"Rust is the fastest-growing programming language, with its developer community doubling in size over the past two years," writes The New Stack, "yet JavaScript remains the most popular language with 25.2 million active developers, according to the results of a recent survey." The 26th edition of SlashData's Developer Nation survey showed that the Rust community doubled its number of users over the past two years — from two million in the first quarter of 2022 to four million in the first quarter of 2024 — and by 33% in the last 12 months alone. The SlashData report covers the first quarter of 2024. "Rust has developed a passionate community that advocates for it as a memory-safe language which can provide great performance, but cybersecurity concerns may lead to an even greater increase," the report said. "The USA and its international partners have made the case in the last six months for adopting memory-safe languages...."

"JavaScript's dominant position is unlikely to change anytime soon, with its developer population increasing by 4M developers over the last 12 months, with a growth rate in line with the global developer population growth," the report said. The strength of the JavaScript community is fueled by the widespread use of the language across all types of development projects, with at least 25% of developers in every project type using it, the report said. "Even in development areas not commonly associated with the language, such as on-device coding for IoT projects, JavaScript still sees considerable adoption," SlashData said.

Also, coming in strong, Python has overtaken Java as the second most popular language, driven by the interest in machine learning and AI. The battle between Python and Java shows Python with 18.2 million developers in Q1 2024 compared to Java's 17.7 million. This comes about after Python added more than 2.1 million net new developers to its community over the last 12 months, compared to Java which only increased by 1.2 million developers... Following behind Java there is a six-million-developer gap to the next largest community, which is C++ with 11.4 million developers, closely trailed by C# with 10.2 million and PHP with 9.8 million. Languages with the smallest communities include Objective-C with 2.7 million developers, Ruby with 2.5 million, and Lua with 1.8 million. Meanwhile, the Go language saw its developer population grow by 10% over the last year. It had previously outpaced the global developer population growth, growing by 5Y% over the past two years, from three million in Q1 2022 to 4.7 million in Q1 2024.
"TNS analyst Lawrence Hecht has a few different takeaways. He notes that with the exceptions of Rust, Go and JavaScript, the other major programming languages all grew slower than the total developer population, which SlashData says increased 39% over the last two years alone."

Mistral, the French AI startup backed by Microsoft and valued at $6 billion, has released its first generative AI model for coding, dubbed Codestral. From a report: Codestral, like other code-generating models, is designed to help developers write and interact with code. It was trained on over 80 programming languages, including Python, Java, C++ and JavaScript, explains Mistral in a blog post. Codestral can complete coding functions, write tests and "fill in" partial code, as well as answer questions about a codebase in English. Mistral describes the model as "open," but that's up for debate. The startup's license prohibits the use of Codestral and its outputs for any commercial activities. There's a carve-out for "development," but even that has caveats: the license goes on to explicitly ban "any internal usage by employees in the context of the company's business activities." The reason could be that Codestral was trained partly on copyrighted content. Codestral might not be worth the trouble, in any case. At 22 billion parameters, the model requires a beefy PC in order to run.

"While general-purpose languages like Python, C++, and Java remain popular in AI development," writes VentureBeat, "the resurgence of AI-first languages signifies a recognition that AI's unique demands require specialized languages tailored to the domain's specific needs... designed from the ground up to address the specific needs of AI development." Bend, created by Higher Order Company, aims to provide a flexible and intuitive programming model for AI, with features like automatic differentiation and seamless integration with popular AI frameworks. Mojo, developed by Modular AI, focuses on high performance, scalability, and ease of use for building and deploying AI applications. Swift for TensorFlow, an extension of the Swift programming language, combines the high-level syntax and ease of use of Swift with the power of TensorFlow's machine learning capabilities...

At the heart of Mojo's design is its focus on seamless integration with AI hardware, such as GPUs running CUDA and other accelerators. Mojo enables developers to harness the full potential of specialized AI hardware without getting bogged down in low-level details. One of Mojo's key advantages is its interoperability with the existing Python ecosystem. Unlike languages like Rust, Zig or Nim, which can have steep learning curves, Mojo allows developers to write code that seamlessly integrates with Python libraries and frameworks. Developers can continue to use their favorite Python tools and packages while benefiting from Mojo's performance enhancements... It supports static typing, which can help catch errors early in development and enable more efficient compilation... Mojo also incorporates an ownership system and borrow checker similar to Rust, ensuring memory safety and preventing common programming errors. Additionally, Mojo offers memory management with pointers, giving developers fine-grained control over memory allocation and deallocation...

