"I'm still teaching at Princeton," 83-year-old Brian Kernighan recently told an audience at New Jersey's InfoAge Science and History Museums. And last month the video was uploaded to YouTube, a new article points out, "showing that his talk ended with a unique question-and-answer session that turned almost historic..." "Do you think there's any sort of merit to Rust replacing C?" one audience member asked... "Or is this just a huge hype bubble that's waiting to die down...?" '"I have written only one Rust program, so you should take all of this with a giant grain of salt," he said. "And I found it a — pain... I just couldn't grok the mechanisms that were required to do memory safety, in a program where memory wasn't even an issue!" Speaking of Rust, Kernighan said "The support mechanism that went with it — this notion of crates and barrels and things like that — was just incomprehensibly big and slow. And the compiler was slow, the code that came out was slow..." All in all, Kernighan had had a bad experience. "When I tried to figure out what was going on, the language had changed since the last time somebody had posted a description! And so it took days to write a program which in other languages would take maybe five minutes..." It was his one and only experience with the language, so Kernighan acknowledged that when it comes to Rust "I'm probably unduly cynical. "But I'm — I don't think it's gonna replace C right away, anyway." Kernighan was also asked about NixOS and HolyC — but his formative experiences remain rooted in Bell Labs starts in the 1970s, where he remembers it was "great fun to hang out with these people." And he acknowledged that the descendants of Unix now power nearly every cellphone. "I find it intriguing... And I also find it kind of irritating that underneath there is a system that I could do things with — but I can't get at it!" Kernighan answered questions from Slashdot readers in 2009 and again in 2015...

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Thursday saw the release of Rust 1.89.0 But this week the Rust Foundation also released its second comprehensive annual technology report. A Rust Foundation announcement shares some highlights: - Trusted Publishing [GitHub Actions authentication using cryptographically signed tokens] fully launched on crates.io, enhancing supply chain security and streamlining workflows for maintainers. - Major progress on crate signing infrastructure using The Update Framework (TUF), including three full repository implementations and stakeholder consensus. - Integration of the Ferrocene Language Specification (FLS) into the Rust Project, marking a critical step toward a formal Rust language specification [and "laying the groundwork for broader safety certification and formal tooling."] - 75% reduction in CI infrastructure costs while maintaining contributor workflow stability. ["All Rust repositories are now managed through Infrastructure-as-Code, improving maintainability and security."] - Expansion of the Safety-Critical Rust Consortium, with multiple international meetings and advances on coding guidelines aligned with safety standards like MISRA. ["The consortium is developing practical coding guidelines, aligned tooling, and reference materials to support regulated industries — including automotive, aerospace, and medical devices — adopting Rust."] - Direct engagement with ISO C++ standards bodies and collaborative Rust-C++ exploration... The Foundation finalized its strategic roadmap, participated in ISO WG21 meetings, and initiated cross-language tooling and documentation planning. These efforts aim to unlock Rust adoption across legacy C++ environments without sacrificing safety. The Rust Foundation also acknowledges continued funding from OpenSSF's Alpha-Omega Project and "generous infrastructure donations from organizations like AWS, GitHub, and Mullvad VPN" to the Foundation's Security Initiative, which enabled advances like including GitHub Secret Scanning and automated incident response to "Trusted Publishing" and the integration of vulnerability-surfacing capabilities into crates.io. There was another announcement this week. In November AWS and the Rust Foundation crowdsourced "an effort to verify the Rust standard library" — and it's now resulted in a new formal verification tool called "Efficient SMT-based Context-Bounded Model Checker" (or ESBMCESBMC) This winning contribution adds ESBMC — a state-of-the-art bounded model checker — to the suite of tools used to analyze and verify Rust's standard library. By integrating through Goto-Transcoder, they enabled ESBMC to operate seamlessly in the Rust verification workflow, significantly expanding the scope and flexibility of verification efforts... This achievement builds on years of ongoing collaboration across the Rust and formal verification communities... The collaboration has since expanded. In addition to verifying the Rust standard library, the team is exploring the use of formal methods to validate automated C-to-Rust translations, with support from AWS. This direction, highlighted by AWS Senior Principal Scientist Baris Coskun and celebrated by the ESBMC team in a recent LinkedIn post, represents an exciting new frontier for Rust safety and verification tooling.

