The Tiobe index tries to track the popularity of programming languages by counting the number of search results for the language's name followed by the word "programming" (on 25 different search engines). And this month there were some surprises...

By TIOBE's reckoning, compared to a year ago PHP has now fallen from #7 to #12, while Delphi/Object Pascal shot up five spots from #16 to #11. In that same year, Fortran jumped from #12 to #8 — while both Visual Basic and SQL dropped down a single rank. Toward the top of the list, C actually fell from the #2 spot over the last 12 months to the #4 spot.

And Go just reached the #7 rank on the TIOBE's ranking of programming language popularity — "an all time high for Go," according to TIOBE CEO Paul Jansen. In this month's note, he explains what he thinks is unusual about this — starting by saying that Go programs are both fast, and easy in many ways — easy to deploy, easy to learn, and easy to understand. Python for instance is easy to learn but not fast, and deployment for larger Python programs is fragile due to dependencies on all kind of versioned libraries in the environment.

If compared to Rust for instance (another contender for a top position), Go is a tiny bit slower, but the Go programs are much easier to understand. The next hurdle for Go in the TIOBE index is JavaScript at position #6. That will be a tough one to pass. JavaScript is ubiquitous in software development, although for larger JavaScript systems we see a shift to TypeScript nowadays.
"If annual trends continue this way, Go will bypass JavaScript within 3 years," TIOBE's CEO predicts. (Adding "Let's see what the future has in store for Go...") Although the Go team actually has specific plans for the future, according to a blog post this week celebrating Go's 15th anniversary: We're working on making Go better for AI — and AI better for Go — by enhancing Go's capabilities in AI infrastructure, applications, and developer assistance. Go is a great language for building production systems, and we want it to be a great language for building production AI systems, too... For AI applications, we will continue building out first-class support for Go in popular AI SDKs, including LangChainGo and Genkit. And from its very beginning, Go aimed to improve the end-to-end software engineering process, so naturally we're looking at bringing the latest tools and techniques from AI to bear on reducing developer toil, leaving more time for the fun stuff — like actually programming!
TIOBE's top 10 programming language rankings for the month of November:

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

"Java application security would be enhanced through two proposals aimed at resisting quantum computing attacks," reports InfoWorld, "one plan involving digital signatures and the other key encapsulation." The two proposals reside in the OpenJDK JEP (JDK Enhancement Proposal) index.

The Quantum-Resistant Module-Lattice-Based Digital Signature Algorithm proposal calls for enhancing the security of Java applications by providing an implementation of the quantum-resistant module-latticed-based digital signature algorithm (ML-DSA). ML-DSA would secure against future quantum computing attacks by using digital signatures to detect unauthorized modifications to data and to authenticate the identity of signatories. ML-DSA was standardized by the United States National Institute of Standards and Technology (NIST) in FIPS 204.

The Quantum-Resistant Module-Lattice-Based Key Encapsulation Mechanism proposal calls for enhancing application security by providing an implementation of the quantum-resistant module-lattice-based key encapsulation mechanism (ML-KEM). KEMs are used to secure symmetric keys over insecure communication channels using public key cryptography. ML-KEM is designed to be secure against future quantum computing attacks and was standardized by NIST in FIPS 203.

An anonymous reader quotes a report from Oregon Live: Intel told employees this week that it will bring back free coffee and tea at its work sites, one of many benefits the chipmaker eliminated last summer as it sought to slash $10 billion from its annual budget. "Although Intel still faces cost challenges, we understand that small comforts play a significant role in our daily routines," Intel wrote on its internal messaging forum, called Circuit. "We know this is a small step, but we hope it is a meaningful one in supporting our workplace culture." Intel declined comment. The company did not resume offering free fruit, another perk eliminated last summer. Employees say privately that morale has been devastated by Intel's poor financial performance and by cutbacks aimed at returning the business to profitability.