Mojo is conceptually lower-level than some other emerging AI languages like Bend, which compiles modern high-level language features to native multithreading on Apple Silicon or NVIDIA GPUs. Mojo offers fine-grained control over parallelism, making it particularly well-suited for hand-coding modern neural network accelerations. By providing developers with direct control over the mapping of computations onto the hardware, Mojo enables the creation of highly optimized AI implementations.

According to Mojo's creator, Modular, the language has already garnered an impressive user base of over 175,000 developers and 50,000 organizations since it was made generally available last August. Despite its impressive performance and potential, Mojo's adoption might have stalled initially due to its proprietary status. However, Modular recently decided to open-source Mojo's core components under a customized version of the Apache 2 license. This move will likely accelerate Mojo's adoption and foster a more vibrant ecosystem of collaboration and innovation, similar to how open source has been a key factor in the success of languages like Python.

Developers can now explore Mojo's inner workings, contribute to its development, and learn from its implementation. This collaborative approach will likely lead to faster bug fixes, performance improvements and the addition of new features, ultimately making Mojo more versatile and powerful.
The article also notes other languages "trying to become the go-to choice for AI development" by providing high-performance execution on parallel hardware. Unlike low-level beasts like CUDA and Metal, Bend feels more like Python and Haskell, offering fast object allocations, higher-order functions with full closure support, unrestricted recursion and even continuations. It runs on massively parallel hardware like GPUs, delivering near-linear speedup based on core count with zero explicit parallel annotations — no thread spawning, no locks, mutexes or atomics. Powered by the HVM2 runtime, Bend exploits parallelism wherever it can, making it the Swiss Army knife for AI — a tool for every occasion...

The resurgence of AI-focused programming languages like Mojo, Bend, Swift for TensorFlow, JAX and others marks the beginning of a new era in AI development. As the demand for more efficient, expressive, and hardware-optimized tools grows, we expect to see a proliferation of languages and frameworks that cater specifically to the unique needs of AI. These languages will leverage modern programming paradigms, strong type systems, and deep integration with specialized hardware to enable developers to build more sophisticated AI applications with unprecedented performance. The rise of AI-focused languages will likely spur a new wave of innovation in the interplay between AI, language design and hardware development. As language designers work closely with AI researchers and hardware vendors to optimize performance and expressiveness, we will likely see the emergence of novel architectures and accelerators designed with these languages and AI workloads in mind. This close relationship between AI, language, and hardware will be crucial in unlocking the full potential of artificial intelligence, enabling breakthroughs in fields like autonomous systems, natural language processing, computer vision, and more.

The future of AI development and computing itself are being reshaped by the languages and tools we create today.
In 2017 Modular AI's founder Chris Lattner (creator of the Swift and LLVM) answered questions from Slashdot readers.

"The TIOBE Index sets out to reflect the relative popularity of computer languages," writes i-Programmer, "so it comes as something of a surprise to see two languages dating from the 1950's in this month's Top 20. 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:

1. Python
2. C
3. C++
4. Java
5. C#
6. JavaScript
7. Visual Basic
8. Go
9. SQL
10. 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:

1. Python (28.98% share)
2. Java (15.97% share)
3. JavaScript (8.79%)
4. C# (6.78% share)
5. R (4.76% share)
6. PHP (4.55% share)
7. TypeScript (3.03% share)
8. Swift (2.76% share)
9. Rust (2.6% share)

The PHP programming language has sunk to its lowest position ever on the long-running TIOBE index of programming language popularity. It now ranks #17 — lower than Assembly Language, Ruby, Swift, Scratch, and MATLAB. InfoWorld reports: When the Tiobe index started in 2001, PHP was about to become the standard language for building websites, said Paul Jansen, CEO of software quality services vendor Tiobe. PHP even reached the top 3 spot in the index, ranking third several times between 2006 and 2010. But as competing web development frameworks such as Ruby on Rails, Django, and React arrived in other languages, PHP's popularity waned.

"The major driving languages behind these new frameworks were Ruby, Python, and most notably JavaScript," Jansen noted in his statement accompanying the index. "On top of this competition, some security issues were found in PHP. As a result, PHP had to reinvent itself." Nowadays, PHP still has a strong presence in small and medium websites and is the language leveraged in the WordPress web content management system. "PHP is certainly not gone, but its glory days seem to be over," Jansen said.
A note on the rival Pypl Popularity of Programming Language Index argues that the TIOBE Index "is a lagging indicator. It counts the number of web pages with the language name." So while "Objective-C" ranks #30 on TIOBE's index (one rank above Classic Visual Basic), "who is reading those Objective-C web pages? Hardly anyone, according to Google Trends data." On TIOBE's index, Fortran now ranks #10.

