This paper presents a framework for architecture alignment that can be positioned between approaches for software architecture, which concern software artefacts only, and strategic alignment models, which have a business focus. The framework is currently applied in case study research to find alignment patterns used in practice. First results presented in this paper indicate that the framework might yield an operationalization of strategic architecture alignment models. We also present an alignment pattern which shows a difference between how architectures are designed at the application level and the infrastructure level. We think this difference is significant for practical alignment models.

New application domains cause today's database sizes to grow rapidly, posing great demands on technology. Data fragmentation facilitates techniques (like distribution, parallelization. and main-memory computing) meeting these demands. Also, fragmentation might help to improve efficient processing of query types such as top N. Database design and query optimization require a good notion of the costs resulting from a certain fragmentation. Our mathematically derived selectivity model facilitates this. Once its two parameters have been computed based on the fragmentation, after each (though usually infrequent) update, our model can forget the data distribution, resulting in fast and quite good selectivity estimation. We show experimental verification for Zipfian distributed IR databases.

Efficient, flexible, and scalable integration of full text information retrieval (IR) in a DBMS is not a trivial case. This holds in particular for query optimization in such a context. To facilitate the bulk-oriented behavior of database query processing, a priori knowledge of how to limit the data efficiently prior to query evaluation is very valuable at optimization time. The usually imprecise nature of IR querying provides an extra opportunity to limit the data by a trade-off with the quality of the answer. In this paper we present a mathematically derived model to predict the quality implications of neglecting information before query execution. In particular we investigate the possibility to predict the retrieval quality for a document collection for which no training information is available, which is usually the case in practice. Instead, we construct a model that can be trained on other document collections for which the necessary quality information is available, or can be obtained quite easily. We validate our model for several document collections and present the experimental results. These results show that our model performs quite well, even for the case were we did not train it on the test collection itself.

An operation in object-oriented databases gives rise to the processing of a path. Several database operations may result into the same path. The authors address the problem of optimal index configuration for a single path. As it is shown an optimal index configuration for a path can be achieved by splitting the path into subpaths and by indexing each subpath with the optimal index organization. The authors present an algorithm which is able to select an optimal index configuration for a given path. The authors consider a limited number of existing indexing techniques (simple index, inherited index, nested inherited index, multi-index, and multi-inherited index) but the principles of the algorithm remain the same adding more indexing techniques.>

In order to obtain the performance required for nonstandard database environments, a hierarchical complex object model with object references is used as a storage structure for complex objects. Several storage models for these complex objects, as well as a benchmark to evaluate their performance, are described. A cost model for analytical performance evaluation is developed, and the analytical results are validated by means of measurements on the DASDBS, complex object storage system. The results show which storage structures for complex objects are the most efficient under which circumstances.>

The execution of a query in a parallel database machine can be controlled in either a control flow way, or in a data flow way. In the former case a single system node controls the entire query execution. In the latter case the processes that execute the query, although possibly running on different nodes of the system, trigger each other. Lately, many database research projects focus on data flow control since it should enhance response times and throughput. The authors study control versus data flow with regard to controlling the execution of database queries. An analytical model is used to compare control and data flow in order to gain insights into the question which mechanism is better under which circumstances. Also, some systems using data flow techniques are described, and the authors investigate to which degree they are really data flow. The results show that for particular types of queries data flow is very attractive, since it reduces the number of control messages and balances these messages over the nodes.>

The grid file offers multiattribute access and is a structure proposed for geometrical applications. This means that so-called point, partial match, partial range and range queries for the concerned attributes are supported. The generalized grid file (GGF), which offers fast access for a single attribute too, is described. The performance of the GGF structure is evaluated for the business environment, and the results look promising. The generalized grid file seems to be a good storage and access structure for computer-integrated manufacturing (CIM), an environment in which business and geometrical applications meet

In optimizing database queries one inevitably encounters two important estimation problems. The first problem is to estimate the number of page accesses when selecting k tuples from a relation. The other problem is to estimate the number of different equijoin values remaining after selecting k tuples from a relation. The estimated values strongly depend on how the tuples are distributed over the pages (first problem) and how the equijoin values are distributed over the relation (second problem). It appears to be possible to find restrictive upper and lower limits for these problems in many practical situations. Results derived elsewhere appear to fall significantly outside these limits. Finally, a (time) efficient algorithm to approximate the values to be estimated, is proposed.

Recently, extensions for relational database management systems (DBMS) have been proposed to support also hierarchical structures (complex objects). These extensions have been mainly implemented on top of an existing DBMS. Such an approach leads to many disadvantages not only from the conceptual point of view but also from performance aspects. Thus paper reports on a 3-year effort to design and prototype a DBMS to support a generalized relational data model, called extended NF2 (Non First Normal Form) data model which treats flat relations, lists, and hierarchical structures in a uniform way. The logical data model, a language for this model, and alternatives for storage structures to implement generalized relations are presented and discussed.