[...] Christy Pambianchi, Intel's chief people officer, told employees that Intel had been spending $100 million annually on free and discounted food and beverages and couldn't afford to keep doing that. "Until we get into a better financial health position, we need to be suspending those," Pambianchi said, according to an account of the meeting reviewed by The Oregonian/OregonLive. By Wednesday the company had reversed itself, committing to keep its employees caffeinated. In August, Intel announced plans to lay off over 16,000 employees, representing more than 15% of its global workforce. Its stock dropped to a 50-year low following the announcement. Starting November 8, Nvidia will replace the chipmaker on the Dow Jones Industrial Average.

GitHub released its annual "State of the Octoverse" report this week. And while "Systems programming languages, like Rust, are also on the rise... Python, JavaScript, TypeScript, and Java remain the most widely used languages on GitHub."

In fact, "In 2024, Python overtook JavaScript as the most popular language on GitHub." They also report usage of Jupyter Notebooks "skyrocketed" with a 92% jump in usage, which along with Python's rise seems to underscore "the surge in data science and machine learning on GitHub..." We're also seeing increased interest in AI agents and smaller models that require less computational power, reflecting a shift across the industry as more people focus on new use cases for AI... While the United States leads in contributions to generative AI projects on GitHub, we see more absolute activity outside the United States. In 2024, there was a 59% surge in the number of contributions to generative AI projects on GitHub and a 98% increase in the number of projects overall — and many of those contributions came from places like India, Germany, Japan, and Singapore...

Notable growth is occurring in India, which is expected to have the world's largest developer population on GitHub by 2028, as well as across Africa and Latin America... [W]e have seen greater growth outside the United States every year since 2013 — and that trend has sped up over the past few years.
Last year they'd projected India would have the most developers on GitHub #1 by 2027, but now believe it will happen a year later. This year's top 10?

1. United States
2. India
3. China
4. Brazil
5. United Kingdom
6. Russia
7. Germany
8. Indonesia
9. Japan
10. Canada

Interestingly, the UK's population ranks #21 among countries of the world, while Germany ranks #19, and Canada ranks #36.)

GitHub's announcement argues the rise of non-English, high-population regions "is notable given that it is happening at the same time as the proliferation of generative AI tools, which are increasingly enabling developers to engage with code in their natural language." And they offer one more data point: GitHub's For Good First Issue is a curated list of Digital Public Goods that need contributors, connecting those projects with people who want to address a societal challenge and promote sustainable development...

Significantly, 34% of contributors to the top 10 For Good Issue projects... made their first contribution after signing up for GitHub Copilot.
There's now 518 million projects on GitHub — with a year-over-year growth of 25%...

Boeing received an email from the chief pilot at Ethiopian Airlines on December 1, 2018 with several questions, reports the New York Times (alternate URL here). "in essence the pilot was asking for direction. If we see a series of warnings on the new 737 Max, he posed, what do we do?" What ensued was an email conversation among a number of Boeing senior officials about whether they could answer the pilot's questions without violating international restrictions on disseminating information about a crash while it was still under investigation. That restriction was in play because a 737 Max flown by Lion Air had crashed a few weeks earlier leaving Indonesia. The inquiry from Ethiopian Airlines would prove chillingly prescient because just months later one of its 737s would go down because of a flight control malfunction similar to the one that led to the Lion Air crash. The Ethiopian Airlines crash would kill everyone on board and leave questions about whether Boeing had done everything it could to inform pilots of what it had learned about the malfunction and how to handle it.

In response to the inquiry from Ethiopian Airlines, Boeing's chief pilot, Jim Webb, proposed to his colleagues that he thank the airline for attending a previous briefing on the flight control system, called MCAS, but otherwise decline to answer the pilot's first two questions and just refer the airline to training materials and previously issued guidance. Most of those on the email agreed.
Boeing's eventual response? "I can only address the current system and the Operations Manual Bulletin. The first two questions directly relate to the accident scenario; therefore, I will be unable to address them here." The Times adds that Boeing's chief pilot Jim Webb then "ended the email by stating that if airline officials had any additional questions about the bulletin and system, they should feel free to reach out....