Meanwhile, PHP ranks #7 on Pypl (based on the frequency of searches for language tutorials).

TIOBE's top ten?

1. Python
2. C
3. C++
4. Java
5. C#
6. JavaScript
7. Go
8. Visual Basic
9. SQL
10. Fortran

The next two languages, ranked #11 and #12, are Delphi/Object Pascal and Assembly Language.

"It's a bad day for bugs," joked TechCrunch on Wednesday. "Earlier today, Sentry announced its AI Autofix feature for debugging production code..."

And then the same day, BleepingComputer reported that GitHub "introduced a new AI-powered feature capable of speeding up vulnerability fixes while coding." This feature is in public beta and automatically enabled on all private repositories for GitHub Advanced Security customers. Known as Code Scanning Autofix and powered by GitHub Copilot and CodeQL, it helps deal with over 90% of alert types in JavaScript, Typescript, Java, and Python... After being toggled on, it provides potential fixes that GitHub claims will likely address more than two-thirds of found vulnerabilities while coding with little or no editing.

"When a vulnerability is discovered in a supported language, fix suggestions will include a natural language explanation of the suggested fix, together with a preview of the code suggestion that the developer can accept, edit, or dismiss," GitHub's Pierre Tempel and Eric Tooley said...

Last month, the company also enabled push protection by default for all public repositories to stop the accidental exposure of secrets like access tokens and API keys when pushing new code. This was a significant issue in 2023, as GitHub users accidentally exposed 12.8 million authentication and sensitive secrets via more than 3 million public repositories throughout the year.
GitHub will continue adding support for more languages, with C# and Go coming next, according to their announcement.

"Our vision for application security is an environment where found means fixed."

Databricks CTO Matei Zaharia "said that Databricks had to keep track of scheduling a million things," remembers adjunct MIT professor Michael Stonebraker. " He said that this can't be done with traditional operating system scheduling, and so this was done out of a Postgres database. And then he started to whine that Postgres was too slow, and I told him we can do better than that...."

This resulted in DBOS — short for "database operating system" — which they teamed up to build with teams Stanford and MIT, according to The Next Platform: They founded a company to commercialize the idea in April 2023 and secured $8.5 million initial seed funding to start building the real DBOS. Engine Ventures and Construct Capital led the funding, along with Sinewave and GutBrain Ventures...

"The state that the operating system has to keep track of — memory, files, messages, and so on — is approximately linear to the resources you have got," says Stonebraker. "So without me saying another word, keeping track of operating system state is a database problem not addressed by current operating system schedulers. Moreover, OLTP [Online Transaction Processing] database performance has gone up dramatically, and that is why we thought instead of running the database system in user space on top of the operating system, why don't we invert our thinking 180 degrees and run the operating system on top of the database, with all of the operating services are coded in SQL...?"

For now, DBOS can give the same kind of performance as that full blown Linux operating system, and thanks to the distributed database underpinnings of its kernel, it can do things that a Linux kernel just cannot do... One is provide reliable execution, which means that if a program running atop DBOS is ever interrupted, it starts where it left off and does not have to redo its work from some arbitrary earlier point and does not crash and have to start from the beginning. And because every little bit of the state of the operating system — and therefore the applications that run atop it — is preserved, you can go backwards in time in the system and restart the operating system if it experiences some sort of anomaly, such as a bad piece of application software running or a hack attack. You can use this "time travel" feature, as Stonebraker calls it, to reproduce what are called heisenbugs — ones that are very hard to reproduce precisely because there is no shared state in the distributed Linux and Kubernetes environment and that are increasingly prevalent in a world of microservices.

The other benefit of the DBOS is that it presents a smaller attack surface for hackers, which boosts security, and that you analyze the metrics of the operating system in place since they are already in a NoSQL database that can be queried rather than aggregating a bunch of log files from up and down the software stack to try to figure out what is going on...

There is also a custom tier for DBOS, which we presume costs money, that can use other databases and datastores for user application data, stores more than three days of log data, can have multiple users per account, that adds email and Slack support with DBOS techies, and that is available on other clouds as well as AWS.
The operating system kernel/scheduler "is itself largely a database," with services written in TypeScript, according to the article. The first iteration used the FoundationDB distributed key-value store for its scheduling core (open sourced by Apple in 2018), according to the article — "a blazingly fast NoSQL database... Stonebraker says there is no reason to believe that DBOS can't scale across 1 million cores or more and support Java, Python, and other application languages as they are needed by customers..."

