Someone asked me about my template that used a “cache wrapper” for lambdas, so I decided to write a post explaining how it works. For reference, here is a submission of mine from 2021 that uses that template. Here’s what you will find implementations for in this post: Generalized hashing (for tuple types, sequence types and basic types) Convenient aliases for policy based data structures Wrappers for recursive (or otherwise) lambdas that automatically do caching (memoization) for you. Jump to the Usage section if you only care about the template, though I would strongly recommend reading the rest of the post too since it has a lot of cool/useful things in my opinion. ...

Introduction A lot of people shy away from solving (mathematical) recurrences just because the theory is not very clear/approachable due to not having an advanced background in math. As a consequence, the usual ways of solving recurrences tend to be: Find the first few terms on OEIS. Guess terms from the rate of growth of the recurrence (exponential rate of growth means you can sometimes estimate the exponential terms going from largest to smallest — though this fails in cases where there is a double-root of the characteristic equation) Use some theorem whose validity you can’t prove (the so-called characteristic equation method) Overkill using generating functions But this doesn’t have to be the case, because there is a nice method you can apply to solve equations reliably. I independently came up with this method back when I was in middle school, and surprisingly a lot of people have no idea that you can solve recurrences like this. ...

Motivation On a computer science discord server, someone recently asked the following question: Is the master theorem applicable for the following recurrence? \(T(n) = 7T(\lfloor n / 20 \rfloor) + 2T(\lfloor n / 8 \rfloor) + n\) There was some discussion related to how \(T\) is monotonically increasing (which is hard to prove), and then someone claimed that there is a solution using induction for a better bound. However, these ad hoc solutions often require some guessing and the Master theorem is not directly applicable. ...

The contents are as follows: Introduction Why you should use lambdas Some context Hand-rolling our own lambdas C++ lambda syntax explained Using lambdas Using lambdas with the STL Some useful non-trivial patterns Some other interesting patterns Examples of competitive programming code using C++ lambdas Prerequisites: knowing a bit about structs/classes in C++, member functions, knowing that the STL exists. If you feel something is not very clear, I recommend waiting for a bit, because I tried to ensure that all important ideas are explained at some point or another, and if you don’t understand and it doesn’t pop up later, it is probably not that important (and should not harm the experience of reading this post). Nevertheless, if I missed out on explaining something that looks important, please ask me in the comments — I’d be happy to answer your questions! ...

This post is not about the binary GCD algorithm, but rather about exploring theoretical guarantees for an optimization on top of the standard Euclidean algorithm. The STL version is faster than both these algorithms, because it uses the binary GCD algorithm, but these algorithms are of interest from theoretical considerations. In particular, my conjecture is that the second algorithm takes at most as many iterations as the first one, and if true, it’d be a pretty surprising claim, given how hard it is to bound Euclidean algorithm runtimes. So, it would be really cool if someone could prove this property. ...

Note: for those who don’t like using the post-increment operator (i++), hopefully this post convinces you that it is not just a convention that C programmers coaxed the world into following out of tradition. Also, all of the following discusses the increment operators in C++, and not C, where the semantics are slightly different. Disclaimer: I use ++i much more often in code. But i++ has its own place, and I use it — and the generalization I mention — quite frequently wherever it is a sane choice. ...

I believe that adding the Boost library on Codeforces would be a great addition for C++ competitive programmers. AtCoder already supports it (alongside GMP and Eigen, but Boost has replacements/wrappers for those: Boost.Multiprecision and Boost.uBLAS). CodeChef supports it too (or at least used to support it at some point, not sure now). I’ve seen at least 3 posts by people trying to use Boost on Codeforces and failing, and on thinking about it, I couldn’t really come up with a good reason (in my opinion) that Boost should not be supported on Codeforces. ...

Disclaimer: Please verify that whichever of the following solutions you choose to use indeed increases the stack limit for the execution of the solution, since different OSes/versions can behave differently. On Linux (and probably MacOS), running ulimit -s unlimited in every instance of the shell you use to execute your program will work just fine (assuming you don’t have a hard limit). On some compilers, passing -Wl,--stack=268435456 to the compiler options should give you a 256MB stack. ...

TL;DR The Floyd-Warshall algorithm is a special case of the more general case of aggregation over paths in a graph — in this post, we look at a few examples and point to some references for further study. The algebraic path problem constitutes a family of problems that can be solved using similar techniques. This and this paper develop the theory of semirings in this context, and this treats some computational aspects of it. Kleene algebras are what end up being used in most of the examples given here, but semirings are more general structures. While not discussed in the post, the idea of a valuation algebra is a further generalization that shows connections to more problems of various types. Introduction Most people doing competitive programming who learn about the Floyd-Warshall algorithm learn it in the context of computing the lengths of the shortest paths between all pairs of vertices in a graph on \(n\) vertices in \(O(n^3)\), which is better than naively running Dijkstra or other kinds of shortest-path algorithms (other than Johnson’s algorithm for the sparse case), and can also identify negative cycles. ...

It’s been about 5 years since the round took place, and since there was no editorial all this time, I decided to write one myself. Thanks to tfg for discussing problem F with me and coming up with the permutation interpretation that makes it much easier to reason about the problem. The idea in F was also inspired by other submissions. 1060A Hints/intuition Think about two cases: when there are very few 8s, and when there are a lot of 8s. ...