Improving a long standing result of Schonhage, Paterson and Pippenger we show that the median of a set containing n elements can be found using at most 2:95n comparisons.

We introduce exponential search trees as a novel technique for converting static polynomial space search structures for ordered sets into fully-dynamic linear space data structures. This leads to an optimal bound of O ( � log n / log log n) for searching and updating a dynamic set X of n integer keys in linear space. Searching X for an integer y means finding the maximum key in X which is smaller than or equal to y. This problem is equivalent to the standard text book problem of maintaining an ordered set. The best previous deterministic linear space bound was O(log n / log log n) due to Fredman and Willard from STOC 1990. No better deterministic search bound was known using polynomial space. We also get the following worst-case linear space trade-offs between the number n, the word length W, and the maximal key U < 2W: O(min{log log n + log log U log n / log W, log log n · log log log U}). These trade-offs are, however, not likely to be optimal. Our results are generalized to finger searching and string searching, providing optimal results for both in terms of n.

We study the exact number of symbol comparisons that are required to solve the string matching problem and present a family of efficient algorithms. Unlike previous string matching algorithms, the algorithms in this family do not "forget" results of comparisons, what makes their analysis much simpler. In particular, we give a linear-time algorithm that finds all occurrences of a pattern of length m in a text of length n in n+d 4 log m+2 m (n \Gamma m)e comparisons. The pattern preprocessing takes linear time and makes at most 2m comparisons. This algorithm establishes that, in general, searching for a long pattern is easier than searching for a short one. We also show that any algorithm in the family of the algorithms presented must make at least n + blog mcb n\Gammam m c symbol comparisons, for m = 2 k \Gamma 1 and any integer k 1.

Problems involving strings arise in many areas of computer science and have numerous practical applications. We consider several problems from a theoretical perspective and provide efficient algorithms and lower bounds for these problems in sequential and parallel models of computation. In the sequential setting, we present new algorithms for the string matching problem improving the previous bounds on the number of comparisons performed by such algorithms. In parallel computation, we present tight algorithms and lower bounds for the string matching problem, for finding the periods of a string, for detecting squares and for finding initial palindromes.

In this paper we introduce a new class of shortest path problems, where the contribution of a link to the path length computation depends not only on the weight of that link but also on the weights of the links already traversed. This class of problems may be viewed as \nonMarkovian ". We consider a specic problem that belong to this class, which is encountered in the multimedia data transmission domain. We consider this problem under dierent conditions and develop algorithms. The shortest path problem in multimedia data transmission environment can be solved in O(n 2 ) or O(n 3 ) computational time. 1

The multiple selection problem asks for the elements of rank r1 , r2 , . . . , rk from a linearly ordered set of n elements. Let B denote the information theoretic lower bound on the number of element comparisons needed for multiple selection. We first show that a variant of multiple quickselect --- a well known, simple, and practical generalization of quicksort --- solves this problem with B + expected comparisons.

Improving a long standing result of Bent and John, and extending a recent result of Dor, Hastad, Ulfbeg and Zwick, we obtain a (2+ffl)n lower bound (for some fixed ffl ? 0) on the number of comparisons required, in the worst case, for selecting the median of n elements.

A great deal of effort has been directed towards determining the minimum number of binary comparisons sufficient to produce various partial orders given some partial order. For example, the sorting problem considers the minimum number of comparisons sufficient to construct a total order starting from n elements. The merging problem considers the minimum number of comparisons sufficient to construct a total order from two total orders. The searching problem can be seen as a special case of the merging problem in which one of the total orders is a singleton. The selection problem considers the minimum number of comparisons sufficient to select the i th largest of n elements. Little, however, is known about the minimum number of comparisons sufficient to produce an arbitrary partial order. In this paper we briefly survey the known results on this problem and we present some first results on partial orders which can be produced using either restricted types of comparisons or a limited n...

this paper to eliminate such initial transient periods

We prove that sorting 13 elements requires 34 comparisons.