And the article speculates they could take things even further. "There is no reason why DBOS cannot complete the circle and not only have a database as an operating system kernel, but also have a relational database as the file system for applications."

Rust's official survey team released results from their 8th annual survey "focused on gathering insights and feedback from Rust users". In terms of operating systems used by Rustaceans, the situation is very similar to the results from 2022, with Linux being the most popular choice of Rust users [69.7%], followed by macOS [33.5%] and Windows [31.9%], which have a very similar share of usage. Rust programmers target a diverse set of platforms with their Rust programs, even though the most popular target by far is still a Linux machine [85.4%]. We can see a slight uptick in users targeting WebAssembly [27.1%], embedded and mobile platforms, which speaks to the versatility of Rust.

We cannot of course forget the favourite topic of many programmers: which IDE (developer environment) do they use. Visual Studio Code still seems to be the most popular option [61.7%], with RustRover (which was released last year) also gaining some traction [16.4%].
The site ITPro spoke to James Governor, co-founder of the developer-focused analyst firm RedMonk, who said Rust's usage is "steadily increasing", pointing to its adoption among hyperscalers and cloud companies and in new infrastructure projects. "Rust is not crossing over yet as a general-purpose programming language, as Python did when it overtook Java, but it's seeing steady growth in adoption, which we expect to continue. It seems like a sustainable success story at this point."

But InfoWorld writes that "while the use of Rust language by professional programmers continues to grow, Rust users expressed concerns about the language becoming too complex and the low level of Rust usage in the tech industry." Among the 9,374 respondents who shared their main worries for the future of Rust, 43% were most concerned about Rust becoming too complex, a five percentage point increase from 2022; 42% were most concerned about low usage of Rust in the tech industry; and 32% were most concerned about Rust developers and maintainers not being properly supported, a six percentage point increase from 2022. Further, the percentage of respondents who were not at all concerned about the future of Rust fell, from 30% in 2022 to 18% in 2023.

The Tiobe index tries to gauge the popularity of programming languages based on search results for courses, programmers, and third-party vendors, according to InfoWorld.

And by that criteria, "Google's Go language, or golang, has reached its highest position ever..." The language, now in the eighth ranked position for language popularity, has been on the rise for several years.... In 2015, Go hit position #122 in the TIOBE index and all seemed lost," said Paul Jansen, CEO of Tiobe. "One year later, Go adopted a very strict 'half-a-year' release cycle — backed up by Google. Every new release, Go improved... Nowadays, Go is used in many software fields such as back-end programming, web services and APIs," added Jansen...

Elsewhere in the February release of Tiobe's index, Google's Carbon language, positioned as a successor to C++, reached the top 100 for the first time. Python is #1 on both TIOBE's index and the alternative Pypl Popularity of Programming Language index, which InfoWorld says "assesses language popularity based on how often language tutorials are searched on in Google." But the two lists differ on whether Java and JavaScript are more popular than C-derived languages — and which languages should then come after them. (Go ranks #12 on the Pypl index...)

TIOBE's calculation of the 10 most-popular programming languages:

1. Python
2. C
3. C++
4. Java
5. C#
6. JavaScript
7. SQL
8. Go
9. Visual Basic
10. PHP

Pypl's calculation of the 10 most-popular programming languages:

1. Python
2. Java
3. JavaScript
4. C/C++
5. C#
6. R
7. PHP
8. TypeScript
9. Swift
10. Objective-C

On Tuesday, The Independent, Tom's Hardware, and many other tech outlets reported on a story about how three million smart toothbrushes were used in a DDoS attack. The only problem? It "didn't actually happen," writes Jason Koebler via 404 Media. "There are no additional details about this apparent attack, and most of the article cites general research by a publicly traded cybersecurity company called Fortinet which has detected malicious, hijacked internet of things devices over the years. A search on Fortinet's website shows no recent published research about hacked smart toothbrushes." From the report: The original article, called "The toothbrushes are attacking," starts with the following passage: "She's at home in the bathroom, but she's part of a large-scale cyber attack. The electric toothbrush is programmed with Java, and criminals have unnoticed installed malware on it - like on 3 million other toothbrushes. One command is enough and the remote-controlled toothbrushes simultaneously access the website of a Swiss company. The site collapses and is paralyzed for four hours. Millions of dollars in damage is caused. This example, which seems like a Hollywood scenario, actually happened. It shows how versatile digital attacks have become." [...]

