This paper provides experimental and theoretical evidence for the existence of contiguous failure regions in the program input space (`blob' defects). For realtime systems where successive input values tend to be similar, blob defects can have a major impact on the software survival time because the failure probability is not constant. For example, with a `random walk' input sequence, the probability of failure decreases as the time from the last failure increases. It is shown that the key factors affecting the survival time are the input `trajectory ', the rate of change of the input values and the `surface area' of the defect (rather than its volume). 1 Introduction This paper is an extension of earlier experimental studies on the failure characteristics of some known software defects [1, 2, 3]. The results of these studies cast doubt on the general validity of an assumption of constant probability of failure for software. In conventional reliability theory, it is often assumed that...

In the last few years, theoretical study of quantum systems serving as computational devices has achieved tremendous progress. We now have strong theoretical evidence that quantum computers, if built, might be used as a dramatically powerful computational tool, capable of performing tasks which seem intractable for classical computers. This review is about to tell the story of theoretical quantum computation. I left out the developing topic of experimental realizations of the model, and neglected other closely related topics which are quantum information and quantum communication. As a result of narrowing the scope of this paper, I hope it has gained the benefit of being an almost self contained introduction to the exciting field of quantum computation. The review begins with background on theoretical computer science, Turing machines and Boolean circuits. In light of these models, I define quantum computers, and discuss the issue of universal quantum gates. Quantum algorithms, including Shor’s factorization algorithm and Grover’s algorithm for searching databases, are explained. I will devote much attention to understanding what the origins of the quantum computational power are, and what the limits of this power are. Finally, I describe the recent theoretical results which show that quantum computers maintain their complexity power even in the presence of noise, inaccuracies and finite precision. This question cannot be separated from that of quantum complexity, because any realistic model will inevitably be subject to such inaccuracies. I tried to put all results in their context, asking what the implications to other issues in computer science and physics are. In the end of this review I make these connections explicit, discussing the possible implications of quantum computation on fundamental physical questions, such as the transition from quantum to classical physics. 1

. During the last decade, CCS has been extended in different directions, among them priority and real time. One of the most satisfactory results for CCS is Milner's complete proof system for observational congruence [28]. Observational congruence is fair in the sense that it is possible to escape divergence, reflected by an axiom recX:(ø:X + P ) = recX:ø:P . In this paper we discuss observational congruence in the context of interactive Markov chains, a simple stochastic timed variant CCS with maximal progress. This property implies that observational congruence becomes unfair, i.e. it is not always possible to escape divergence. This problem also arises in calculi with priority. So, completeness results for such calculi modulo observational congruence have been unknown until now. We obtain a complete proof system by replacing the above axiom by a set of axioms allowing to escape divergence by means of a silent alternative. This treatment can be profitably adapted to other calculi. 1 I...

Abstract. It is possible toviewthecombinatorial structuresknown as (integral) t-designs asZ-modules in a natural way. In this note we introduce a polynomial associated to each such Z-module. Using this association, we quickly derive explicit bases for the important class of submodules which correspond to the so-called null-designs. Introduction. Among the most fundamental (and least understood) types of combinatorial configurations are the t-designs [2], [5], [6]. These can be defined as follows. Let v, k, andA be positive integers satisfying-<k<- v.At-design Sx (t, k, v) is a collection #9 of k-subsetsB (called blocks) of a v-set V with the property that every t-subset of V occurs as a subset of exactlyA blocksB.(It is notrequired thatblocks

as Viral Acharya and Christopher Mann for their insightful comments. This paper would not have seen the light of day (at least not under its actual form) without the constant help and support from Kenneth Garbade. A special thought goes to Claudia Perlich and Jerold Weiss. The usual disclaimer applies. Temporal Resolution of Uncertainty, the Investment Policy of Leveraged Firms and Corporate Debt Yields This paper attempts to link the agency literature (concerned with whether debt will trigger underinvestment incentives or risk-shifting behavior) with the one dealing with temporal resolution of uncertainty. To the best of our knowledge, apart from one article by John and Ronen (1990), there is no research article linking the two literatures. We are concerned here with how the product/input market influences deviations from the optimal investment policy, in particular to what extent the speed of resolution of uncertainty of the industry in which a given firm operates affects the risk-shifting behavior of a shareholder-aligned manager. We assume that investors are risk neutral and that the return on the risky technology is normally distributed. It is then shown that the pattern of temporal resolution of uncertainty monotonically affects risk shifting as well as bond yields, even after contracts mitigating deviations from optimal investment policy have been written; empirical implications are derived and discussed. 2

In this paper, we describe three algorithms for the generation of symmetric Lévy noise and we discuss the relative performance in terms of time of execution on an Intel Pentium M processor at 1500 MHz. The relative performance of the three algorithm is given as a function of the Lévy stable index α and of the number of produced random points.

Inference in random environment ABSTRACT: We study the problem of maximum likelihood estimation in some random environment population models t defined through It6 stochastic differential equations. It is shown that a criticality parameter can be estimated consistently. The asymptotic behavior of the estimators is analyzed t and a goodness of fit test is proposed. KEY WORDS: Stochastic differential equation t random environment t population process t maximum likelihood estimation. AMS (1980) Classification: Primary 62F12 Secondary 60H101. Introducti on Classical population models are usually written in the form of differential equations. These deterministic models can be thought of as representing the average behavior of a large population. Voltera and D'Ancona (1935) mOdelled single species population development by an equation of the form (1) Here x t represents the population size at time t. whereas the function f. which may depend on the population history. measures the growth rate. This model does not deal with fluctuations around the average behavior. One way to incorporate randomness. i.e. to allow for individual differences and interaction between the individuals. is to replace (1) by the Ito stochastic differential equation (2) with X

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We consider, following the work of S. Kerov, random walks which are continuous-space generalizations of the Hook Walks defined by Greene-Nijenhuis-Wilf, performed under the graph of a continual Young diagram. The limiting point of these walks is a point on the graph of the diagram. We present several explicit formulas giving the probability densities of these limiting points in terms of the shape of the diagram. This partially resolves a conjecture of Kerov concerning an explicit formula for the so-called Markov transform. We also present two inverse formulas, reconstructing the shape of the diagram in terms of the densities of the limiting point of the walks. One of the two formulas can be interpreted as an inverse formula for the Markov transform. As a corollary, some new integration identities are derived. 1.