"It is impossible to know whether any pilots with Ethiopian Arlines would have acted differently if Webb's reply had been more forthcoming. But Boeing's limited response to an airline seeking help highlights a missed opportunity to collaborate on safety and to pass along lessons Boeing had collected following the Lion Air jet's crash into the Java Sea on Oct. 29, 2018."

An anonymous reader quotes a report from InfoWorld: Select developers now are getting free access to JetBrains' WebStorm and Rider IDEs. The company on October 24 announced it has launched non-commercial licenses for its WebStorm JavaScript and TypeScript IDE and the Rider cross-platform .NET and game development IDE. As of now, developers using these IDEs for non-commercial purposes, such as open source project development or content creation, can use them for free. JetBrains views the move as expanding the availability of these IDEs to a broader swath of developer roles. More than two-thirds of developers code outside of work as a hobby and nearly 40% code for educational and learning purposes outside of work, the company said."Previously this year, JetBrains released other products under the same terms for non-commercial use, including RustRover, an IDE for Rust development, and Aqua, an IDE designed for test automation," notes InfoWorld. "JetBrains also provides community editions of IntelliJ and PyCharm, IDEs for Java and Python, respectively, which can be used to build proprietary and commercial software."

JetBrains has an FAQ section with additional details about the change.

Last month C dropped from 3rd to 4th in TIOBE's ranking of programming language popularity (which tries to calculate each language's share of search engine results). Java moved up into the #3 position in September, reports TechRepublic, which notes that by comparison October "saw relatively little change" — though percentages of search results increased slightly. "At number one, Python jumped from 20.17% in September to 21.9% in October. In second place, C++ rose from 10.75% in September to 11.6%. In third, Java ascended from 9.45% to 10.51%..."

Is there a larger trend? TIOBE CEO Paul Jansen writes that the need to harvest more data increases demand for fast data manipulation languages. But they also need to be easy to learn ("because the resource pool of skilled software engineers is drying up") and secure ("because of continuous cyber threats.") King of all, Python, is easy to learn and secure, but not fast. Hence, engineers are frantically looking for fast alternatives for Python. C++ is an obvious candidate, but it is considered "not secure" because of its explicit memory management. Rust is another candidate, although not easy to learn. Rust is, thanks to its emphasis on security and speed, making its way to the TIOBE index top 10 now. [It's #13 — up from #20 a year ago]

The cry for fast, data crunching languages is also visible elsewhere in the TIOBE index. The language Mojo [a faster superset of Python designed for accelerated hardware like GPUs]... enters the top 50 for the first time. The fact that this language is only 1 year old and already showing up, makes it a very promising language.
In the last 12 months three languages also fell from the top ten:

• PHP (dropping from #8 to #15)

• SQL (dropping from #9 to #11)

• Assembly language (dropping from #10 to #16)

Redmonk's latest programming language ranking (attempting to gauge "potential future adoption trends") has found evidence of "a landscape resistant to change." Outside of CSS moving down a spot and C++ moving up one, the Top 10 was unchanged. And even in the back half of the rankings, where languages tend to be less entrenched and movement is more common, only three languages moved at all... There are a few signs of languages following in TypeScript's footsteps and working their way up the path, both in the Top 20 and at the back end of the Top 100 as we'll discuss shortly, but they're the exception that proves the rule.

It's possible that we'll see more fluid usage of languages, and increased usage of code assistants would theoretically make that much more likely, but at this point it's a fairly static status quo. With that, some results of note:

- TypeScript (#6): technically TypeScript didn't move, as it was ranked sixth in our last run, but this is the first quarter in which is has been the sole occupant of that spot. CSS, in this case, dropped one place to seven leaving TypeScript just outside the Top 5. It will be interesting to see whether or not it has more momentum to expend or whether it's topped out for the time being.