The "3 million hacked smart toothbrushes" story has now been viral for more than 24 hours and literally no new information about it has emerged despite widespread skepticism from people in the security industry and its virality. The two Fortinet executives cited in the original report did not respond to an email and LinkedIn message seeking clarification, and neither did Fortinet's PR team. The author of the Aargauer Zeitung story also did not respond to a request for more information. I called Fortinet's headquarters, asked to speak to the PR contact listed on the press release about its earnings, which was published after the toothbrush news began to go viral, and was promptly disconnected. The company has continued to tweet about other, unrelated things. They have not responded to BleepingComputer either, nor the many security researchers who are asking for further proof that this actually happened. While we don't know how this happened, Fortinet has been talking specifically about the dangers of internet-connected toothbrushes for years, and has been using it as an example in researcher talks. In a statement to 404 Media, Fortinet said "To clarify, the topic of toothbrushes being used for DDoS attacks was presented during an interview as an illustration of a given type of attack, and it is not based on research from Fortinet or FortiGuard Labs. It appears that due to translations the narrative on this topic has been stretched to the point where hypothetical and actual scenarios are blurred."

An anonymous reader quotes a report from Tom's Hardware: According to a recent report published by the Aargauer Zeitung (h/t Golem.de), around three million smart toothbrushes have been infected by hackers and enslaved into botnets. The source report says this sizable army of connected dental cleansing tools was used in a DDoS attack on a Swiss company's website. The firm's site collapsed under the strain of the attack, reportedly resulting in the loss of millions of Euros of business. In this particular case, the toothbrush botnet was thought to have been vulnerable due to its Java-based OS. No particular toothbrush brand was mentioned in the source report. Normally, the toothbrushes would have used their connectivity for tracking and improving user oral hygiene habits, but after a malware infection, these toothbrushes were press-ganged into a botnet.

Stefan Zuger from the Swiss branch of the global cybersecurity firm Fortinet provided the publication with a few tips on what people could do to protect their own toothbrushes -- or other connected gadgetry like routers, set-top boxes, surveillance cameras, doorbells, baby monitors, washing machines, and so on. "Every device that is connected to the Internet is a potential target -- or can be misused for an attack," Zuger told the Swiss newspaper. The security expert also explained that every connected device was being continually probed for vulnerabilities by hackers, so there is a real arms race between device software/firmware makers and cyber criminals. Fortinet recently connected an 'unprotected' PC to the internet and found it took only 20 minutes before it became malware-ridden. UPDATE 1/7/24: This attack "didn't actually happen," writes Jason Koebler via 404 Media. "There are no additional details about this apparent attack, and most of the article cites general research by a publicly traded cybersecurity company called Fortinet which has detected malicious, hijacked internet of things devices over the years. A search on Fortinet's website shows no recent published research about hacked smart toothbrushes."

The cybersecurity firm Fortinet said in a statement: "To clarify, the topic of toothbrushes being used for DDoS attacks was presented during an interview as an illustration of a given type of attack, and it is not based on research from Fortinet or FortiGuard Labs. It appears that due to translations the narrative on this topic has been stretched to the point where hypothetical and actual scenarios are blurred. FortiGuard Labs has not observed Mirai or other IoT botnets target toothbrushes or similar embedded devices."

"Oracle's plans to evolve Java in 2024 involve OpenJDK projects," writes InfoWorld, citing a recent video by Oracle Java developer relations representative Nicolai Parlog. (Though many improvements may not be usable until 2025 or later...) - For Project Babylon, Parlog cited plans for code reflection, expanding the reflection API, and allowing transformation of Java code inside a method. The goal is to allow developers to write Java code that libraries then can interpret as a mathematical function, for example. The Babylon team in coming weeks plans to publish work on use cases such as auto-differentiating, C# LINQ emulation, and GPU programming.

- In Project Leyden, which is aimed at improving startup times, plans for 2024 involve refining the concept of condensers and working toward the production-readiness of prototype condensers.

- In Project Amber, current features in preview include string templates, a simplified main method, and statements before this() and super(). "I expect all three to finalize in 2024," said Parlog. Under exploration are capabilities such as primitive types in patterns and with expressions.

- In Project Valhalla, work will focus on value classes and objects, which provide class instances that have only final instance fields and lack object identity [to] significantly reduce the run time overhead of boxed Integer, Double, and Byte objects...

- In Project Lilliput, aimed at downsizing Java object headers in the HotSpot JVM and reducing Java's memory footprint, work now centers on polishing a fast-locking scheme.

- Project Panama, for interconnecting JVM and native C code, "has three irons in the fire," Parlog said.

