The field of computational complexity and algorithmic techniques is witnessing significant developments, with a focus on resolving long-standing problems and improving existing methods. Researchers are exploring innovative approaches to tackle complex challenges, such as counting and sampling traces in regular languages, and reconstructing binary strings from traces with deletions. Notably, new bounds are being established for various problems, including circular trace reconstruction, and improvements are being made to sampling algorithms for permutations and well-typed functions. The connection between bounded treewidth and multiple context-free languages is also being leveraged to provide optimal algorithms for computing downward closures. Some noteworthy papers in this area include: A paper that presents a fully polynomial-time randomized approximation scheme and a fully polynomial-time almost uniform sampler for counting and sampling Mazurkiewicz traces. A paper that describes an exact sampler for well-typed functions in a simply-typed, first-order functional programming language. A paper that establishes a connection between bounded treewidth and multiple context-free languages, and provides an optimal algorithm for computing downward closures.