- Kotlin (#14) / Scala (#14): both of these JVM-based languages jumped up a couple of spots — two spots in Scala's case and three for Kotlin. Scala's rise is notable because it had been on something of a downward trajectory from a one time high of 12th, and Kotlin's placement is a mild surprise because it had spent three consecutive runs not budging from 17, only to make the jump now. The tie here, meanwhile, is interesting because Scala's long history gives it an accretive advantage over Kotlin's more recent development, but in any case the combination is evidence of the continued staying power of the JVM.

- Objective C (#17): speaking of downward trajectories and the 17th placement on this list, Objective C's slide that began in mid-2018 continued and left the language with its lowest placement in these rankings to date at #17. That's still an enormously impressive achievement, of course, and there are dozens of languages that would trade their usage for Objective C's, but the direction of travel seems clear.

- Dart (#19) / Rust (#19): while once grouped with Kotlin as up and coming languages driven by differing incentives and trends, Dart and Rust have not been able to match the ascent of their counterpart with five straight quarters of no movement. That's not necessarily a negative; as with Objective C, these are still highly popular languages and communities, but it's worth questioning whether new momentum will arrive and from where, particularly because the communities are experiencing some friction in growing their usage.
It's important to remember Redmonk's methodology. "We extract language rankings from GitHub and Stack Overflow, and combine them for a ranking that attempts to reflect both code (GitHub) and discussion (Stack Overflow) traction. The idea is not to offer a statistically valid representation of current usage, but rather to correlate language discussion and usage in an effort to extract insights into potential future adoption trends."

Having said that, here's the current top ten in Redmonk's ranking:

1. JavaScript
2. Python
3. Java
4. PHP
5. C#
6. TypeScript
7. CSS
8. C++
9. Ruby
10. C

Their announcement also notes that at the other end of the list, the programming language Bicep "jumped eight spots to #78 and Zig 10 to #87. That progress pales next to Ballerina, however, which jumped from #80 to #61 this quarter. The general purpose language from WS02, thus, is added to the list of potential up and comers we're keeping an eye on."

Pundits aggregate results from multiple pollsters to minimize biases. So ZDNet tried the same approach, but aggregating rankings for the popularity of 19 top programming languages. Senior contributing editor David Gewirtz combined results from nine popularity rankings, including PYPL, the Tiobe index, GitHub's Usage 2023 summary report, and several rankings from Stack Overflow and from IEEE Spectrum.

The results? The top cluster contains Python, JavaScript, and Java. These are all very representative in the world of AI coding...

The next cluster contains the classic C-based languages [C++, C#, C], plus TypeScript (which is a more robust JavaScript variant) and SQL.

Below that are languages that were dominant a while ago, the web languages used to build and operate websites [HTML/CSS, PHP, Shell], followed by a range of other languages that are either growing in popularity (R, Dart) or dropping in popularity (Ruby). [Just above Ruby are Go, Rust, Kotlin, and Lua.]

Finally, at the bottom is Swift, Apple's language of choice. Objective-C, the previous language of Apple programming, has all but dropped off the list since Apple launched Swift. But while Apple boasts many developers, Swift is clearly not a standout in programmer interest... [T]here aren't a huge number of companies hiring Apple app developers, at least primarily. That's why Swift is relatively far down the chart. Objective-C is being replaced by Swift, and we can see it dropping right before our eyes.
"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."

theodp writes: Typos happen to the best of us, but spelling still counts when it comes to software development. So, it's kind of surprising to see that both Amazon CEO Andy Jassy and former AWS CEO Adam Selipsky failed to notice an embarrassing typo in a demo video they offered to their millions of followers on social media as evidence of Amazon Q AI's Java upgrade capabilities, which Amazon has been trumpeting for months in SEC filings, shareholder communication, and Amazon's latest earnings call with Wall Street analysts.