It's a geek tradition that started online back in 2000. Programming language "advent calendars" offer daily tips about a programming language (if not a Christmas-themed programming puzzle) -- one a day through December 25th.

And 2023 finds a wide variety of fun sites to choose from:

• For example, there's 24 coding challenges at the Advent of JavaScript site (where "each challenge includes all the HTML and CSS you need to get started, allowing you to focus on the JavaScript.") And there's another 24 coding challenges on a related site... Advent of CSS.

• The cyber security training platform "TryHackMe.com" even coded up a site they call "Advent of Cyber," daring puzzle-solvers to "kickstart your cyber security career by engaging in a new, beginner-friendly exercise every day leading up to Christmas!"

• The programming puzzles at Advent of Code are continuing through the 25th (though so far less than 30,000 people have solved both parts of Saturday's challenge.)

• Every year since 2000 there's also been a new edition of the Perl Advent Calendar, and this month Year 23 started off with goodies from Perl's massive module repository, CPAN. (Specifically its elf-themed story references the Music::MelodicDevice::Ornamentation module) -- along with the MIDI::Util library and TiMidity++, a software synthesizer that can play MIDI files without a hardware synthesizer.)

• Meanwhile, since 2009 there's also been an advent calendar for Raku (the programming language formerly known as Perl 6), promising an article a day. (Day One's entry was titled "Rocking Raku Meets Stodgy Debian...")

• James Bennett, from the Django project's core team, is even attempting a Python/Django Advent calendar.

• There's also a JVM advent calendar for the Java Virtual Machine, plus another advent calendar promising daily posts about C#.

• The HTMHell site — which bills itself as "a collection of bad practices in HTML, copied from real websites" — is celebrating the season with the "HTMHell Advent Calendar," promising daily articles on security, accessibility, UX, and performance.

An anonymous reader quotes a report from The Register: Two years after the Log4Shell vulnerability in the open source Java-based Log4j logging utility was disclosed, circa one in four applications are dependent on outdated libraries, leaving them open to exploitation. Research from security shop Veracode revealed that the vast majority of vulnerable apps may never have updated the Log4j library after it was implemented by developers as 32 percent were running pre-2015 EOL versions. Prior investigations from Veracode also showed that 79 percent of all developers never update third-party libraries after first introducing them into projects, and given that Log4j2 -- the specific version of Log4j affected by the vulnerability -- dates back to 2014, this could explain the large proportion of unpatched apps.

A far smaller minority are running versions that were vulnerable at the time of the Log4j vulnerability's disclosure in December 2021. Only 2.8 percent are still using versions 2.0-beta9 through 2.15.0 -- post-EOL versions that remain exposed to Log4Shell, the industry-coined moniker of the vulnerability's exploit. Some 3.8 percent are still running version 2.17, a post-patch version of the Java logger that's not exposed to Log4Shell attacks, but is vulnerable to a separate remote code execution (RCE) bug (CVE-2021-44832).

The researchers believe this illustrates a minority of developers that acted quickly when the vulnerability was first disclosed, as was the advice at the time, had returned to older habits of leaving libraries untouched. Altogether, just shy of 35 percent remain vulnerable to Log4Shell, and nearly 40 percent are vulnerable to RCE flaws. The EOL versions of Log4j are also vulnerable to three additional critical bugs announced by Apache, bringing the total to seven high and critical-rated issues. "At a surface level, the numbers above show that the massive effort to remediate the Log4Shell vulnerability was effective in mitigating risk of exploitation of the zero-day vulnerability. That should not be surprising," said Chris Eng, chief research officer at Veracode.

"The bigger story at the two-year anniversary, however, is that there is still room for improvement when it comes to open source software security. If Log4Shell was another example in a long series of wake-up calls to adopt more stringent open source security practices, the fact that more than one in three applications currently run vulnerable versions of Log4j shows there is more work to do.

"The major takeaway here is that organizations may not be aware of how much open source security risk they are exposed to and how to mitigate it."

"Every day, 3 trillion dollars worth of transactions are handled by a 64-year-old programming language that hardly anybody knows anymore," writes PC Magazine. But most school's don't teach the mainframe programming language COBOL any more, and "COBOL cowboys" are aging out of the workforce, with replacements in short supply.

"This is precisely the kind of problem that IBM thinks it can fix with AI." IBM's approach is fairly straightforward: Rather than relying exclusively on a limited pool of human programmers to solve the problem, it built a generative AI-powered code assistant (watsonx) that helps convert all that dusty old COBOL code to a more modern language, thereby saving coders countless hours of reprogramming. In extremely simplified terms, the process is similar to feeding an essay written in English into ChatGPT and asking it to translate certain paragraphs into Esperanto. It allows programmers to take a chunk of COBOL and enlist watsonx to transform it into Java.

