Guiding Service Composition in a Visual Service Creation Environment

Current day service composition languages like WS-BPEL require in-depth knowledge of this language by the service composition designers. In this paper we present a high-level, visual Service Creation Environment (SCE). This SCE provides service composition templates, verifica-tion of compatibility and guidelines, and advanced separa-tion of concerns through Aspect-Oriented Software Devel-opment. Composition templates are abstract descriptions of reusable compositions containing several placeholders for services. Services are verified to be compatible with the composition template when a service is mapped onto a composition template’s placeholder. Composition guide-lines such as QoS constraints can be added to the SCE and verified. The modularization of crosscutting concerns is supported by the SCE through the general-purpose Padus Aspect-Oriented Programming language and the possibil-ity to add concern-specific languages on top of Padus. The SCE generates the appropriate WS-BPEL processes given a complete and verified service composition. 1

AspectJ code analysis and verification with GASR

Aspect-oriented programming languages extend existing languages with new features for supporting modularization of crosscutting concerns. These features however make existing source code analysis tools unable to reason over this code. Consequently, all code analysis efforts of aspect-oriented code that we are aware of have either built limited analysis tools or were performed manually. Given the significant complexity of building them or manual analysis, a lot of duplication of effort could have been avoided by using a general-purpose tool. To address this, in this paper we present Gasr: a source code analysis tool that reasons over AspectJ source code, which may contain metadata in the form of annotations. Gasr provides multiple kinds of analyses that are general enough such that they are reusable, tailorable and can reason over annotations. We demonstrate the use of Gasr in two ways: we first automate the recognition of previously identified aspectual source code assumptions. Second, we turn implicit assumptions into explicit assumptions through annotations and automate their verification. In both uses Gasr performs detection and verification of aspect assumptions on two well-known case studies that were manually investigated in earlier work. Gasr finds already known aspect assumptions and adds instances that had been previously overlooked

V.: Explicit platform models for mda

Abstract. The main drive for Model-Driven Architecture is that many software applications have to be deployed on a variety of platforms. The way MDA achieves this is by transforming a platform-independent model of the software to a platform-specific model, given a platform model. In current MDA approaches, the model transformations implicitly represent this platform model. Therefore, the number of different target platforms is limited to the number of supported model transformations. We propose a separate platform model, based on description logics, that can can be used to automatically select and configure a number of reusable model transformations for a concrete platform. This platform model can be extended to describe the relevant platform information, including concrete platform instances as well as platform constraints for each model transformation. This separates the model transformation concern from the platform concern and, since the model transformations are no longer limited to targeting one platform, more platforms can be supported with the same set of transformations.