Just 37 seconds into the demo of the software that Amazon says saved it 4,500 developer-years of work and provided an additional $260M in annualized efficiency gains, Amazon Q kicks off the Java upgrade conversation by saying, "I can help you upgrade your Jave [sic] 8 and 11 codebases to Java 17." The embarrassing misspelling did prompt Twitter user @archo5dev to alert Jassy to the typo, but there's been no response yet from Jassy, who boasted that Amazon developers were unable to find any mistakes in Q's work in "79% of the auto-generated code reviews."

It's probably worth noting that both Jassy and Selipsky opted to showcase a drop-dead simple demo of Amazon Q Code Transformation rather than some of the lengthier and less-magical demos of the product.

Long-time Slashdot reader theodp shared this anecdote about Amazon's GenAI assistant for software development, Amazon Q: On Thursday, Amazon CEO Andy Jassy took to Twitter to boast that using Amazon Q to do Java upgrades has already saved Amazon from having to pay for 4,500 developer-years of work. ("Yes, that number is crazy but, real," writes Jassy). And Jassy says it also provided Amazon with an additional $260M in annualized efficiency gains from enhanced security and reduced infrastructure costs.

"Our developers shipped 79% of the auto-generated code reviews without any additional changes," Jassy explained. "This is a great example of how large-scale enterprises can gain significant efficiencies in foundational software hygiene work by leveraging Amazon Q."

Jassy — who FORTUNE reported had no formal training in computer science — also touted Amazon Q's Java upgrade prowess in his Letter to Shareholders earlier this year, as has Amazon in its recent SEC filings ("today, developers can save months using Q to move from older versions of Java to newer, more secure and capable ones; in the near future, Q will help developers transform their .net code as well"). Earlier this week, Business Insider reported on a leaked recording of a fireside chat in which AWS CEO Matt Garman predicted a paradigm shift in coding as a career in the foreseeable future with the prevalence of AI. According to Garman, "If you go forward 24 months from now, or some amount of time — I can't exactly predict where it is — it's possible that most developers are not coding."

The Japanese government has released details of an app that verifies the legitimacy of its troubled My Number Card -- a national identity document. From a report: Beginning in 2015, every resident of Japan was assigned a 12 digit My Number that paved the way for linking social security, taxation, disaster response and other government services to both the number itself and a smartcard. The plan was to banish bureaucracy and improve public service delivery -- but that didn't happen.

My Number Card ran afoul of data breaches, reports of malfunctioning card readers, and database snafus that linked cards to other citizens' bank accounts. Public trust in the scheme fell, and adoption stalled. Now, according to Japan's Digital Ministry, counterfeit cards are proliferating to help miscreant purchase goods -- particularly mobile phones -- under fake identities. Digital minister Taro Kono yesterday presented his solution to the counterfeits: a soon to be mandatory app that confirms the legitimacy of the card. The app uses the camera on a smartphone to read information printed on the card -- like date of birth and name. It compares those details to what it reads from info stored in the smartcard's resident chip, and confirms the data match without the user ever needing to enter their four-digit PIN.

An anonymous reader quotes a report from The Conversation, written by Michael W. Crowder, Professor of Chemistry and Biochemistry and Dean of the Graduate School at Miami University: For many people, the aroma of freshly brewed coffee is the start of a great day. But caffeine can cause headaches and jitters in others. That's why many people reach for a decaffeinated cup instead. I'm a chemistry professor who has taught lectures on why chemicals dissolve in some liquids but not in others. The processes of decaffeination offer great real-life examples of these chemistry concepts. Even the best decaffeination method, however, does not remove all of the caffeine -- about 7 milligrams of caffeine usually remain in an 8-ounce cup. Producers decaffeinating their coffee want to remove the caffeine while retaining all -- or at least most -- of the other chemical aroma and flavor compounds.

