while lo < hi:
mid = (lo + hi) // 2
if a[mid] == x:
return mid
elif a[mid] < x:
lo = mid + 1
else:
hi = mid
return -1
But then I discovered that there's an alternative approach which has only one test per iteration: while lo < hi:
mid = (lo + hi) // 2
if a[mid] < x:
lo = mid + 1
else:
hi = mid
if lo < len(a) and a[lo] == x:
return lo
else:
return -1
If comparisons are expensive compared to other operations then this is twice as fast as the variant with two comparisons per iteration. (If comparisons are cheap, as they are if you are searching an array of numbers in a compiled language, then it doesn't make much difference.)Sorry to burst your bubble, but any moderately complex LOB CRUD app usually has a large amount of far more complex algos than a binary sort. Your off-hand comment shows a total ignorance of what's involved in writing a LOB CRUD web app.
In my experience, algos are the really easy part of programming. The hard part is managing complexity.
His point is that when you design an algorithm you need to be able to reason about why it works.
Based on the rest of your comments in this thread, it sounds to me like you have something against the mathematical background of CS? Writing code is not the same thing as doing computer science. Plenty of people are perfectly happy doing the former, but CS as an academic discipline is rooted in discrete math so any school that teaches it should also teach the background.
Notice how it took you just one sentence to summarise the few hundred words he wrote.
We've a fairly big problem in this industry that "qualified" CS graduates don't actually signal anything about their suitability for the profession. A significant chunk can't even fizzbuzz.
I'd suggest teaching mathematical models instead of showing loops and recursion in practical code is a large chunk of the problem.
Oh, come on. What sornaensis's one sentence summarizes is ... the one sentence at the start of my comment. It's true that his is shorter; it also gives less information.
(For the avoidance of doubt, that isn't a problem. Since you declared yourself unable to understand what I wrote, it's fair enough to try to simplify it.)
The rest of what I wrote was (1) an answer to your subsidiary question "What am I missing?" plus (2) an explanation of what I was talking about, in case it was stuff you weren't familiar with.
(Of course if I'd known you'd respond as unpleasantly as you did, I wouldn't have bothered trying to be helpful. But at the time I thought you might well be asking a sincere question rather than just wanting to vent about how out of touch those hoity-toity theoreticians are.)
I didn't claim that CRUD apps don't have complexity in them. I claimed that CRUD apps don't typically have the sort of thing in them for which this kind of small-scale semi-formal stuff is useful in them. I am happy to stand by that claim; do you actually disagree with it?
I get the impression that you think I was being sniffy about CRUD apps. I wasn't. In particular, (1) I don't think CRUD apps are low-value. There are plenty of CRUD apps that add much more value to the world than almost any piece of code of the sort that invariants are super-helpful for. And (2) I don't think that CRUD apps are easy. Well, doubtless some are, but as you say they commonly have huge amounts of complication in them, of a sort that isn't amenable to the kind of formalized reasoning I was talking about.
To answer the implied question in your first sentence: I wasn't trying to make a point, I was giving an answer to a question you asked, namely why mathematical induction might be important for programmers.
Briefer and more explicit version of that answer: For people writing certain kinds of code, understanding mathematical induction makes it easier to reason about that code via techniques such as loop invariants, which makes it easier to make that code bullet-proof. There are many other kinds of code for which nothing closely related to mathematical induction is of any value at all.
(And, to reiterate lest I set the bee in your bonnet buzzing again: Whether a kind of code benefits from this sort of technique has basically nothing to do with how important it is, or how difficult it is to write overall, or what anyone should think of the people writing it.)
Whether you are missing anything depends on whether you ever write the sort of code that benefits from this. (Even if you do, you still might not be missing anything. You might be comfortable with loop invariants but not have connected them with proof by induction. Or you might be good at reasoning about these things in other ways that don't involve invariants.)
(You can stop reading here if you're already very familiar with loop variants and invariants.)
Here's the sort of thing I mean by loop variants/invariants. Suppose you're writing a binary search. (Don't write a binary search. Use someone else's that's already had the bugs taken out.) This is basically pretty simple but surprisingly easy to get subtly wrong, which means it's the sort of code it may be useful to write and document in such a way that you have an informal proof of its correctness. Like this:
The above is pseudocode in no particular language. Is it correct? Those variants and invariants (1) divide that question in two and (2) provide a strategy for answering the second half of the question. First sub-question: if the (in)variants always hold, does that imply that the code is correct? Second sub-question: do they always hold? (Strategy for second sub-question: proof by induction on array size and/or number of iterations.)The first invariant implies that since mid is always between lo (inclusive) and hi (exclusive) it's safe to access a[mid]. The second, given that it holds at both start and end of the loop body, implies that if we exit the loop then indeed x isn't in the array. The only ways to leave the function are via the return in the middle, which only happens when we have explicitly found x, and via the return at the end, which only happens when x is known to be absent; therefore, if we return anything, we return the right thing. And the variant says that the quantity D, which starts by equalling the number of elements in the array, is reduced by a factor of at least 2 at each step; as it's always a (strictly) positive integer, this implies that the number of steps is at most log_2(n), so the function does return.
(Note that that last bit is more or less a proof by induction on array size that the function always returns.)
So if the invariants hold then the function does the right thing in the right amount of time.
Proving that the invariants hold is the induction-like bit. The first invariant holds at the start (since lo,hi start out being exactly min index and max index + 1). Each time around the loop we replace either lo or hi with something in between the two, so we still have min <= lo <= hi < max+1; and we will exit the loop unless in fact lo<hi. So the first invariant always holds.
The second invariant holds at the start (since lo,hi are bounds on the entire array). Because the array is sorted, our adjustments to lo/hi make this invariant true again for the next time around the loop. So the second invariant holds at the end of the loop -- and of course therefore at the start of the next iteration.
(Note that those were both proofs by induction, though I wasn't super-explicit about the fact.)
The variant works because if we write D = hi-lo and E = floor(D/2) then the new value of D is, depending on which branch of that if we take, either E or D-E-1; note that D-E-1<=E; so new-D <= E <= D/2 as claimed.
It's probably pretty clear what sort of code this is useful for: highly "algorithmic" code that's basically doing something fairly simple but that's tricky to think about and easy to get wrong. If you're writing a language's standard library, or implementing some sort of iterative mathematical algorithm, then you're quite likely to find it useful. The less like that your code is, the less often this technique will be useful to you. (Fairly extreme example: if you are writing a CRUD webapp then it is unlikely that anything you do will benefit from this.)