Software Engineering

cross-posted from: https://lemmy.bestiver.se/post/841355

Good (but scary) overview of state of AI in the og article, some points:

Don't read if you don't want to ruin your day.

The first scaling crisis happened in 1996, when Linus wrote that he was "buried alive in emails". It was addressed by adopting a more modular architecture, with the introduction of loadable kernel modules, and the creation of the maintainers role, who support the contributors in ensuring that they implement the high standards of quality needed to merge their contributions.

Resurfaced in my feed. Obvious in retrospect.

COBOL remains crucial to businesses and institutions around the world.

Good before going to bed on Friday evening :)

Yea or Nay?

Could be fun ;)

A nice cheatsheet/summary for software architecture

Even sourcing, cqrs and friends and a take on YAGNI

This talk covers the origins of flame graphs, how you can create them using open source software, and how to interpret them. In practice, flame graphs don’t always work completely due to problems walking stack traces, resolving symbols, and other issues; this talk explains the problems and shows you the latest techniques for fixing them.

Joe Duffy discusses the challenges (and solutions) met while running IaC and how that shapes the future of IaC.

Mark Richards' long running series on software architecture comes in bite-sized videos running about 10 minutes.

The point of this blog post is that, although most of us don’t work on software that would directly be considered safety-critical, we live in a world that’s becoming increasingly automated and computerized, and sometimes, bugs in seemingly mundane pieces of code, even web apps, can cause real-world suffering and harm, particularly when they go unfixed for weeks, months or even years.

In May 2023 over 90,000 developers responded to our annual survey about how they learn and level up, which tools they're using, and which ones they want. ... This year, we went deep into AI/ML to capture how developers are thinking about it and using it in their workflows. Stack Overflow is investing heavily in enhancing the developer experience across our products, using AI and other technology, to get people to solutions faster.

NOTE: This is primarily an invitation for the "SEI and White House OSTP to Explore the Future of Software and AI Engineering", but there is this big section on the "future of software engineering" that is very interesting.

Conclusion: Four Areas for Improving Collaboration on ML-Enabled System Development

At Pinterest, Closeup recommendations (aka Related Pins) is typically a feed of recommended content (primarily Pins) that we serve on any pin closeup. Closeup recommendations generate the largest amount of impressions among all recommendation surfaces at Pinterest and are uniquely critical for our users’ inspiration-to-realization journey. It’s important that we surface qualitative, relevant, and context-and-user-aware recommendations for people on Pinterest.

The repository consists of three layers:

PS: Sounds like an ad, but still interesting to see tools in the wild that support AI for these conceptual phases in software engineering

In today’s hybrid work landscape, meetings have become abundant, but unfortunately, many of them still suffer from inefficiency and ineffectiveness. Specifically, meetings aimed at generating ideas to address various challenges related to people, processes, or products encounter recurring issues. The lack of a clear goal in these meetings hinders active participation, and the organizer often dominates the conversation, resulting in a limited number of ideas that fail to fully solve the problem. Both the organizer and attendees are left feeling dissatisfied with the outcomes.

After reading this: I know Kung-Fu

Reminded me of Kevin Kelly's book Out of Control

As the flagship track at QCon, Architectures You've Always Wondered About showcases real-world examples of innovator companies pushing the limits with modern software systems.

Always interesting to see real life design choices.

Saving for the comparison with the next year

AI recruitment post as it seems

Kinda cool ;)

Leslie shares his journey into computing, which started out as something he only did in his spare time as a mathematician. Scott and Leslie discuss the differences and similarities between computer science and software engineering, the math involved in Leslie’s high-level temporal logic of actions (TLA), which can help solve the famous Byzantine Generals Problem, and the algorithms Leslie himself has created. He also reflects on how the building of distributed systems has changes since the 60s and 70s.

Specifically, we’re diving into a massive migration project by Khan Academy, involving moving one million lines of Python code and splitting them across more than 40 services, mostly in Go, as part of a migration that took 3.5 years and involved around 100 software engineers.

Always interesting to read real world applications of the concepts. Nubank's framework is a mix of storytelling, design thinking, empathy mapping, ...

Adopting DevOps practices is nowadays a recurring task in the industry. DevOps is a set of practices intended to reduce the friction between the software development (Dev) and the IT operations (Ops), resulting in higher quality software and a shorter development lifecycle. Even though many resources are talking about DevOps practices, they are often inconsistent with each other on the best DevOps practices. Furthermore, they lack the needed detail and structure for beginners to the DevOps field to quickly understand them.

Attention economy is a pretty important concept in today's socioeconomic systems. Here an article by Nielsen Norman Group explaining it a bit in the context of digital products.

Very good paper by @paulralph@mastodon.acm.org discussing Rational Paradigm (non emprirical) and Empiriral Paradigm (evidence-based, scientific) in software engineering. Historically the Rational Paradigm has dominated both the software engineering research and industry, which is also evident in software engineering international standards, bodies of knowledge (e.g. IEEE CS SWEBOK), curriculum guidelines, ... Basically, much of the "standard" knowledge and mainstream literature has no basis in science, but "guru" knowledge. But people rarely follow rational approaches successfully or faithfully, which suggest using detailed plans, ...

There are people/researchers from ACM and so on sharing pretty interesting, useful content about software engineering.

Developers across government and industry should commit to using memory safe languages for new products and tools, and identify the most critical libraries and packages to shift to memory safe languages, according to a study from Consumer Reports.

This kind of scaling issue is new to Codeberg (a nonprofit free software project), but not to the world. All projects on earth likely went through this at a certain point or will experience it in the future.