Decaffeination has a rich history, and now almost all coffee producers use one of three common methods. All these methods, which are also used to make decaffeinated tea, start with green, or unroasted, coffee beans that have been premoistened. Using roasted coffee beans would result in a coffee with a very different aroma and taste because the decaffeination steps would remove some flavor and odor compounds produced during roasting. Here's a summary of each method discussed by Dr. Crowder:

The Carbon Dioxide Method: Developed in the early 1970s, the carbon dioxide method uses high-pressure CO2 to extract caffeine from moistened coffee beans, resulting in coffee that retains most of its flavor. The caffeine-laden CO2 is then filtered out using water or activated carbon, removing 96% to 98% of the caffeine with minimal CO2 residue.

The Swiss Water Process: First used commercially in the early 1980s, the Swiss water method uses hot water and activated charcoal filters to decaffeinate coffee, preserving most of its natural flavor. This chemical-free approach removes 94% to 96% of the caffeine by soaking the beans repeatedly until the desired caffeine level is achieved.

Solvent-Based Methods: Originating in the early 1900s, solvent-based methods use organic solvents like ethyl acetate and methylene chloride to extract caffeine from green coffee beans. These methods remove 96% to 97% of the caffeine through either direct soaking in solvent or indirect treatment of water containing caffeine, followed by steaming and roasting to ensure safety and flavor retention.

"It's chemically impossible to dissolve out only the caffeine without also dissolving out other chemical compounds in the beans, so decaffeination inevitably removes some other compounds that contribute to the aroma and flavor of your cup of coffee," writes Dr. Crowder in closing. "But some techniques, like the Swiss water process and the indirect solvent method, have steps that may reintroduce some of these extracted compounds. These approaches probably can't return all the extra compounds back to the beans, but they may add some of the flavor compounds back."

Lindsay Clark reports via The Register: Only 14 percent of Oracle Java subscribers plan to stay on Big Red's runtime environment, according to a study following the introduction of an employee-based subscription model. At the same time, 36 percent of the 663 Java users questioned said they had already moved to the employee-based pricing model introduced in January 2023. Shortly after the new model was implemented, experts warned that it would create a significant price hike for users adopting it. By July, global tech research company Gartner was forecasting that those on the new subscription package would face between two and five times the costs compared with the previous usage-based model.

As such, among the 86 percent of respondents using Oracle Java SE who are currently moving or plan to move all or some of their Java applications off Oracle environments, 53 percent said the Oracle environment was too expensive, according to the study carried out by independent market research firm Dimensional Research. Forty-seven percent said the reason for moving was a preference for open source, and 38 percent said it was because of uncertainty created by ongoing changes in pricing, licensing, and support. [...]

To support OpenJDK applications in production, 46 percent chose a paid-for platform such as Belsoft Liberica, IBM Semeru, or Azul Platform Core; 45 percent chose a free supported platform such as Amazon Corretto or Microsoft Build of OpenJDK; and 37 percent chose a free, unsupported platform. Of the users who have already moved to OpenJDK, 25 percent said Oracle had been significantly more expensive, while 41 percent said Big Red's licensing had made it somewhat more expensive than the alternative. The survey found three-quarters of Java migrations were completed within a year, 23 percent within three months.

An anonymous reader shared this report from InfoWorld: Rust has leaped to its highest position ever in the monthly Tiobe index of language popularity, scaling to the 13th spot this month, with placement in the top 10 anticipated in an upcoming edition. Previously, Rust has never gone higher than 17th place in the Tiobe Programming Index. Tiobe CEO Paul Jansen attributed Rust's ascent in the just-released July index to a February 2024 U.S. White House report recommending Rust over C/C+ for safety reasons. He also credited the growing community and ecosystem support for the language. "Rust is finally moving up."
The article adds that these rankings are based on "the number of skilled engineers worldwide, courses, and third-party vendors pertaining to languages, examining websites such as Google, Amazon, Wikipedia, and more than 20 others to determine the monthly numbers."

