Jan Ploski

Trustworthy software systems: a discussion of basic concepts and terminology

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.

Research issues in software fault categorization

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.

WISENT: e-Science for Energy Meteorology

Our energy production increasingly depends on renewable energy sources, which impose new challenges for distributed and decentralized systems. One problem is that the availability of renewable energy sources such as wind and solar is not continuous as it is affected by meteorological factors. The challenge is to develop forecast methods capable of determining the level of power generation in near real-time in order to control power plants for optimal energy production. Another scenario is the identification of optimal locations for such power plants. In our collaborative project, these tasks are investigated in the domain of energy meteorology. For that purpose large data sources from many different sensors (e.g., satellites and ground stations) are the base for complex computations. The idea is to parallelize these computations in order to obtain significant speedup. This paper reports on an ongoing project employing Grid technologies in that context. Our approach to processing large data sets from a variety of heterogeneous data sources as well as ideas for parallel and distributed computing in energy meteorology are presented. Preliminary experience with several Grid middleware systems in our application scenario is discussed.

Grid-based deployment and performance measurement of the Weather Research & Forecasting model

A system developed for benchmarking multi-processor Numerical Weather Prediction applications deployed on D-Grid resources is presented. The system currently serves to perform functional and non-functional software tests of the Weather Research and Forecasting (WRF) model used in the project WISENT. The resulting performance data and the input configurations are automatically published through a web portal to enable third-party comparisons with other, existing WRF deployments. The developed system relies on a self-contained, domain-independent software module for running MPI and other multi-processor Grid (Globus Toolkit 4) jobs that require a user-defined synchronized initialization and cleanup phase.

Exception Handling in an Event-Driven System

Exception handling mechanisms were invented in 1970s to support structured programming methods for hierarchically organised software systems. The need to increase reusability and flexibility led to the development of new programming paradigms that do not emphasise hierarchical design. Event-driven systems n which objects communicate using notifications about changed states - are a prime example. Unfortunately, this style of communication makes exception handling more difficult than in hierarchical systems. We contribute an analysis of the factors which influence exception handling in event-driven systems. The main focus of our discussion lies on the challenge of appropriate exception propagation. We provide results from an empirical case study performed on the source code of the Eclipse IDE that support our analysis

Grid-based processing of high-volume meteorological data sets

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.