JetBrains

Our premier #dotnet community event, JetBrains .NET Days Online 2024, is back for its sixth edition! 💰 Free 📢 September 25–26 🗣️ Laïla Bougriâ, Mariekie Coetzee 🇦🇺, Chris Woodruff, Alexander Zeitler, Cecil Phillip, Irina Dominte(Scurtu), Gael Fraiteur, Daniel Ward, Roman Provazník, Stefano Tempesta, Andrei Karpov, Andrii Rublov, and Konstantin Saltuk. 🎙️ Topics on the agenda: C#, .NET Aspire, Blazor, Razor, HTMX, F#, ReSharper, microservices, code verification techniques, testing, and even ASP.NET MVC! Register: https://lnkd.in/dq8jdNwK #JBDotNetDays

Discussions about the correct ratio of testers to developers have been ongoing for years in the software development industry. Here’s some data from our Developer Ecosystem survey (2700 responses). 41% of respondents have less than one QA engineer per 10 developers in their project, and 32% have 1-3 QA engineers per 10 developers. The need for some kind of standard here is itself a questionable topic because this ratio may vary greatly from company to company and project to project. Still, this data may indicate how far software development teams must go to establish effective quality assurance practices. With a significant portion of teams operating with minimal QA resources, the industry faces ongoing challenges in ensuring high-quality software delivery. What ratio do you have in your team? How do you collaborate with testers to improve the quality of your solutions?

"You build it, you run it." This philosophy empowers developers to take full ownership of their code, from development all the way through to production. While this approach can lead to a sense of ownership and operational excellence, it’s important to equip developers with the right tools and support. Without these, developers may struggle with on-call duties and production responsibilities, leading to stress and inefficiency. Teams can reduce production issues by testing their code well and maintaining good observability. JetBrains Developer Advocate Marit van Dijk and Field CTO at Honeycomb Liz Fong-Jones discussed this approach and other aspects of efficient development collaboration for GOTO Unscripted. Watch the full conversation here: https://lnkd.in/d4i7ZXYd. Video credit: GOTO Conferences

Many in the tech industry are familiar with technical debt, but it can mean different things depending on your perspective. For some, it’s a trade-off for quickly getting a product to market. For others, it’s a lingering issue that can slow progress and innovation if not addressed.

Join us for JetBrains GameDev Days 2024! This is a free live virtual event dedicated to game development, covering Unity, Unreal Engine, and Godot. Learn how to craft the best games from expert speakers. Register: https://lnkd.in/d5eT7nK2 🗓️ October 9–10 🎙️ Topics: #gamedev, #Unity, #UnrealEngine, #Godot, CI/CD, and more!

While AI coding assistants can deliver major productivity gains, many of these tools equate productivity with generating new code faster. Unfortunately, there is early evidence that coding assistants can erode code quality. Code analytics company GitClear analyzed 153 million changed lines of code authored between January 2020 and December 2023 and noted distinct changes after the launch of GitHub Copilot. Lines of churned code – code which is committed but reverted, removed, or updated within the following two weeks – increased by 39% in 2023. Code churn may indicate that incomplete and erroneous code was committed. Another 2023 research paper concluded that many GitHub Copilot solutions for the HumanEval programming problem dataset contained code smells, estimating that 172 minutes of work would be needed to tackle the resulting technical debt. What causes code quality problems when using AI coding assistants? How to avoid them? Read the full article to explore the problem of the AI-driven code quality gap: https://lnkd.in/defkN_QY

Registration for JetBrains #JavaScriptDay2024 is now open! We invite you to join us for JetBrains #JavaScriptDay2024, our annual online event about modern JavaScript and TypeScript development. This year, we’ve gathered an impressive lineup of community experts to share their thoughts on the latest trends and the most widely discussed new features of React, Angular, Vue, and, of course, JavaScript and TypeScript. The speakers joining us this year are Evan You, Kevin Powell, Danny Thompson, Shruti Kapoor, Josh Goldberg, Bekah Hawrot Weigel, Chau Tran, and Jeremy Elbourn. We’ll cover everything you need to know about the ever-changing world of JavaScript today! Learn more and register now: https://lnkd.in/dX6ubFwE

What is the most popular game development engine? What challenges the industry is facing? How is AI used in game development companies? See the answers to these and other questions in the 2024 State of Game Technology report, a collaboration with Perforce Software! This report offers a deep dive into the current game development landscape, based on insights from professionals around the world. It covers the adoption of new technologies, the challenges organizations are facing, and the tools that are shaping the future of game development. Explore the highlights in the image carousel, and see the link to the full report in the comments 👇

JetBrains Rider has won the CEDEC Excellence Award in the Engineering category! This award is a testament to our team’s dedication to providing a robust IDE that supports game development with Unity and Unreal Engine, driving productivity and innovation in the industry. We extend our sincere thanks to the CEDEC committee for this recognition.

LLMs are getting better, but their tendency to “hallucinate,” meaning they produce incorrect information, remains. Fortunately, LLM’s hallucination rate can be measured and compared against other models. In this video, JetBrains Developer Advocate Jodie Burchell, PhD explains how hallucinations occur in LLMs and how we can measure one specific type of hallucination: the tendency of models to regurgitate misinformation that they have learned from their training data. You will also learn about recent initiatives to try to reduce hallucinations in LLMs using a technique called retrieval-augmented generation, and how complex this can be to get right, introducing another layer of complexity on top of the already tricky area of LLM deployment. Watch the full talk here: https://lnkd.in/dQivqa97. Video credit: Python Software Foundation.