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Last month Microsoft pledged $4 billion (in cash and AI/cloud technology) to "advance" AI education in K-12 schools, community and technical colleges, and nonprofits (according to a blog post by Microsoft President Brad Smith). But in the launch event video, Smith also says it's time to "switch hats" from coding to AI, adding that "the last 12 years have been about the Hour of Code, but the future involves the Hour of AI." Long-time Slashdot reader theodp writes: This sets the stage for Code.org CEO Hadi Partovi's announcement that his tech-backed nonprofit's [annual educational event] Hour of Code is being renamed to the Hour of AI... Explaining the pivot, Partovi says: "Computer science for the last 50 years has had a focal point around coding that's been — sort of like you learn computer science so that you create code. There's other things you learn, like data science and algorithms and cybersecurity, but the focal point has been coding. "And we're now in a world where the focal point of computer science is shifting to AI... We all know that AI can write much of the code. You don't need to worry about where did the semicolons go, or did I close the parentheses or whatnot. The busy work of computer science is going to be done by the computer itself. "The creativity, the thinking, the systems design, the engineering, the algorithm planning, the security concerns, privacy concerns, ethical concerns — those parts of computer science are going to be what remains with a focal point around AI. And what's going to be important is to make sure in education we give students the tools so they don't just become passive users of AI, but so that they learn how AI works." Speaking to Microsoft's Smith, Partovi vows to redouble the nonprofit's policy work to "make this [AI literacy] a high school graduation requirement so that no student graduates school without at least a basic understanding of what's going to be part of the new liberal arts background [...] As you showed with your hat, we are renaming the Hour of Code to an Hour of AI."

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Started in 1984, it's been described as the internet's longest-running contest. And yesterday 2025's International Obfuscated C Code Contest concluded — with 23 new winners announced in a special four-and-a-half-hour livestreamed ceremony! Programmers submitted their funniest programs showcasing C's unusual/obscure subtleties while having some fun. (And demonstrating the importance of clarity and style by setting some very bad examples...) Among this year's winners were an OpenRISC 32-bit CPU emulator, a virtual machine capable of running Doom, and some kind of salmon recipe that makes clever use of C's U"string" literal prefix... But yes, every entry's source code is ridiculously obfuscated. ("Before you set off on your adventure to decode this program's logic, make sure you have enough food, ammo, clothes, oxen, and programming supplies," read the judge's remarks on the winner of this year's "diabolical logistics" prize. "You'll be driving for 2170 miles through a wild wilderness inspired by Oregon Trail...") And one entrant also struggled mightily in adapting a rough port of their program's old Atari 2600 version, but was never gonna give it up... Thanks to long-time Slashdot reader achowe for bringing the news (who has submitted winning entries in four different decades, starting in 1991 and continuing through 2024)... Including a 2004 award for the best abuse of the contest's guidelines. ("We are not exactly sure how many organisations will be upset with this entry, but we are considering starting an IOCCC standards body just to reign in the likes of Mr Howe....")

