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.

Bridging the Gap between Variability in Client Application and Database Schema.

Abstract: Database schemas are used to describe the logical design of a database Diverse groups of users have different perspectives on the schema which leads to different local schemas Research has focused on view integration to generate a global, consistent schema out of different local schemas or views However, this approach seems to be too constrained when the generated global view should be variable and only a certain subset is needed Variable schemas are needed in software product lines in which products are tailored to the needs of stakeholders We claim that traditional modeling techniques are not sufficient for expressing a variable database schema We show that software product line methodologies, when applied to the database schemas, overcome existing limitations and allow the generation of tailor-made database schemas

Automatic detection of feature interactions using the Java modeling language: an experience report

Abstract: In the development of complex software systems, interactions between different program features increase the design complexity. Feature-oriented software development focuses on the representation and compositions of features. The implementation of features often cuts across object-oriented module boundaries and hence comprises interactions. The manual detection and treatment of feature interactions requires a deep knowledge of the implementation details of the features involved. Our goal is to detect interactions automatically using specifications by means of design by contract and automated theorem proving. We provide a software tool that operates on programs in Java and the Java Modeling Language (JML). We discuss which kinds of feature interactions can be detected automatically with our tool and how to detect other kinds of interactions.

Functional test of small-delay faults using SAT and Craig interpolation

Abstract: We present SATSEQ, a timing-aware ATPG system for small-delay faults in non-scan circuits. The tool identifies the longest paths suitable for functional fault propagation and generates the shortest possible sub-sequences per fault. Based on advanced model-checking techniques, SATSEQ provides detection of small-delay faults through the longest functional paths. All test sequences start at the circuit's initial state; therefore, overtesting is avoided. Moreover, potential invalidation of the fault detection is taken into account. Experimental results show high detection and better performance than scan testing in terms of test application time and overtesting-avoidance.

Teachers' Judgements of Students' Foreign-Language Achievement.

Abstract: Numerous studies have been conducted on the accuracy of teacher judgement in different educational areas such as mathematics, language arts and reading. Teacher judgement of students’ foreign-language achievement, however, has been rarely investigated. The study aimed to examine the accuracy of teacher judgement of students’ foreign-language achievement, uncover variables moderating the accuracy in a multilevel analysis and explore motivational and emotional characteristics of misjudged English learning students. Five hundred five Chinese fifth-grade students and their 16 English teachers took part in the investigation. Students completed a standardized English test and a questionnaire about motivation and emotion for English learning. Concurrently, English teachers estimated each of their students’ test performance. Teachers predicted the rank order of students’ achievement very accurately but tended to overestimate students’ level of achievement. Multilevel modelling revealed that neither students’ gender, performance level and perceived teacher treatment nor teachers’ teaching experience and level of education moderated the accuracy of teachers’ judgements. Underestimated students showed the same achievement as overestimated students but had a lower self-concept, higher anxiety and more shame about English learning. Although teachers’ judgements were fairly accurate, teachers’ underestimation of students’ achievement was associated with negative motivational and emotional characteristics of students.