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

Interestingly, Rust has just moved into the top ten on the rival rankings from the rival Pypl Popularity of Programming Language index (which according to the article "assesses how often languages are searched on in Google.")

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

IEEE Spectrum (the IEEE's official publication) asks the question. "How does an AI code generator compare to a human programmer?" A study published in the June issue of IEEE Transactions on Software Engineering evaluated the code produced by OpenAI's ChatGPT in terms of functionality, complexity and security. The results show that ChatGPT has an extremely broad range of success when it comes to producing functional code — with a success rate ranging from anywhere as poor as 0.66 percent and as good as 89 percent — depending on the difficulty of the task, the programming language, and a number of other factors. While in some cases the AI generator could produce better code than humans, the analysis also reveals some security concerns with AI-generated code.
The study tested GPT-3.5 on 728 coding problems from the LeetCode testing platform — and in five programming languages: C, C++, Java, JavaScript, and Python. The results? Overall, ChatGPT was fairly good at solving problems in the different coding languages — but especially when attempting to solve coding problems that existed on LeetCode before 2021. For instance, it was able to produce functional code for easy, medium, and hard problems with success rates of about 89, 71, and 40 percent, respectively. "However, when it comes to the algorithm problems after 2021, ChatGPT's ability to generate functionally correct code is affected. It sometimes fails to understand the meaning of questions, even for easy level problems," said Yutian Tang, a lecturer at the University of Glasgow. For example, ChatGPT's ability to produce functional code for "easy" coding problems dropped from 89 percent to 52 percent after 2021. And its ability to generate functional code for "hard" problems dropped from 40 percent to 0.66 percent after this time as well...

The researchers also explored the ability of ChatGPT to fix its own coding errors after receiving feedback from LeetCode. They randomly selected 50 coding scenarios where ChatGPT initially generated incorrect coding, either because it didn't understand the content or problem at hand. While ChatGPT was good at fixing compiling errors, it generally was not good at correcting its own mistakes... The researchers also found that ChatGPT-generated code did have a fair amount of vulnerabilities, such as a missing null test, but many of these were easily fixable.
"Interestingly, ChatGPT is able to generate code with smaller runtime and memory overheads than at least 50 percent of human solutions to the same LeetCode problems..."

An anonymous reader quotes a report from Ars Technica: More than 384,000 websites are linking to a site that was caught last week performing a supply-chain attack that redirected visitors to malicious sites, researchers said. For years, the JavaScript code, hosted at polyfill[.]com, was a legitimate open source project that allowed older browsers to handle advanced functions that weren't natively supported. By linking to cdn.polyfill[.]io, websites could ensure that devices using legacy browsers could render content in newer formats. The free service was popular among websites because all they had to do was embed the link in their sites. The code hosted on the polyfill site did the rest. In February, China-based company Funnull acquired the domain and the GitHub account that hosted the JavaScript code. On June 25, researchers from security firm Sansec reported that code hosted on the polyfill domain had been changed to redirect users to adult- and gambling-themed websites. The code was deliberately designed to mask the redirections by performing them only at certain times of the day and only against visitors who met specific criteria.

The revelation prompted industry-wide calls to take action. Two days after the Sansec report was published, domain registrar Namecheap suspended the domain, a move that effectively prevented the malicious code from running on visitor devices. Even then, content delivery networks such as Cloudflare began automatically replacing pollyfill links with domains leading to safe mirror sites. Google blocked ads for sites embedding the Polyfill[.]io domain. The website blocker uBlock Origin added the domain to its filter list. And Andrew Betts, the original creator of Polyfill.io, urged website owners to remove links to the library immediately. As of Tuesday, exactly one week after malicious behavior came to light, 384,773 sites continued to link to the site, according to researchers from security firm Censys. Some of the sites were associated with mainstream companies including Hulu, Mercedes-Benz, and Warner Bros. and the federal government. The findings underscore the power of supply-chain attacks, which can spread malware to thousands or millions of people simply by infecting a common source they all rely on.