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America's nonprofit College Board lets high school students take college-level classes — including a computer programming course that culminates with a 90-minute test. But students did better on questions about If-Then statements than they did on questions about arrays, according to the head of the program. Long-time Slashdot reader theodp explains: Students exhibited "strong performance on primitive types, Boolean expressions, and If statements; 44% of students earned 7-8 of these 8 points," says program head Trevor Packard. But students were challenged by "questions on Arrays, ArrayLists, and 2D Arrays; 17% of students earned 11-12 of these 12 points." "The most challenging AP Computer Science A free-response question was #4, the 2D array number puzzle; 19% of students earned 8-9 of the 9 points possible." You can see that question here. ("You will write the constructor and one method of the SumOrSameGame class... Array elements are initialized with random integers between 1 and 9, inclusive, each with an equal chance of being assigned to each element of puzzle...") Although to be fair, it was the last question on the test — appearing on page 16 — so maybe some students just didn't get to it. theodp shares a sample Java solution and one in Excel VBA solution (which includes a visual presentation). There's tests in 38 subjects — but CS and Statistics are the subjects where the highest number of students earned the test's lowest-possible score (1 out of 5). That end of the graph also includes notoriously difficult subjects like Latin, Japanese Language, and Physics. There's also a table showing scores for the last 23 years, with fewer than 67% of students achieving a passing grade (3+) for the first 11 years. But in 2013 and 2017, more than 67% of students achieved that passsing grade, and the percentage has stayed above that line ever since (except for 2021), vascillating between 67% and 70.4%. 2018: 67.8% 2019: 69.6% 2020: 70.4% 2021: 65.1% 2022: 67.6% 2023: 68.0% 2024: 67.2% 2025: 67.0%

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It's a cultural milestone. Fiverr just released an ad mocking vibe coding. The video features what its description calls a "clueless entrepreneur" building an app to tell if an avocado is ripe — who soon ends up blissfully singing with an avocado to the tune of the cheesy 1987 song "Nothing's Gonna Stop Us Now." The avocado sings joyously of "a new app on the rise in a no-code world that's too good to be true" (rhyming that with "So close. Just not tested through...") "Let them say we're crazy. I don't care about bugs!" the entrepreneur sings back. "Built you in a minute, now I'm so high off this buzz..." But despite her singing to the overripe avocado that "I don't need a backend if I've got the spark!" and that they can "build this app together, vibe-coding forever. Nothing's going to stop us now!" — the build suddenly fails. (And it turns out that avocado really was overripe...) Fiverr then suggests viewers instead hire one of their experts for building their apps... The art/design site Creative Bloq acknowledges Fiverr "flip-flopping between scepticism and pro-AI marketing." (They point out a Fiverr ad last November had ended with the tagline "Nobody cares that you use AI! They care about the results — for the best ones higher Fiverr experts who've mastered every digital skill including AI.") But the site calls this new ad "a step in the right direction towards mindful AI usage." Just like an avocado that looks perfect on the outside, once you inspect the insides, AI-generated code can be deceptively unripe. Fiverr might be feeling the impact of vibecoding themselves. The freelancing web site saw the company's share price fall over 14% this week, with one Yahoo! Finance site saying this week's quarterly results revealed Fiverr's active buyers dropped 10.9% compared to last year — a decrease of 3.4 million buyers which "overshadowed a 9.8% increase in spending per buyer." Even when issuing a buy recommendation, Seeking Alpha called it "a short-term rebound play, as the company faces longer-term risks from AI and active buyer churn."

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Developers are growing increasingly frustrated with AI coding tools that produce deceptively flawed solutions, according to Stack Overflow's latest survey of over 49,000 programmers worldwide. The 2025 survey exposes a widening gap between AI adoption and satisfaction: while 84% of developers now use or plan to use AI tools, their trust has cratered. Only 33% trust AI accuracy today, down from 43% last year. The core problem isn't broken code that developers can easily spot and discard. Instead, two-thirds report wrestling with AI solutions that appear correct but contain subtle errors requiring significant debugging time. Nearly half say fixing AI-generated code takes longer than expected, undermining the productivity gains these tools promise to deliver.

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BrianFagioli writes: AI might be the future of software development, but a new report suggests we're not quite ready to take our hands off the wheel. Veracode has released its 2025 GenAI Code Security Report, and the findings are pretty alarming. Out of 80 carefully designed coding tasks completed by over 100 large language models, nearly 45 percent of the AI-generated code contained security flaws. That's not a small number. These are not minor bugs, either. We're talking about real vulnerabilities, with many falling under the OWASP Top 10, which highlights the most dangerous issues in modern web applications. The report found that when AI was given the option to write secure or insecure code, it picked the wrong path nearly half the time.

