Schulze and ranked-pairs elections have received much attention recently, and the former has quickly become a quite widely used election system. For many cases these systems have been proven resistant to bribery, control, or manipulation, with ranked pairs being particularly praised for being NP-hard for all three of those. Nonetheless, the present paper shows that with respect to the number of candidates, Schulze and ranked-pairs elections are fixed-parameter tractable to bribe, control, and manipulate: we obtain uniform, polynomial-time algorithms whose degree does not depend on the number of candidates. We also provide such algorithms for some weighted variants of these problems.

A program can benefit from improved cache block utilization when contemporaneously accessed data elements are placed in the same memory block. This can reduce the program's memory block working set and thereby, reduce the capacity miss rate. We formally define the problem of data packing for arbitrary number of blocks in the cache and packing factor (the number of data objects fitting in a cache block) and study how well the optimal solution can be approximated for two dual problems. On the one hand, we show that the cache hit maximization problem is approximable within a constant factor, for every fixed number of blocks in the cache. On the other hand, we show that unless P = NP, the cache miss minimization problem cannot be efficiently approximated.

Modern software executes a large amount of code. Previous techniques of code layout optimization were developed one or two decades ago and have become inadequate to cope with the scale and complexity of new types of applications such as compilers, browsers, interpreters, language VMs and shared libraries.This paper presents Codestitcher, an inter-procedural basic block code layout optimizer which reorders basic blocks in an executable to benefit from better cache and TLB performance. Codestitcher provides a hierarchical framework which can be used to improve locality in various layers of the memory hierarchy. Our evaluation shows that Codestitcher improves the performance of the original program by 3% to 25% (on average, by 10%) on 5 widely used applications with large code sizes: MySQL, Clang, Firefox, Apache, and Python. It gives an additional improvement of 4% over LLVM's PGO and 3% over PGO combined with the best function reordering technique.

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