Jit Tech News 14

In this edition of Jit Tech News, our experts have found interesting articles for you:?

- about software flaws that the White House deems to be a threat to national security.?

- which will provide why code coverage is important;?

- about Small Language Models;?

- which will provide the necessary knowledge of Unicode.?

?

? Are you interested in any of the articles?

? Share this issue of JTN on your profile.?

Don't wait, read on!???

1. Mastering Test Automation and Code Coverage: Keys to Software Development Quality - Pawel Dolny

The article "Test Automation and Code Coverage" on web.dev discusses the importance of test automation and code coverage in software development. It begins by explaining that test automation is crucial for maintaining high-quality software, as it allows developers to run tests frequently and efficiently.

The article highlights that code coverage is a metric that measures the percentage of code executed during testing, indicating how much of the codebase is tested. It emphasizes that while high code coverage is beneficial, it should not be the sole indicator of testing effectiveness, as it does not guarantee the quality of tests.

The article also discusses the use of tools like Istanbul for JavaScript code coverage, which can help developers identify untested parts of their code. Furthermore, it suggests that developers should aim for a balance between code coverage and meaningful test cases, focusing on testing critical paths and edge cases.

Lastly, the article encourages developers to use test automation and code coverage as part of a broader testing strategy, complementing manual testing and other quality assurance practices.?

? To read more and dive deeper into the topic, visit the article at?https://web.dev/articles/ta-code-coverage .

2. The Significance of Unicode in Software Development: Insights from Nicolai Tonsky's Guide?

In 2024, the importance of understanding Unicode remains as crucial as ever, given its foundational role in software development. Nicolai Tonsky's article "The Absolute Minimum Every Software Developer Must Know About Unicode in 2023 (Still No Excuses!)" provides a comprehensive guide to Unicode, emphasizing its significance beyond emojis. It highlights the prevalence of UTF-8 as the dominant encoding for data transfer and storage, while UTF-16 is still utilized in certain in-memory representations.

The article also delves into the concept of extended grapheme clusters, crucial for semantic operations on strings, and the necessity of employing Unicode libraries for accurate handling of Unicode data. The knowledge and understanding of Unicode are essential for developers to ensure their software can accurately handle and display text across different languages and scripts.?

? To explore the intricacies of Unicode and its implications for software development further, it’s recommended to read the full article at https://tonsky.me/blog/unicode/ .

3. In Rust we trust, shall we? – Oskar Maksymiuk

Have you heard that the US White House has urged programmers to utilize memory-safe programming languages when developing new software? The directive, detailed in a technical report available at https://www.whitehouse.gov/wp-content/uploads/2024/02/Final-ONCD-Technical-Report.pdf , underscores the importance of mitigating common software flaws to safeguard against potential national security risks.?

Throughout my career, I’ve encountered numerous examples of memory leaks in mission-critical applications. These leaks have the potential to disrupt entire systems and lead to significant financial losses. However, I never imagined that such common software flaws could escalate to the point of being addressed by the White House as a national security risk!

If you’re as surprised as I am, you may find it worthwhile to read StackOverflow's article, which sheds further light on why memory leaks are one of the most common causes of software exploits. You can access the article here: https://stackoverflow.blog/2024/03/04/in-rust-we-trust-white-house-office-urges-memory-safety .

In Rust we trust, shall we????

4. Attention, programmers! Let it be known: Devin has arrived!?

If you ever doubt AI’s potential to replace programmers, check this out https://www.cognition-labs.com/blog . The AI world has been accelerating rapidly in the past two years, and we still don't seem to see its limits. Who would have thought, before the pandemic, that there would be a tool capable of writing complete applications based on Upwork job descriptions? While Cognition Labs claims that Devin should be used as a supporting tool alongside programmers, allowing engineers to focus on more interesting problems and enabling engineering teams to pursue more ambitious goals and so on and on… what can we expect from Devin v3 if this is just the first version? Instead of writing code, will programmers become mere curators of AI-generated code in the future??

On a side note: It's impressive that Devin can learn to use unfamiliar technologies. This feature sounds like a game-changer for projects focused on modernizing legacy software.

5. Oskar Maksymiuk: I bet you’ve heard about Large Language Models, but have you heard about the concept of Small Language Models (SLMs)?

https://thenewstack.io/the-rise-of-small-language-models/ ?

In short, Small Language Models (SLMs) are compelling alternatives to Large Language Models (LLMs) that may democratize AI adoption in smaller businesses. While LLMs like GPT-4 or LLaMA exhibit remarkable capabilities, which we leverage every day, the rise of SLMs offers businesses accessible and cost-effective solutions for language processing tasks. SLMs are more streamlined, with a simpler architecture, requiring less computational power to train, and cheaper to run. Additionally, SLMs can offer a level of customization often out of reach for LLMs, as their smaller size allows for easier fine-tuning and tailoring them to operate only on specific use cases and domains. Thanks to this, in some cases, SLMs like Phi-2, DistilBERT, or Orca 2 demonstrate effectiveness comparable to, and sometimes exceeding LLMs.?

As Small Language Models (SLMs) continue to advance, can we anticipate a future where software offerings will provide on-premise SLMs acting as know-it-all AI assistants within companies, equipped with the knowledge of all business processes and domains, revolutionizing how organizations operate and make decisions??