The ARB (from Latin arbor, tree) project was initiated almost 10 years ago. The ARB program package comprises a variety of directly interacting software tools for sequence database maintenance and analysis which are controlled by a common graphical user interface. Although it was initially designed for ribosomal RNA data, it can be used for any nucleic and amino acid sequence data as well. A central database contains processed (aligned) primary structure data. Any additional descriptive data can be stored in database fields assigned to the individual sequences or linked via local or worldwide networks. A phylogenetic tree visualized in the main window can be used for data access and visualization. The package comprises additional tools for data import and export, sequence alignment, primary and secondary structure editing, profile and filter calculation, phylogenetic analyses, specific hybridization probe design and evaluation and other components for data analysis. Currently, the package is used by numerous working groups worldwide.

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Separation of concerns represents an important principle for managing complexity in the design and architecture of large component-based software systems. The fundamental approach is to develop local solutions for individual concerns first, and combine them later into an overall solution for the complete system. However, comprehensive support for the integration of interdependent, possibly conflicting concerns related to synchronization behavior is still missing. In our work, we propose a sound solution for this complex type of composition, employing well-known UML description techniques as well as a rigorous formal model of component synchronization behavior. Based on this foundation, we describe a constructive synthesis algorithm which reliably detects conflicting concerns or generates a maximal synchronization behavior for software components with multiple interactions. An optimized implementation of the algorithm has been integrated into a CASE tool to illustrate feasibility and scalability of the presented technique to the example of a moderately large case study.

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