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.

Credit Where Credit is Due? The Impact of Project Contributions and Social Factors on Authorship and Inventorship

Abstract: Using unique survey data from over 2,000 life scientists, we examine the extent to which different types of substantive project contributions as well as social factors predict whether a scientist is named as author on a paper and inventor on a patent resulting from the same project. We find that the predictors of authorship differ from those of inventorship. A wider range of project contributions may result in authorship, and social factors appear to play a larger role in authorship decisions than in inventorship decisions. We also find evidence that project contributions and social factors interact in predicting authorship, suggesting that the two sets of factors should be considered jointly rather than seen as independent determinants of attribution. In addition to providing novel insights into the functioning of the authorship and inventorship system, our results have important implications for administrators, managers, and policy makers, as well as for innovation scholars who often rely on patents and publications as measures of scientists' performance.

A Constraint Oriented Proof Methodology Based on Modal Transition Systems

Abstract: We present a constraint-oriented state-based proof methodology for concurrent software systems which exploits compositionality and abstraction for the reduction of the verification problem under investigation. Formal basis for this methodology are Modal Transition Systems allowing loose state-based specifications, which can be refined by successively adding constraints. Key concepts of our method are projective views, separation of proof obligations, Skolemization and abstraction. Central to the method is the use of Parametrized Modal Transition Systems. The method easily transfers to real-time systems, where the main problem are parameters in timing constraints.

Guaranteeing Syntactic Correctness for All Product Line Variants: A Language-Independent Approach

Abstract: A software product line (SPL) is a family of related program variants in a well-defined domain, generated from a set of features. A fundamental difference from classical application development is that engineers develop not a single program but a whole family with hundreds to millions of variants. This makes it infeasible to separately check every distinct variant for errors. Still engineers want guarantees on the entire SPL. A further challenge is that an SPL may contain artifacts in different languages (code, documentation, models, etc.) that should be checked. In this paper, we present CIDE, an SPL development tool that guarantees syntactic correctness for all variants of an SPL. We show how CIDE’s underlying mechanism abstracts from textual representation and we generalize it to arbitrary languages. Furthermore, we automate the generation of plug-ins for additional languages from annotated grammars. To demonstrate the language-independent capabilities, we applied CIDE to a series of case studies with artifacts written in Java, C++, C, Haskell, ANTLR, HTML, and XML.

Structured merge with auto-tuning: balancing precision and performance

Abstract: Software-merging techniques face the challenge of finding a balance between precision and performance. In practice, developers use unstructured-merge (i.e., line-based) tools, which are fast but imprecise. In academia, many approaches incorporate information on the structure of the artifacts being merged. While this increases precision in conflict detection and resolution, it can induce severe performance penalties. Striving for a proper balance between precision and performance, we propose a structured-merge approach with auto-tuning. In a nutshell, we tune the merge process on-line by switching between unstructured and structured merge, depending on the presence of conflicts. We implemented a corresponding merge tool for Java, called JDime. Our experiments with 8 real-world Java projects, involving 72 merge scenarios with over 17 million lines of code, demonstrate that our approach indeed hits a sweet spot: While largely maintaining a precision that is superior to the one of unstructured merge, structured merge with auto-tuning is up to 12 times faster than purely structured merge, 5 times on average.

Boosting k -Induction with Continuously-Refined Invariants

Abstract: \(k\)-induction is a promising technique to extend bounded model checking from falsification to verification. In software verification, \(k\)-induction works only if auxiliary invariants are used to strengthen the induction hypothesis. The problem that we address is to generate such invariants (1) automatically without user-interaction, (2) efficiently such that little verification time is spent on the invariant generation, and (3) that are sufficiently strong for a \(k\)-induction proof. We boost the \(k\)-induction approach to significantly increase effectiveness and efficiency in the following way: We start in parallel to \(k\)-induction a data-flow-based invariant generator that supports dynamic precision adjustment and refine the precision of the invariant generator continuously during the analysis, such that the invariants become increasingly stronger. The \(k\)-induction engine is extended such that the invariants from the invariant generator are injected in each iteration to strengthen the hypothesis. The new method solves the above-mentioned problem because it (1) automatically chooses an invariant by step-wise refinement, (2) starts always with a lightweight invariant generation that is computationally inexpensive, and (3) refines the invariant precision more and more to inject stronger and stronger invariants into the induction system. We present and evaluate an implementation of our approach, as well as all other existing approaches, in the open-source verification-framework CPAchecker. Our experiments show that combining \(k\)-induction with continuously-refined invariants significantly increases effectiveness and efficiency, and outperforms all existing implementations of \(k\)-induction-based verification of C programs in terms of successful results. Open image in new window