University of Passau

About: University of Passau is a education organization based out in Passau, Bayern, Germany. It is known for research contribution in the topics: Computer science & Context (language use). The organization has 1543 authors who have published 4763 publications receiving 93338 citations.

Compositional minimisation of finite state systems using interface specifications

Abstract: We present a method for thecompositional construction of theminimal transition system that represents the semantics of a given distributed system. Our aim is to control thestate explosion caused by the interleavings of actions of communicating parallel components byreduction steps that exploitglobal communication constraints given in terms ofinterface specifications. Theeffect of the method, which is developed forbisimulation semantics here, depends on the structure of the distributed system under consideration, and theaccuracy of the interface specifications. However, itscorrectness is independent of the correctness of the interface specifications provided by the program designer.

Detection of feature interactions using feature-aware verification

Abstract: A software product line is a set of software products that are distinguished in terms of features (i.e., end-user-visible units of behavior). Feature interactions-- situations in which the combination of features leads to emergent and possibly critical behavior --are a major source of failures in software product lines. We explore how feature-aware verification can improve the automatic detection of feature interactions in software product lines. Feature-aware verification uses product-line-verification techniques and supports the specification of feature properties along with the features in separate and composable units. It integrates the technique of variability encoding to verify a product line without generating and checking a possibly exponential number of feature combinations. We developed the tool suite SPLVERIFIER for feature-aware verification, which is based on standard model-checking technology. We applied it to an e-mail system that incorporates domain knowledge of AT&T. We found that feature interactions can be detected automatically based on specifications that have only local knowledge.

Scalable prediction of non-functional properties in software product lines: Footprint and memory consumption

Abstract: Context: A software product line is a family of related software products, typically created from a set of common assets Users select features to derive a product that fulfills their needs Users often expect a product to have specific non-functional properties, such as a small footprint or a bounded response time Because a product line may have an exponential number of products with respect to its features, it is usually not feasible to generate and measure non-functional properties for each possible product Objective: Our overall goal is to derive optimal products with respect to non-functional requirements by showing customers which features must be selected Method: We propose an approach to predict a product's non-functional properties based on the product's feature selection We aggregate the influence of each selected feature on a non-functional property to predict a product's properties We generate and measure a small set of products and, by comparing measurements, we approximate each feature's influence on the non-functional property in question As a research method, we conducted controlled experiments and evaluated prediction accuracy for the non-functional properties footprint and main-memory consumption But, in principle, our approach is applicable for all quantifiable non-functional properties Results: With nine software product lines, we demonstrate that our approach predicts the footprint with an average accuracy of 94%, and an accuracy of over 99% on average if feature interactions are known In a further series of experiments, we predicted main memory consumption of six customizable programs and achieved an accuracy of 89% on average Conclusion: Our experiments suggest that, with only few measurements, it is possible to accurately predict non-functional properties of products of a product line Furthermore, we show how already little domain knowledge can improve predictions and discuss trade-offs between accuracy and required number of measurements With this technique, we provide a basis for many reasoning and product-derivation approaches

Biodiesel: A New Oildorado?

Abstract: Guaranteeing tax reductions and exemptions, the European governments intend to increase the share of biofuels in total EU fuel consumption to 5.75% by 2010. The financial support of this EU objective is frequently justified by expected positive environmental impacts, most notably the mitigation of climate change, and by favorable employment effects in the agricultural sector. This paper investigates the environmental and economic implications of the support of rapeseed-based biodiesel as a substitute for fossil diesel.Based on a survey of recent empirical studies, we find that the energy and greenhouse gas balances of this environmental strategy are clearly positive.Yet, its overall environmental balance is currently far from being unequivocally positive. Most importantly, biodiesel is not a cost-efficient emission abatement strategy. Thus, for the abatement of greenhouse gases,we recommend more efficient alternatives based on both renewable and conventional technologies.