> I think a lot of people just want to be able to discuss different areas of the automatic memory management design space separately, and maintaining the distinction between reference counting and garbage collection (meaning tracing GCs) lets them do that.<p>The problem is that there are many differences in memory management techniques that offer different tradeoffs, and the difference between refcounting and tracing is not necessarily the biggest of them.<p>For example, one of the most important distinctions in memory management is whether it optimises for footprint or speed (or some compromise), and the line isn't where people who don't understand memory management think it is. It can matter (often a great deal) whether you determine that an object is dead dynamically (say, by counting references) or statically (by manually writing free or by having the language track lifetimes), but it doesn't matter as much as whether or not the mechanism needs to know when objects are dead in the first place. So reference counting, manual free, static lifetimes, and even non-moving mark-and-sweep tracing collectors (like Go's) generally optimise for footprint at the expense of speed (although different allocators can have some control over that tradeoff), while arenas and tracing moving collectors optimise for speed at the expense of footprint (although here, too, they have some control over the tradeoff). So the line for this super-important tradeoff is between [manual, static, refcoutning] and [arenas, moving tracing]; non-moving tracing collectors are somewhere in between but may be closer to the first group.<p>People who don't understand memory management and may not have a lot of experience in low-level programming sometimes think that manual or statically-determined freeing must be fast because low-level languages, which inexperienced people think are fast, use them. In fact, low-level languages have some concerns that are much more important than speed and that preclude them from optimisations such as moving pointers. To get around that performance handicap, these languages try to avoid using their heap memory management as much as possible because they're using a rather slow technique because of their constraints.
I don't really disagree much with what you said. My favored PLang Nim (<a href="https://nim-lang.org/" rel="nofollow">https://nim-lang.org/</a> -- it has both `ref` and `ptr` styles of pointer, one auto-managed, one manually managed) even changed a while back it's `nim c --gc=x` command-line language to `nim c --mm=x`, and I was in favor of said change.<p>However, it does inspire me to write.. The kernel of all this terminology confusion is under-exposure of industrial programmers to not just academic terminology, but also the very design space you mention (which has always been nicely covered by Jones' outstanding book). Just to take an example from the root of this thread:<p>>widespread common usage of the term “garbage collected programming language” which specifically contrasts manual languages like C++ or Rust against garbage collected ones<p>Boehm-Wiser conservative collection for <i>C</i>, among the most manual languages of all, pre-dates its very first ANSI 1989 standard.<p>This underexposure itself is downstream of the kinds of oversimplifications/lies of marketing and in this particular case came from Java. The evolution I witnessed was roughly 1) linking Boehm with -lgc and deleting (or #define'ing away) all your `free()` calls is conservative - to be <i>precise</i> you need compiler aid and a lot of programmers are "not perfect==awful" personality types, 2) Sun Microsystems wants to leverage a lot of reliability issues with C code and become <i>The</i> Platform and spends <i>gobs</i> of money to win hearts & minds, partly succeeding, 3) part of its ad-warfare against the then WIntel hegemony and/or tutorials/introductory material for Junior Programmers (<i>often</i> the target of "be more reliable" material) plays fast & loose with GC terminology because marketing plays fast & loose structurally for fun but mostly profit, 4) because human language really does == language usage a la Quine, everyone in the industry re-defines what "GC" means to bind it to a programming language instead of to a specific run-time, 5) industry & academics use different language, confusion ensues and so here we are.<p>This is not even the 100th time that either explicit or implicit forces of marketing have achieved confusion analogously to this. If you believe most people don't need much of what they spend on then confusion is arguably intrinsic to marketing of ideas/products. The highly misleading but suggestive metaphorical language used all over "AI" in both research and in product-lines is a more current case of this, leading anyone who knows much to have to qualify "not AGI" or other such junk just to have a conversation.<p>So, what is my point? Basically just that the larger problem here will persist as long as there is money to be made/attention to be garnered by sowing confusion/having people talk past each other/think some product is more than it really is. I have no meta-strategy in my back pocket to block these successful confusions, but it does seem worth being aware of it.