But of course, it's not quite that simple in practice... After IBM and the customer have a thorough understanding of the application landscape, the data flow, and the existing dependencies, "we help them refactor their applications," says IBM's Vice President of Product Management, IT Automation, Keri Olson. "That is, breaking it down into smaller pieces, which the customer can selectively choose, at that point, to do the modernization from COBOL to Java." Skyla Loomis, IBM's Vice President of IBM Z Software adds, "But you have to remember that this is a developer assistant tool. It's AI assisted, but it still requires the developer. So yes, the developer is involved with the tooling and helping the customers select the services."

Once the partnership between man and machine is established, the AI steps in and says, 'Okay, I want to transform this portion of code. The developer may still need to perform some minor editing of the code that the AI provides, Loomis explains. "It might be 80 or 90 percent of what they need, but it still requires a couple of changes. It's a productivity enhancement — not a developer replacement type of activity."
The article quotes a skeptical Gartner Distinguished Vice President and Analyst, who notes that IBM "has no case studies, at this time, to validate its claims."

"Structured concurrency is a new way to use multithreading in Java," reports InfoWorld.

"It allows developers to think about work in logical groups while taking advantage of both traditional and virtual threads." Available in preview in Java 21, structured concurrency is a key aspect of Java's future, so now is a good time to start working with it... Java's thread model makes it a strong contender among concurrent languages, but multithreading has always been inherently tricky. Structured concurrency allows you to use multiple threads with structured programming syntax. In essence, it provides a way to write concurrent software using familiar program flows and constructs. This lets developers focus on the business at hand, instead of the orchestration of threading.

As the JEP for structured concurrency says, "If a task splits into concurrent subtasks then they all return to the same place, namely the task's code block." Virtual threads, now an official feature of Java, create the possibility of cheaply spawning threads to gain concurrent performance. Structured concurrency provides the simple syntax to do so. As a result, Java now has a unique and highly-optimized threading system that is also easy to understand...

Between virtual threads and structured concurrency, Java developers have a compelling new mechanism for breaking up almost any code into concurrent tasks without much overhead... Any time you encounter a bottleneck where many tasks are occurring, you can easily hand them all off to the virtual thread engine, which will find the best way to orchestrate them. The new thread model with structured concurrency also makes it easy to customize and fine-tune this behavior. It will be very interesting to see how developers use these new concurrency capabilities in our applications, frameworks, and servers going forward.
It involves a new class StructuredTaskScope located in the java.util.concurrent library. (InfoWorld points out that "you'll need to use --enable-preview and --source 21 or --source 22 to enable structured concurrency.")

Their reporter shared an example on GitHub, and there's more examples in the Java 21 documentation. "The structured concurrency documentation includes an example of collecting subtask results as they succeed or fail and then returning the results."

An anonymous reader shared this report from InfoWorld: JetBrains' Kotlin language, a Java rival endorsed by Google for Android mobile development, continues to scale up Tiobe's index of language popularity, reaching the 15th spot in the November 2023 rankings...

Software quality services company Tiobe cites Kotlin advantages including interoperability with Java and unrivaled Android accommodations as reasons for the language's rise. Kotlin, Tiobe CEO Paul Jansen said, also fits in with a modern programming culture of expressive languages that have a strong type system and avoid null pointer exceptions by design. "Based on my experience, I am pretty sure Kotlin can reach a top 10 position," Jansen said. It remains to be seen if it can ever scale as high as a top four slot, he added...

In the rival Pypl Popularity of Programming languages index this month, Kotlin was ranked 13th with a 1.76% share, having slipped slightly year-over-year.
Kotlin's rank on the TIOBE index rose three positions in the last month — after rising two positions the month before. TIOBE's CEO says the language has now achieved its highest ranking ever on the index, surpassing 2017's "first wave of Kotlin popularity...when Google announced first class support for Kotlin on Android."

Rust now ranks #20 on the index, behind Delphi/Object Pascal, Swift, Ruby, and R.

Here's TIOBE November rankings for top-20 most popular programming languages:

1. Python
2. C
3. C++
4. Java
5. C#
6. JavaScript
7. PHP
8. Visual Basic
9. SQL
10. Assembly Language
11. Scratch
12. Fortran
13. Go
14. MATLAB
15. Kotlin
16. Delphi/Object Pascal
17. Swift
18. Ruby
19. R
20. Rust

In Chrome, JavaScript (and WebAssembly) code are both executed by Google's open source V8 engine — which already has garbage-collecting capabilities. "This means developers making use of, for example, PHP compiled to Wasm, end up shipping a garbage collector implementation of the ported language (PHP) to the browser that already has a garbage collector," writes Google developer advocate Thomas Steiner, "which is as wasteful as it sounds."