theodp writes: As with last year," tweeted College Board's AP Program Chief Trevor Packer, "the most challenging free-response question on this year's AP Computer Science A exam was Q4 on 2D Array." While it takes six pages of the AP CS A exam document [PDF] to ask question 4 (of 4), the ask of students essentially boils down to using Java to move from the current location in a 2-D grid to either immediately below or to the right of that location based on which neighbor contains the lesser value, and adding the value at that location to a total (suggested Java solution, alternative Excel VBA solution). Much like rules of the children's game Pop-O-Matic Trouble, moves are subject to the constraint that you cannot move to the right or ahead if it takes you to an invalid position (beyond the grid dimensions).

Ironically, many of the AP CS A students who struggled with the grid coding problem were likely exposed by their schools from kindergarten on to more than a decade's worth of annual Hour of Code tutorials that focused on the concepts of using code to move about in 2-D grids. The move-up-down-left-right tutorials promoted by schools came from tech-backed nonprofit Code.org and its tech giant partners and have been taught over the years by the likes of Bill Gates, Mark Zuckerberg, and President Obama, as well as characters from Star Wars, Disney Princess movies, and Microsoft Minecraft.

The news of American high school students struggling again with fairly straightforward coding problems after a year-long course of instruction comes not only as tech companies and tech-tied nonprofits lobby state lawmakers to pass bills making CS a high school graduation requirement in the US, but also as a new report from King's College urges lawmakers and educators to address a stark decline in the number of UK students studying computing at secondary school, which is blamed on the replacement of more approachable ICT (Information and Communications Technology) courses with more rigorous computer science courses in 2013 (a switch pushed by Google and Microsoft), which it notes students have perceived as too difficult and avoided taking.

Last month TIOBE announced its estimate that the four most popular programming languages were:

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

But this month C++ "overtook" C for the first time, TIOBE announced, becoming (according to the same methodology) the #2 most popular programming language, with C dropping to #3. " C++ has never been that high in the TIOBE index," says TIOBE Software CEO Paul Jansen in the announcement, "whereas C has never been that low."

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...

Long-time Slashdot reader theodp writes: "Great news, Louisiana!" tech-backed Code.org exclaimed Wednesday in celebratory LinkedIn, Facebook, and Twitter posts. Louisiana is "officially the 10th state to make computer science a [high school] graduation requirement. Huge thanks to Governor Jeff Landry for signing the bill and to our legislative champions, Rep. Jason Hughes and Sen. Thomas Pressly, for making it happen! This means every Louisiana student gets a chance to learn coding and other tech skills that are super important these days. These skills can help them solve problems, think critically, and open doors to awesome careers!"

Representative Hughes, the sponsor of HB264 — which calls for each public high school student to successfully complete a one credit CS course as a requirement for graduation and also permits students to take two units of CS instead of studying a Foreign Language — tweeted back: "HUGE thanks @codeorg for their partnership in this effort every step of the way! Couldn't have done it without [Code.org Senior Director of State Government Affairs] Anthony [Owen] and the Code.org team!"

Code.org also on Wednesday announced the release of its 2023 Impact Report, which touted its efforts "to include a requirement for every student to take computer science to receive a high school diploma." Since its 2013 launch, Code.org reports it's spent $219.8 million to push coding into K-12 classrooms, including $19 million on Government Affairs (Achievements: "Policies changed in 50 states. More than $343M in state budgets allocated to computer science.").

In Code.org by the Numbers, the nonprofit boasts that 254,683 students started Code.org's AP CS Principles course in the academic year (2025 Goal: 400K), while 21,425 have started Code.org's new Amazon-bankrolled AP CS A course. Estimates peg U.S. public high school enrollment at 15.5M students, annual K-12 public school spending at $16,080 per pupil, and an annual high school student course load at 6-8 credits...