> especially given binary search is quite literally the first algorithm every programmer learns.
I get what you're saying, and it doesn't change your point, but: no _way_ is binary search the first algorithm people learn. For binary search to even be intelligible you already have to know, at a minumum linear search and the concept of sorting (you probably know a sorting algorithm first). You also learn dozens of other really simple algorithms first in practice.
> no _way_ is binary search the first algorithm people learn. For binary search to even be intelligible you already have to know, at a minumum linear search and the concept of sorting
Almost every 6-10 year old kid who had to use physical dictionaries intuitively learned (probably even discovered by themselves) something like binary search. It's a different matter whether they could formalize that into an algorithm and write code to handle all the edge cases. But the basic idea is very intuitive. Kids can also pick up the intuition to incorporate improvements even beyond balanced binary search eg. there might be a lot of words starting with "S" so split into two groups at a little less than the middle, etc.
> Almost every 6-10 year old kid who had to use physical dictionaries intuitively learned (probably even discovered by themselves) something like binary search.
I find this highly unlikely. It might be true for those children who grow up to study computer science, though.
If you are asking which is the "first algorithm" a human learns in their life then it's likely more related to movement (crawl? walk? move food towards mouth?) or selection (which item can I eat? who are my parents?) rather than a physical dictionary. Even considering that it's been a while since kids encountered a physical dictionary.
If you are asking about formal algorithms then we're talking about the beginning of a programmers or computer scientists education and then it's usually some form of O(n^2) sort that they will encounter first, if we don't count things like "how to add two multi-digit integers" which is typically an algorithm every kid learns in primary school.
Binary search tends to be one of the first recursive algorithms that are taught which is another level entirely regarding intellectual development.
I guess my response was to how I read your comment fitting in with the higher level discussion. My main point is that many of these algorithms are intuitive, and kids learn these much earlier than when they learn formal programming (which might typically be in their teens).
Looking over your comment again, I also don't dispute that linear search and sorting are simpler -- even toddlers learn these.
> no _way_ is binary search the first algorithm people learn
It legit was the first one we learned, the first algorithm written on the blackboard by the professor (this was in the 2000s but the first algorithm lessons were on blackboard and paper!)
Probably because something simpler linear like "find the minimum value in a list" is too dull as an algorithm example
Agreed, WRT the bigger picture; lots of little algorithms could come before binary search.
But, giving them binary search before sorting kinda works. It is motivating. If you do sorting first, it just seems like a weird high-effort excursion into a niche bookkeeping thing about lists. Once they see how fast binary search is (just give them pre-sorted lists to run it on), sorting becomes interesting, right?
This is what I do in my introductory data structures and algorithms course at a Bay Area community college: I teach binary search as part of my introduction to recursion, and then the following lectures are a series of lessons on sorting algorithms, beginning with selection sort and then insertion sort. After teaching these O(n^2) algorithms, I spend a lecture on merge sort and then have a lecture on quicksort, both for covering O(n lg n) sorts and for introducing my students to divide-and-conquer recursive algorithms.
It is a shame that quicksort has to be covered. I mean, it does have to be covered. But it has an O(n^2) cost for a particular input, despite being generally considered nlog(n), seems to me to introduce some fuzziness in an otherwise solid concept.
Quicksort is an important, extremely flexible, and very hard to beat unstable comparison sort.
It's based on a very simple but powerful idea/strategy (divide & conquer). Its flexibility means it can be adapted to partially sort, find top-N, find the median or any other rank, all optimally.
And it's so much faster in practice than everything else (why?), that even after mitigating its worse case, it often comes out ahead.
Also, it is relevant/necessary to teach the concept of average, best and worse cases in complexity analysis. What best way to do it than “the best sorting algorithm is terrible for some inputs”?
You can also use it to teach/learn adaptive algorithms (you're almost expected too): switch to something else on the base case; or on the worst case; can we do better for low cardinality; etc.
If you’re forced to use comparative sorting and write it by hand and it’s near random etc then Quicksort isn’t that bad but even then there’s better options.
And it is hard to beat, which is why the standard libraries of languages like C++, Rust, Go, C#, Java (etc) use some quicksort variant for their unstable sorts (and some mergesort variant when they need stability).
All of the above aren't forced to use comparison sorts, they just do; no other caveats required.
You mentioned it was a comparisons sort, but not that you were only comparing it with other comparison sorts.
There’s also a huge caveat, libraries know less about your data than you do. Thus different default choices become optimal but any decent library will give you many options for very good reasons.
Quicksort is relatively terrible for partially ordered lists like appended timestamps from multiple processes etc etc. It’s only ok at a very narrow range of problems, and the important bit isn’t the implementation but where those borders are.
> Quicksort is relatively terrible for partially ordered lists like appended timestamps from multiple processes etc etc.
It's not, not really: pdqsort handles those organically.
I'm sorry if "best sort", "so much faster" and "very hard to beat" felt like baits. But "huge caveat", "relatively terrible" and being "forced to use comparative sorting" are not fair descriptions of quicksort or why it's used and chosen by standard libraries.
Regardless, my point was that there's a lot to learn from quicksort. It's not “a shame” that it must be taught, and mergesort is not “best.”
Mergesort is best because it is the most elegant and beautiful sorting algorithm. Just merge lists so that they stay sorted.
Quicksort has all sorts of nonsense bouncing around and picking pivots. Eww. Terrible.
I will admit that I could have been more clear that I was evaluating algorithms based on beauty, but given that info I’m sure the conclusion is obvious.
pdqsort fails to detect many partially ordered lists.
So you might argue about the scale of “Huge caveat” but trying to discover information about a list takes computing cycles. Even just pdqsort vs pdqsort_branchless exists due to that exact caveat, it’s fundamental to the nature of the problem. There’s infinitely ways data could have an inherent pattern which would speed up the process of sorting it and no way to algorithmically notice all patterns in such a way as to universally speed up sorting.
As to what there is to learn from Quicksort. I think it’s a poor introduction to algorithms not because it’s of the nature as an algorithm, but early on its many pitfalls draw attention away from more useful topics. Later on it’s simply not complex enough to be worth much attention. So sure in an academic context it looks really appealing, yet when you dig into what the point of teaching algorithms it’s much harder to justify. It’s covered so frequently you’re not even going to see it on interviews.
Even worse is the fact for naive implementations (such as students might come up with) the worst case behaviour occurs in very common cases such as sorting already sorted lists or reverse-sorted lists.
We have different notions of "covered", then. When I teach algorithms and introduce quicksort, the majority of the time is spent discussing strategies for choosing the pivot. I expect none of my students to implement a quicksort with bad pivot selection; if they do, that's my failure as a teacher and definitely failure in "coverage" of the algorithm.
It was actually the first algorithm I discovered and learned in a technical environment, when I was debugging my Skyrim mods list and realized I needed an efficient way to discover which of my hundreds of active mods were interacting, causing the dreaded neck-seam issue (It was Ethereal Elven overhaul and another whose name escapes me.)
It's an unusually intuitive algorithm, so it wouldn't surprise me if it were one many people learn first.
I get what you're saying, and it doesn't change your point, but: no _way_ is binary search the first algorithm people learn. For binary search to even be intelligible you already have to know, at a minumum linear search and the concept of sorting (you probably know a sorting algorithm first). You also learn dozens of other really simple algorithms first in practice.