Category: programming

“With the exception of Java, the C-family of languages still dominates,” the article concludes, before adding that if you’re only going to learn one language, “I’d recommend Python, Java, and JavaScript instead.” But it also advises aspiring programmers to learn “multiple languages and multiple frameworks. Build things in the languages. Programming is not just an intellectual exercise. You have to actually make stuff….

“[L]earning how to learn languages is as important as learning a language — and the best way to do that is to learn more than one.”

As the “hand” moves from the tail (the oldest object) to the head (the newest object), objects that have not been visited are evicted… During the subsequent rounds of sifting, if objects that survived previous rounds remain popular, they will stay in the cache. In such a case, since most old objects are not evicted, the eviction hand quickly moves past the old popular objects to the queue positions close to the head. This allows newly inserted objects to be quickly assessed and evicted, putting greater eviction pressure on unpopular items (such as “one-hit wonders”) than LRU-based eviction algorithms.
It’s an example of “lazy promotion and quick demotion”. Popular objects get retained with minimal effort, with quick demotion “critical because most objects are not reused before eviction.”

After 1559 traces (of 247,017 million requests to 14,852 million objects), they found SIEVE reduces the miss ratio (when needed data isn’t in the cache) by more than 42% on 10% of the traces with a mean of 21%, when compared to FIFO. (And it was also faster and more scalable than LRU.)

“SIEVE not only achieves better efficiency, higher throughput, and better scalability, but it is also very simple.”

1. Python
2. C++
3. C
4. Java

C++ started a new life as of 2011 with its consistent 3 yearly updates. Although most compilers and most engineers can’t take up with this pace, it is considered a success to see the language evolve.

The main strengths of C++ are its performance and scalability. Its downside is its many ways to get things done, i.e. its rich idiom of features, which is caused by its long history and aim for backward compatibility.

C++ is heavily used in embedded systems, game development and financial trading software, just to name a few domains.

There’s different rankings from the rival PYPL index of programming language popularity. It lumps C and C++ together to award them a collective ranking (#5). But unlike TIOBE, it shows Java [and JavaScript and C#] all being more popular (with Python still the #1 most popular language).

Of course, statistical anomalies could be also skewing the results. Visual Basic also lost two ranks in popularity in the last month, according to TIOBE, dropping from the #7 position to the #9 position (now falling just behind Go and SQL). This becomes the first time that Go has risen as high as #7, according to TIOBE’s announcement — with Rust also reaching an all-time high of #17…

Having broken into the the Top 20 in April 2021 Fortran has continued to rise and has now risen to it’s highest ever position at #10… The headline for this month’s report by Paul Jansen on the TIOBE index is:
Fortran in the top 10, what is going on?
Jansen’s explanation points to the fact that there are more than 1,000 hits on Amazon for “Fortran Programming” while languages such as Kotlin and Rust, barely hit 300 books for the same search query. He also explains that Fortran is still evolving with the new ISO Fortran 2023 definition published less than half a year ago….

The other legacy language that is on the rise in the TIOBE index is COBOL. We noticed it re-enter the Top 20 in January 2024 and, having dropped out in the interim, it is there again this month.

More details from TechRepublic:

Along with Fortran holding on to its spot in the rankings, there were a few small changes in the top 10. Go gained 0.61 percentage points year over year, rising from tenth place in May 2023 to eighth this year. C++ rose slightly in popularity year over year, from fourth place to third, while Java (-3.53%) and Visual Basic (-1.8) fell.

Here’s how TIOBE ranked the 10 most popular programming languages in May:

Python
C
C++
Java
C#
JavaScript
Visual Basic
Go
SQL
Fortran

On the rival PYPL ranking of programming language popularity, Fortran does not appear anywhere in the top 29.
A note on its page explains that “Worldwide, Python is the most popular language, Rust grew the most in the last 5 years (2.1%) and Java lost the most (-4.0%).” Here’s how it ranks the 10 most popular programming languages for May:

Python (28.98% share)
Java (15.97% share)
JavaScript (8.79%)
C# (6.78% share)
R (4.76% share)
PHP (4.55% share)
TypeScript (3.03% share)
Swift (2.76% share)
Rust (2.6% share)

And there’s now another update. LWN.net gets you up to speed, calling Julia “a general-purpose, open-source programming language with a focus on high-performance scientific computing.”

Some of Julia’s unusual features:
– Lisp-inspired metaprogramming
– The ability to examine compiled representations of code in the REPL or in a “reactive notebook”
– An advanced type and dispatch system
– A sophisticated, built-in package manager.

Version 1.10 brings big increases in speed and developer convenience, especially improvements in code precompilation and loading times. It also features a new parser written in Julia… [I]t is faster, it produces more useful syntax-error messages, and it provides better source-code mapping, which associates locations in compiled code to their corresponding lines in the source. That last improvement also leads to better error messages and makes it possible to write more sophisticated debuggers and linters…

Between the improvements in precompilation and loading times, and the progress in making small binaries, two major and perennial complaints, of beginners and seasoned Julia users alike, have been addressed… StaticCompiler and related WebAssembly tools will make it easier to write web applications in Julia for direct execution in the browser; it is already possible, but may become more convenient over the next few years.