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Anthropic will implement weekly rate limits for Claude subscribers starting August 28 to address users running its Claude Code AI programming tool continuously around the clock and to prevent account sharing violations. The new restrictions will affect Pro subscribers paying $20 monthly and Max plan subscribers paying $100 and $200 monthly, though Anthropic estimates fewer than 5% of current users will be impacted based on existing usage patterns. Pro users will receive 40 to 80 hours of Sonnet 4 access through Claude Code weekly, while $100 Max subscribers get 140 to 280 hours of Sonnet 4 plus 15 to 35 hours of Opus 4. The $200 Max plan provides 240 to 480 hours of Sonnet 4 and 24 to 40 hours of Opus 4. Claude Code has experienced at least seven outages in the past month due to unprecedented demand.

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Surge CEO Edwin Chen says AI is creating "100x engineers" who can outperform traditional software developers by orders of magnitude. Chen argued that AI coding tools multiply the productivity gains already seen in Silicon Valley's "10x engineers," who can produce ten times the work of their colleagues through faster coding, harder work, and fewer distractions. Chen said AI efficiencies compound these factors to reach 100x productivity levels. The CEO, whose company reached $1 billion in revenue without venture capital funding, believes this could enable billion-dollar single-person companies, extending beyond the $10 million single-person startups that already exist.

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AI coding service Replit deleted a user's production database and fabricated data to cover up bugs, according to SaaStr founder Jason Lemkin. Lemkin documented his experience on social media after Replit ignored his explicit instructions not to make code changes without permission. The database deletion eliminated 1,206 executive records representing months of authentic SaaStr data curation. Replit initially told Lemkin the database could not be restored, claiming it had "destroyed all database versions," but later discovered rollback functionality did work. Replit said it made "a catastrophic error of judgement" and rated the severity of its actions as 95 out of 100. The service also created a 4,000-record database filled with fictional people and repeatedly violated code freeze requests. Lemkin had initially praised Replit after building a prototype in hours, spending $607.70 in additional charges beyond his $25 monthly plan. He concluded the service isn't ready for commercial use by non-technical users.

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Robinhood CEO Vlad Tenev has said that the majority of his company's new code is written by AI, with "close to 100%" of engineers using AI code editors. Speaking on the 20VC podcast, Tenev estimated around 50% of new code at the trading platform is AI-generated. Tenev said the 50% figure is imprecise due to advanced "agentic" code editors that have made it difficult to distinguish human-written from AI-generated code. The company has progressed from GitHub Copilot to Cursor and now Windsurf, where "nearly all of the code is written by AI," he said. Tenev estimated only a "minority" of new code at Robinhood is written by humans.

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An anonymous reader shared this report from InfoWorld: Tiobe CEO Paul Jansen says Ada, a system programming language whose initial development dates back to the late 1970s, could outlast similarly aged languages like Visual Basic, Perl, and Fortran in the language popularity race. In comments on this month's Tiobe language popularity index, posted July 9, Jansen said the index has not seen much change among leading languages such as Python, C#, and Java over the past two years. But there is more movement among older languages such as Visual Basic, SQL, Fortran, Ada, Perl, and Delphi, said Jansen. Every time one of these languages is expected to stay in the top 10, it is replaced by another language, he said. Even more remarkably, newer languages have yet to rise above them. "Where are Rust, Kotlin, Dart, and Julia? Apparently, established languages are hot." "Which one will win? Honestly, this is very hard to tell," Jansen writes, "but I would put my bets on Ada. With the ever-stronger demands on security, Ada is, as a system programming language in the safety-critical domain, likely the best survivor." Perhaps proving his point, one year ago, Ada was ranked #24 — but on this month's index it ranks #9. (Whereas the eight languages above it all remain in the exact same positions they held a year ago...) PythonC++CJavaC#JavaScriptGoVisual BasicAdaDelphi/Object Pascal

