формирование ассортимента и управление им маркетинг
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формирование ассортимента и управление им маркетинг, RedMonk Top 20 Languages Over Time: January 2025, RedMonk Ranks Top Programming Languages Over Time - and , RedMonk's "Top 20 Languages Over Time: September 2012 - June , The RedMonk Programming Language Rankings: June 2022 (2025), RedMonk Top 20 Languages Over Time: January 2025 - vuink.com, Programming Languages Popularity Indexes | by Vaibhav Pandey , RedMonk Programming Language Rankings | by Maan Khan - Medium.
The computing field lapsed into a nostalgia mode over a decade ago, letting programming languages, frameworks, web stack (html, css, JavaScript) stagnate instead of innovating.This nostalgia is not just reverting back to Fortran and punch cards, it's keeping the technological status quo in place for the large part of computing. Innovative products, languages, frameworks, etc. come, get hyped and fail to replace the old time leaders.Nostalgia mode? For one, take a look at any modern web framework (e.g. Angular). It doesn't look a whole lot like it did a decade ago. Whether it is useful change or not may be debatable, but it definitely hasn't stagnated. I have had personal experience updating an old Spring Boot (Java) application and there were lots and lots of changes to be done (we vastly underestimated the complexity... probably because we had assumed it wasn't all that different).That's at a framework level. At a language level, yes things "stagnate" - features evolve slowly (but even C++ is getting new features regularly). This is for a couple of reasons. First, it isn't as if the "old school" were dumb. They created languages that were useful at solving problems and an enormous amount of code was created (and the experience to go along with it). The existing code is still useful and rewriting it would be ridiculously expensive and a waste of time - so it doesn't get rewritten - and "stagnates". FORTRAN still exists because an awful lot of useful code was written in it (FORTRAN excels at efficient numerical computations and it is hard to do better).If what you are proposing is that every few years, we start using some "innovative" new language, you will ultimately get a lot of churn, create training problems for new programmers (oh, I now have to figure out how to use language X). If your project is a decade old, you'll now have 3-4 languages in the project because each new functionality needed to written in the new cool language. Or do you want to rewrite every 3 years working code to be in the new cool language?(My personal theory is that there is very little good code that is less than 10 years old. It takes that amount of time - of continuous use - to find and correct the serious problems in anything remotely complex. It has to stagnate to become good. Occasionally a genius will come along with good code faster than that, but that is rare.), You can track a specific language’s ranking over time by following the horizontal progression of the language’s rank over time. You can review the Top 20 languages of any given iteration by running through the respective data points vertically from top to bottom., The developer-focused analyst firm RedMonk releases twice-a-year rankings of programming language popularity. This week they also released a handy graph showing the movement of top 20 languages since 2012. Their current rankings for programming language popularity 1. JavaScript 2. Python 3..
RedMonk just released their “Top 20 Languages Over Time: September 2012 - June 2024” analyst report. We all know that these kinds of comparisons never tell the full, complex story of the ecosystem, but still, you can gain some insights from this type of reading., While the specific means of collection has changed, the basic process remains the same: 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., As part of RedMonk’s analysis about language rankings, here’s a visualization that tracks the movement of the top 20 languages over the history of the rankings. More commentary about notable movement among languages can be found in the primary analysis, and further notes about our data sources are available here., RedMonk plots each language on two axes — GitHub usage (commits, repos) and Stack Overflow discussion (questions, answers) — then ranks based on the intersection of those dimensions., The RedMonk Programming Language Rankings provide a detailed look at which programming languages are currently popular and growing among developers worldwide. Released twice a year, these, .