Thanks for sharing the article to long-time Slashdot reader lee1 — who also wrote No Starch Press’s Practical Julia: A Hands-On Introduction for Scientific Minds .

lee1 also reminds us that Gnuplot 6.0 was released in December:
lee1 writes: This article surveys the new features, including filled contours in 3D, adaptive plotting resolution, watchpoints, clipping of surfaces, pie charts, and new syntax for conditionals.

Deprecated, archived and “orphaned” NPM packages can contain unpatched and/or unreported vulnerabilities that pose a risk to the projects that depend on them, warned the researchers from Aqua Security’s Team Nautilus, who published their findings in a blog post on Sunday… In conjunction with their research, Aqua Nautilus has released an open-source tool that can help developers identify deprecated dependencies in their projects.

Open-source software may stop receiving updates for a variety of reasons, and it is up to developers/maintainers to communicate this maintenance status to users. As the researchers pointed out, not all developers are transparent about potential risks to users who download or depend on their outdated NPM packages. Aqua Nautilus researchers kicked off their analysis after finding that one open-source software maintainer responded to a report about a vulnerability Nautilus discovered by archiving the vulnerable repository the same day. By archiving the repository without fixing the security flaw or assigning it a CVE, the owner leaves developers of dependent projects in the dark about the risks, the researchers said…

Taking into consideration both deprecated packages and active packages that have a direct dependency on deprecated projects, the researchers found about 4,100 (8.2%) of the top 50,000 most-downloaded NPM packages fell under the category of “official” deprecation. However, adding archived repositories to the definition of “deprecated” increased the number of packages affected by deprecation and deprecated dependencies to 6,400 (12.8%)… Including packages with linked repositories that are shown as unavailable (404 error) on GitHub increases the deprecation rate to 15% (7,500 packages), according to the Nautilus analysis. Encompassing packages without any linked repository brings the final number of deprecated packages to 10,600, or 21.2% of the top 50,000. Team Nautilus estimated that under this broader understanding of package deprecation, about 2.1 billion downloads of deprecated packages are made on the NPM registry weekly.

When it comes to static vs dynamic typing, “I’ve heard a million arguments from both sides throughout my entire career,” Hansson wrote on his blog today, “but seen very few of them ever convinced anyone of anything.”
But wait — he thinks we can all get along:
Personally, I’m unashamedly a dynamic typing kind of guy. That’s why I love Ruby so very much. It takes full advantage of dynamic typing to allow the poetic syntax that results in such beautiful code. To me, Ruby with explicit, static typing would be like a salad with a scoop of ice cream. They just don’t go together.

I’ll also confess to having embraced the evangelical position for dynamic typing in the past. To the point of suffering from a One True Proposition affliction. Seeing the lack of enthusiasm for dynamic typing as a reflection of missing education, experience, or perhaps even competence.

Oh what folly. Like trying to convince an introvert that they’d really like parties if they’d just loosen up a bit…

These days, I’ve come to appreciate the magnificence of multiplicity. Programming would be an awful endeavor if we were all confined to the same paradigm. Human nature is much too varied to accept such constraint on its creativity…But it took a while for me to come to these conclusions. I’m a recovering solutionist. So when I see folks cross their heart in disbelief that anyone, anywhere might fancy JavaScript over TypeScript, I smile, and I remember the days when I’d recognize their zeal in the mirror.

Hansson also sees the “magnificence of multiplicity” in positions about functional vs object-oriented programming. “Poles on both these axes have shown to deliver excellent software over the decades (and awful stuff too!).”

With the financial backing of Amazon Web Services, sudo and su are being rewritten in the Rust programming language in order to increase the memory safety for the widely relied upon software… to further enhance Linux/open-source security.
“[B]ecause it’s written in C, sudo has experienced many vulnerabilities related to memory safety issues,” according to a blog post announcing the project:
It’s important that we secure our most critical software, particularly from memory safety vulnerabilities. It’s hard to imagine software that’s much more critical than sudo and su.
This work is being done by a joint team from Ferrous Systems and Tweede Golf with generous support from Amazon Web Services. The work plan is viewable here. The GitHub repository is here.

Phoronix highlights two new improvements:

In order to speed-up compilation speeds, Rust 1.69 and moving forward debug information is no longer included in build scripts by default. Cargo will avoid emitting debug information in build scripts by default — leading to less informative backtraces in build scripts when problems arise, but faster build speeds by default. Those wanting the debug information emitted can now set the debug flag in their Cargo.toml configuration.

The Cargo build shipped by Rust 1.69 is also now capable of suggesting fixes automatically for some of the generated warnings. Cargo will also suggest using “cargo fix” / “cargo clippy –fix” when it knows the errors can be automatically fixed.