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An anonymous reader quotes a report from Reuters: Contrary to popular belief, using cutting-edge artificial intelligence tools slowed down experienced software developers when they were working in codebases familiar to them, rather than supercharging their work, a new study found. AI research nonprofit METR conducted the in-depth study on a group of seasoned developers earlier this year while they used Cursor, a popular AI coding assistant, to help them complete tasks in open-source projects they were familiar with. Before the study, the open-source developers believed using AI would speed them up, estimating it would decrease task completion time by 24%. Even after completing the tasks with AI, the developers believed that they had decreased task times by 20%. But the study found that using AI did the opposite: it increased task completion time by 19%. The study's lead authors, Joel Becker and Nate Rush, said they were shocked by the results: prior to the study, Rush had written down that he expected "a 2x speed up, somewhat obviously." [...] The slowdown stemmed from developers needing to spend time going over and correcting what the AI models suggested. "When we watched the videos, we found that the AIs made some suggestions about their work, and the suggestions were often directionally correct, but not exactly what's needed," Becker said. The authors cautioned that they do not expect the slowdown to apply in other scenarios, such as for junior engineers or engineers working in codebases they aren't familiar with. Still, the majority of the study's participants, as well as the study's authors, continue to use Cursor today. The authors believe it is because AI makes the development experience easier, and in turn, more pleasant, akin to editing an essay instead of staring at a blank page. "Developers have goals other than completing the task as soon as possible," Becker said. "So they're going with this less effortful route."

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The University of Washington's Paul G. Allen School of Computer Science & Engineering is overhauling its approach to computer science education as AI reshapes the tech industry. Director Magdalena Balazinska has declared that "coding, or the translation of a precise design into software instructions, is dead" because AI can now handle that work. The Pacific Northwest's premier tech program now allows students to use GPT tools in assignments, requiring them to cite AI as a collaborator just as they would credit input from a fellow student. The school is considering "coordinated changes to our curriculum" after encouraging professors to experiment with AI integration.

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"Apple quietly dropped a new AI model on Hugging Face with an interesting twist," writes 9to5Mac. "Instead of writing code like traditional LLMs generate text (left to right, top to bottom), it can also write out of order, and improve multiple chunks at once." "The result is faster code generation, at a performance that rivals top open-source coding models." Traditionally, most LLMs have been autoregressive. This means that when you ask them something, they process your entire question, predict the first token of the answer, reprocess the entire question with the first token, predict the second token, and so on. This makes them generate text like most of us read: left to right, top to bottom... An alternative to autoregressive models is diffusion models, which have been more often used by image models like Stable Diffusion. In a nutshell, the model starts with a fuzzy, noisy image, and it iteratively removes the noise while keeping the user request in mind, steering it towards something that looks more and more like what the user requested... Lately, some large language models have looked to the diffusion architecture to generate text, and the results have been pretty promising... This behavior is especially useful for programming, where global structure matters more than linear token prediction... [Apple] released an open-source model called DiffuCode-7B-cpGRPO, that builds on top of a paper called DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation, released just last month... [W]ith an extra training step called coupled-GRPO, it learned to generate higher-quality code with fewer passes. The result? Code that's faster to generate, globally coherent, and competitive with some of the best open-source programming models out there. Even more interestingly, Apple's model is built on top of Qwen2.5-7B, an open-source foundation model from Alibaba. Alibaba first fine-tuned that model for better code generation (as Qwen2.5-Coder-7B), then Apple took it and made its own adjustments. They turned it into a new model with a diffusion-based decoder, as described in the DiffuCoder paper, and then adjusted it again to better follow instructions. Once that was done, they trained yet another version of it using more than 20,000 carefully picked coding examples. "Although DiffuCoder did better than many diffusion-based coding models (and that was before the 4.4% bump from DiffuCoder-7B-cpGRPO), it still doesn't quite reach the level of GPT-4 or Gemini Diffusion..." the article points out. But "the bigger point is this: little by little, Apple has been laying the groundwork for its generative AI efforts with some pretty interesting and novel ideas."

