With the increasing complexity of in-car communication architectures, their diagnostics have become essential for automotive development and maintenance. In order to help engineers to detect and analyze the potential sources and consequences of errors, it is crucial to provide both comprehensive and detailed insight into the communication processes and their contexts. Two important aspects of these are the dependencies and correlations between onboard functions. In this paper we present a dual-view visualization for exploring the functional dependency chains of in-car communication processes. One view presents the dependencies of hardware components using a space filling approach similar to a treemap, whereas the other view displays the functional correlations as an interactive sequence chart. The views are coupled via color coding and show the dependencies of an interactively selectable functional unit. In an expert evaluation, we assessed the benefits of using this visualization technique for in-car communication diagnostics with very positive results.

We propose to extend database systems by a Skyline operation. This operation filters out a set of interesting points from a potentially large set of data points. A point is interesting if it is not dominated by any other point. For example, a hotel might be interesting for somebody traveling to Nassau if no other hotel is both cheaper and closer to the beach. We show how SSL can be extended to pose Skyline queries, present and evaluate alternative algorithms to implement the Skyline operation, and show how this operation can be combined with other database operations, e.g., join.

Semi-join reducers were introduced in the late 1970s as a means to reduce the communication costs of distributed database systems. Subsequent work in the 1980s showed, however, that semi-join reducers are rarely beneficial for the distributed systems of that time. This paper shows that semi-join reducers can indeed be beneficial in modern client-server or middleware systems - either to reduce communication costs or to better exploit all the resources of a system. Furthermore, we present and evaluate alternative ways to extend state-of-the-art (dynamic programming) query optimizers in order to generate good query plans with semi-join reducers. We present two variants, called Access Root and Join Root, which differ in their implementation complexity, running times and the quality of the plans they produce. We present the results of performance experiments that compare both variants with a traditional query optimizer.

The query optimizer is one of the most important components of a database system. Most commercial query optimizers today are based on a dynamic-programming algorithm, as proposed in Selinger et al. [1979]. While this algorithm produces good optimization results (i.e, good plans), its high complexity can be prohibitive if complex queries need to be processed, new query execution techniques need to be integrated, or in certain programming environments (e.g., distributed database systems). In this paper, we present and thoroughly evaluate a new class of query optimization algorithms that are based on a principle that we calliterative dynamic programming, or IDP for short. IDP has several important advantages: First, IDP-algorithms produce the best plans of all known algorithms in situations in which dynamic programming is not viable because of its high complexity. Second, some IDP variants are adaptive and produce as good plans as dynamic programming if dynamic programming is viable and as good-as possible plans if dynamic programming turns out to be not viable. Three, all IDP-algorithms can very easily be integrated into an existing optimizer which is based on dynamic programming.