"This is where WasmGC comes in." WebAssembly Garbage Collection (or WasmGC) is a proposal of the WebAssembly Community Group [which] adds struct and array heap types, which means support for non-linear memory allocation... In simplified terms, this means that with WasmGC, porting a programming language to WebAssembly means the programming language's garbage collector no longer needs to be part of the port, but instead the existing garbage collector can be used.
Sometime on Halloween, Steiner wrote that in Chrome, WebAssembly garbage collection is now enabled by default. But then he explored what this means for high-level programming languages (with their own built-in garbage collection) being compiled into WebAssembly: To verify the real-world impact of this improvement, Chrome's Wasm team has compiled versions of the Fannkuch benchmark (which allocates data structures as it works) from C, Rust, and Java. The C and Rust binaries could be anywhere from 6.1 K to 9.6 K depending on the various compiler flags, while the Java version is much smaller at only 2.3 K! C and Rust do not include a garbage collector, but they do still bundle malloc/free to manage memory, and the reason Java is smaller here is because it doesn't need to bundle any memory management code at all. This is just one specific example, but it shows that WasmGC binaries have the potential of being very small, and this is even before any significant work on optimizing for size.
The blog post includes two examples of WasmGC-ported programming languages in action:

• "One of the first programming languages that has been ported to Wasm thanks to WasmGC is Kotlin in the form of Kotlin/Wasm."

• "The Dart and Flutter teams at Google are also preparing support for WasmGC. The Dart-to-Wasm compilation work is almost complete, and the team is working on tooling support for delivering Flutter web applications compiled to WebAssembly."

An anonymous reader quotes a report from Ars Technica: Android is slowly entering the RISC-V era. So far we've seen Google say it wants to give the up-and-coming CPU architecture "tier-1" support in Android, putting RISC-V on equal footing with Arm. Qualcomm has announced the first mass-market RISC-V Android chip, a still-untitled Snapdragon Wear chip for smartwatches. Now Google has announced a timeline for developer tools via the Google Open Source Blog. The last post is titled "Android and RISC-V: What you need to know to be ready."

Getting the Android OS and app ecosystem to support a new architecture is going to take an incredible amount of work from Google and developers, and these tools are laying the foundation for that work. First up, Google already has the "Cuttlefish" virtual device emulator running, including a gif of it booting up. This isn't the official "Android Emulator" -- which is targeted at app developers doing app development -- Cuttlefish is a hardware emulator for Android OS development. It's the same idea as the Android Emulator but for the bottom half of the tech stack -- the kernel, framework, and hardware bits. Cuttlefish lets Google and other Android OS contributors work on a RISC-V Android build without messing with an individual RISC-V device. Google says it's working well enough now that you can download and emulate a RISC-V device today, though the company warns that nothing is optimized yet.

The next step is getting the Android Emulator (for app developers) up and running, and Google says: "By 2024, the plan is to have emulators available publicly, with a full feature set to test applications for various device form factors!" The nice thing about Android is that most app code is written with no architecture in mind -- it's all just Java/Kotlin. So once the Android RunTime starts spitting out RISC-V code, a lot of app code should Just Work. That means most of the porting work will need to go into things written in the NDK, the native developer kit, like libraries and games. The emulator will still be great for testing, though.

"A recent analysis accounting for nearly 1.2 million open source software projects primarily across four major ecosystems found that only about 11% of projects were actively maintained," reports InfoWorld: In its 9th Annual State of the Software Supply Chain report, published October 3, software supply chain management company Sonatype assessed 1,176,407 projects and reported an 18% decline this year in actively maintained projects. Just 11% of projects — 118,028 — were receiving active maintenance.

The report also found some new projects, unmaintained in 2022, now being maintained.

The four ecosystems included JavaScript, via NPM; Java, via the Maven project management tool; Python, via the PyPI package index; and .NET, through the NuGet gallery. Some Go projects also were included. According to the report, 18.6% of Java and JavaScript projects that were being maintained in 2022 are no longer being maintained today.
Other interesting findings:

• Nearly 10% reported security breaches due to open source vulnerabilities in the past 12 months.

• Use of AI and machine learning software components within corporate environments surged 135% over the last year.