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"A computer science degree used to be a golden ticket to the promised land of jobs," a college senior tells the New York Times. But "That's no longer the case." The article notes that in the last three years there's been a 65% drop from companies seeking workers with two years of experience or less (according to an analysis by technology research/education organization CompTIA), with tech companies "relying more on AI for some aspects of coding, eliminating some entry-level work." So what do college professors teach when AI "is coming fastest and most forcefully to computer science"? Computer science programs at universities across the country are now scrambling to understand the implications of the technological transformation, grappling with what to keep teaching in the AI era. Ideas range from less emphasis on mastering programming languages to focusing on hybrid courses designed to inject computing into every profession, as educators ponder what the tech jobs of the future will look like in an AI economy... Some educators now believe the discipline could broaden to become more like a liberal arts degree, with a greater emphasis on critical thinking and communication skills. The National Science Foundation is funding a program, Level Up AI, to bring together university and community college educators and researchers to move toward a shared vision of the essentials of AI education. The 18-month project, run by the Computing Research Association, a research and education nonprofit, in partnership with New Mexico State University, is organising conferences and roundtables and producing white papers to share resources and best practices. The NSF-backed initiative was created because of "a sense of urgency that we need a lot more computing students — and more people — who know about AI in the workforce," said Mary Lou Maher, a computer scientist and a director of the Computing Research Association. The future of computer science education, Maher said, is likely to focus less on coding and more on computational thinking and AI literacy. Computational thinking involves breaking down problems into smaller tasks, developing step-by-step solutions and using data to reach evidence-based conclusions. AI literacy is an understanding — at varying depths for students at different levels — of how AI works, how to use it responsibly and how it is affecting society. Nurturing informed skepticism, she said, should be a goal. The article raises other possibilities. Experts also suggest the possibility of "a burst of technology democratization as chatbot-style tools are used by people in fields from medicine to marketing to create their own programs, tailored for their industry, fed by industry-specific data sets." Stanford CS professor Alex Aiken even argues that "The growth in software engineering jobs may decline, but the total number of people involved in programming will increase." Last year, Carnegie Mellon actually endorsed using AI for its introductory CS courses. The dean of the school's undergraduate programs believes that coursework "should include instruction in the traditional basics of computing and AI principles, followed by plenty of hands-on experience designing software using the new tools."

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"Microsoft has released the source code for the GitHub Copilot Chat extension for VS Code under the MIT license," reports BleepingComputer. This provides the community access to the full implementation of the chat-based coding assistant, including the implementation of "agent mode," what contextual data is sent to large language models (LLMs), and the design of system prompts. The GitHub repository hosting the code also details telemetry collection mechanisms, addressing long-standing questions about data transparency in AI-assisted coding tools... As the VS Code team explained previously, shifts in AI tooling landscape like the rapid growth of the open-source AI ecosystem and a more level playing field for all have reduced the need for secrecy around prompt engineering and UI design. At the same time, increased targeting of development tools by malicious actors has increased the need for crowdsourcing contributions to rapidly pinpoint problems and develop effective fixes. Essentially, openness is now considered superior from a security perspective. "If you've been hesitant to adopt AI tools because you don't trust the black box behind them, this move opensources-github-copilot-chat-vscode/offers something rare these days: transparency," writes Slashdot reader BrianFagioli" Now that the extension is open source, developers can audit how agent mode actually works. You can also dig into how it manages your data, customize its behavior, or build entirely new tools on top of it. This could be especially useful in enterprise environments where compliance and control are non negotiable. It is worth pointing out that the backend models powering Copilot remain closed source. So no, you won't be able to self host the whole experience or train your own Copilot. But everything running locally in VS Code is now fair game. Microsoft says it is planning to eventually merge inline code completions into the same open source package too, which would make Copilot Chat the new hub for both chat and suggestions.

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