Software faults are a major threat for the dependability of software systems. When we intend to study the impact of software faults on software behavior, examine the quality of fault tolerance mechanisms, or evaluate diagnostic techniques, the issue of distinguishing fault categories and their frequency distribution arises immediately. This article surveys the literature that provides quantitative data on categories of software faults and discusses the applicability of these software fault category distributions to fault injection case studies.
Basic concepts and terminology for trustworthy software systems are discussed. Our discussion of definitions for terms in the domain of trustworthy software systems is based on former achievements in dependable, trustworthy and survivable systems. We base our discussion on the established literature and on approved standards. These concepts are discussed in the context of our graduate school TrustSoft on trustworthy software systems. In TrustSoft, we consider trustworthiness of software systems as determined by correctness, safety, quality of service (performance, reliability, availability), security, and privacy. Particular means to achieve trustworthiness of component-based software systems - as investigated in TrustSoft - are formal verification, quality prediction and certification; complemented by fault diagnosis and fault tolerance for increased robustness.
Our energy production increasingly depends on regenerative energy sources, which impose new challenges. One problem is the availability of regenerative energy sources like wind and solar radiation that is influenced by fluctuating meteorological conditions. Thus the development of forecast methods capable of determining the level of power generation (e.g., through wind or solar power) in near real-time is needed. Another scenario is the determination of optimal locations for power plants. These aspects are considered in the domain of energy meteorology. For that purpose large data repositories from many heterogeneous sources (e.g., satellites, earth stations, and data archives) are the base for complex computations. The idea is to parallelize these computations in order to obtain significant speed-ups. This paper reports on employing Grid technologies within an ongoing project, which aims to set up a Grid infrastructure among several geographically distributed project partners. An approach to transfer large data sets from many heterogenous data sources and a means of utilizing parallelization are presented. For this purpose we are evaluating various Grid middleware platforms. In this paper we report on our experience with Globus Toolkit 4, Condor, and our first experiments with UNICORE.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.