21 research outputs found
Mean asymptotic behaviour of radix-rational sequences and dilation equations (Extended version)
The generating series of a radix-rational sequence is a rational formal power
series from formal language theory viewed through a fixed radix numeration
system. For each radix-rational sequence with complex values we provide an
asymptotic expansion for the sequence of its Ces\`aro means. The precision of
the asymptotic expansion depends on the joint spectral radius of the linear
representation of the sequence; the coefficients are obtained through some
dilation equations. The proofs are based on elementary linear algebra
Singularity analysis, Hadamard products, and tree recurrences
We present a toolbox for extracting asymptotic information on the
coefficients of combinatorial generating functions. This toolbox notably
includes a treatment of the effect of Hadamard products on singularities in the
context of the complex Tauberian technique known as singularity analysis. As a
consequence, it becomes possible to unify the analysis of a number of
divide-and-conquer algorithms, or equivalently random tree models, including
several classical methods for sorting, searching, and dynamically managing
equivalence relationsComment: 47 pages. Submitted for publicatio
Rational series and asymptotic expansion for linear homogeneous divide-and-conquer recurrences
Among all sequences that satisfy a divide-and-conquer recurrence, the
sequences that are rational with respect to a numeration system are certainly
the most immediate and most essential. Nevertheless, until recently they have
not been studied from the asymptotic standpoint. We show how a mechanical
process permits to compute their asymptotic expansion. It is based on linear
algebra, with Jordan normal form, joint spectral radius, and dilation
equations. The method is compared with the analytic number theory approach,
based on Dirichlet series and residues, and new ways to compute the Fourier
series of the periodic functions involved in the expansion are developed. The
article comes with an extended bibliography
Average Cost of QuickXsort with Pivot Sampling
QuickXsort is a strategy to combine Quicksort with another sorting method X, so that the result has essentially the same comparison cost as X in isolation, but sorts in place even when X requires a linear-size buffer. We solve the recurrence for QuickXsort precisely up to the linear term including the optimization to choose pivots from a sample of k elements. This allows to immediately obtain overall average costs using only the average costs of sorting method X (as if run in isolation). We thereby extend and greatly simplify the analysis of QuickHeapsort and QuickMergesort with practically efficient pivot selection, and give the first tight upper bounds including the linear term for such methods
QuickXsort: A Fast Sorting Scheme in Theory and Practice
QuickXsortis a highly efficient in-place sequential sorting scheme that mixesHoare’sQuicksortalgorithm with X, where X can be chosen from a wider rangeof other known sorting algorithms, likeHeapsort,InsertionsortandMergesort.Its major advantage is thatQuickXsortcan be in-place even if X is not. In thiswork we provide general transfer theorems expressing the number of comparisonsofQuickXsortin terms of the number of comparisons of X. More specifically,if pivots are chosen as medians of (not too fast) growing size samples, the aver-age number of comparisons ofQuickXsortand X differ only byo(n)-terms. Formedian-of-kpivot selection for some constantk, the difference is a linear term whosecoefficient we compute precisely. For instance, median-of-threeQuickMergesortuses at mostnlgn−0.8358n+O(logn)comparisons. Furthermore, we examine thepossibility of sorting base cases with some other algorithm using even less compar-isons. By doing so the average-case number of comparisons can be reduced down tonlgn−1.4112n+o(n)for a remaining gap of only 0.0315ncomparisons to the knownlower bound (while using onlyO(logn)additional space andO(nlogn)time over-all). Implementations of these sorting strategies show that the algorithms challengewell-established library implementations like Musser’sIntrosort
Analysis of pivot sampling in dual-pivot Quicksort: A holistic analysis of Yaroslavskiy's partitioning scheme
The final publication is available at Springer via http://dx.doi.org/10.1007/s00453-015-0041-7The new dual-pivot Quicksort by Vladimir Yaroslavskiy-used in Oracle's Java runtime library since version 7-features intriguing asymmetries. They make a basic variant of this algorithm use less comparisons than classic single-pivot Quicksort. In this paper, we extend the analysis to the case where the two pivots are chosen as fixed order statistics of a random sample. Surprisingly, dual-pivot Quicksort then needs more comparisons than a corresponding version of classic Quicksort, so it is clear that counting comparisons is not sufficient to explain the running time advantages observed for Yaroslavskiy's algorithm in practice. Consequently, we take a more holistic approach and give also the precise leading term of the average number of swaps, the number of executed Java Bytecode instructions and the number of scanned elements, a new simple cost measure that approximates I/O costs in the memory hierarchy. We determine optimal order statistics for each of the cost measures. It turns out that the asymmetries in Yaroslavskiy's algorithm render pivots with a systematic skew more efficient than the symmetric choice. Moreover, we finally have a convincing explanation for the success of Yaroslavskiy's algorithm in practice: compared with corresponding versions of classic single-pivot Quicksort, dual-pivot Quicksort needs significantly less I/Os, both with and without pivot sampling.Peer ReviewedPostprint (author's final draft