You have heard your grandmother tell you many times: parallel programming is hard. In 2022, does it still have to be? Back in grandma’s heyday, they knew a cool and breezy way to do parallelism: pure functional programming. They knew that pure functions are parallel by default, being free of pesky concurrency bugs and all. But, parallel functional programming remained slow and steady, resisting practical efficiency for decades. This post shows the way towards solving the performance problems of functional programming.
Modern analog computers a host of analog behaviors that affect the fidelity of the mapped computation. How can we mitigate these analog behaviors in compilation?
Peer review is an essential aspect of academic research, giving a feedback loop that stimulates and rewards high-quality work – but as we all know, it doesn’t always function well. To help maintain a consensus of what constitutes good reviewing, this note spells out some bad and good reasons to reject and accept papers.
