Programming: Rust, Top Languages and Studying Developers
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[Rust] Diagnosing A Weak Memory Ordering Bug
For the first time in my life I tracked a real bug's root cause to incorrect usage of weak memory orderings. Until now weak memory bugs were something I knew about but had subconciously felt were only relevant to wizards coding on big iron, partly because until recently I've spent most of my career using desktop x86 machines.
Under heavy load a Pernosco service would assert in Rust's std::thread::Thread::unpark() with the error "inconsistent state in unpark". Inspecting the code led to the disturbing conclusion that the only way to trigger this assertion was memory corruption; the value of self.inner.state should always be between 0 and 2 inclusive, and if so then we shouldn't be able to reach the panic. The problem was nondeterministic but I was able to extract a test workload that reproduced the bug every few minutes. I tried recording it in rr chaos mode but was unable to reproduce it there (which is not surprising in hindsight since rr imposes sequential consistency).
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IEEE Survey Ranks Programming Languages
It's been said that programming languages are akin to religion. Engineers and developers will go out of their way to defend the use of their favorite language. (Perhaps it's more the pain of learning a new language that keeps us using the old). Surely you've seen many surveys on programming language preferences. As with all surveys, the results depend on who was asked.
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Programming Languages May Finally Be Reaching a Status Quo
The analyst firm RedMonk has tracked programmers' interest in various programming languages since 2011. During that time, Swift and Kotlin grew faster than any other language the firm tracked, including Google's Go and Mozilla's Rust. Earlier this year Swift, which Apple released in 2014, managed to tie with Apple's much more established Objective-C language for tenth place in RedMonk's rankings.
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Machine learning algorithms can identify anonymous programmers
Rachel Greenstadt, associate professor of computer science at Drexel University, and Aylin Caliskan, an assistant professor at George Washington University, have found that code can be a form of stylistic expression, a bit like writing, reported Wired.
As such, the researchers developed a machine learning algorithm to recognise the coding structure used by individual programmers based on samples of their work and spot their traits in compiled binaries or raw source code.
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