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Astract: The implementation of a domain agnostic software system (such as an enterprise resource planning system or a trading information system) based on the REA model requires a generic, yet highly adaptable software architecture. Building on top of well established academic findings and proposals regarding the REA model we are proposing a software model building on two main concepts: fragments and declarations. Together they establish a single, exible, extendible class hierarchy implemented purely on a database layer. Fragments and declarations are implemented as associative arrays that are enriched with metadata, providing clear access to attributes and their meta information. The system's exibility is drastically increased by enabling the multi-typification of REA entities.

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Astract: Sophisticated business rule engines provide a way to enable users with a non-software-engineering background to take action during the runtime of e.g. an enterprise information system: rules for customers can be defined, based on the turnover realized through them. The REA accounting model defines a concept for the modeling and excecution of business models, yet it does not go into detail how to implement and integrate business rules. We propose the integration of a proven business rule engine in contrast to the definition of a REA specific rule language or model by defining a set of anchor points into which specific business rules can be hooked that are fired when these anchor points are reached.

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Astract: The REA business model language is an established vehicle (i) to model businesses in terms of domain specific value chains and their key concepts and (ii) to capture business data in terms of accounting artefacts. REA has evolved into a specification that could drive web shops, enterprise/trading information systems, enterprise resource planning systems, etc. Such systems require support for sophisticated business rules in order to decouple business logic from application logic. In this work we present a framework for structural integration of business rules into REA business models.

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Astract: E-marketplaces on the World Wide Web are information and transaction silos, which in the general case don't allow transactions across their boundaries. The consequence is that the Web, often termed the global marketplace, is fragmented along the dimensions of geography, content domain, supply or demand, user base, and many more. This fragmentation makes it inefficient to buy and sell commodities on the Web. We propose a framework that serves as a foundation for a distributed, de-centralized e-marketplace on top of the Web, making boundaries between existing systems disappear from the user's perspective. The framework standardizes the creation and description of objects that represent supply and demand. In addition to this, it allows for independent matching services to connect objects suitable for a transaction and it defines protocols for the message exchange between such objects.

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Astract: The original REA accounting model (McCarthy, 1982) has been extended in previous years into a business modeling language. Apart from its conceptual model, academic effort has been put into the definition of a formal description language, based on standards such as UML or OWL. The specification of a generic data model from a software engineering point of view for domain independent use of REA for business model specification and execution has been touched only briefly in the past. Thus, we present a data model concept for runtime-configurable REA business model definition and execution.

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Astract: Electronic Invoicing has attracted a lot of attention by being a cornerstone of the Digital Agenda for Europe, Europe´s 2020 Strategy. This agenda mandates a "think small first" principle in order to enable e-invoicing for companies of any size. The electronic invoice should be exchanged between the ERP systems of business partners. Traditional approaches based on electronic data interchange failed to attract SMEs. Due to the high costs, they only use e-invoicing if forced by their larger business partners. In this paper, we present an alternative approach that is based on native ERP integration of most common e-invoice scenarios. This approach was successfully implemented in a research project resulting in a university spin-off.

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Astract: In model-driven software development, software models are the main artifacts used not only for supporting brainstorming, analysis, and design purposes, but also for generating executable code. Such software models are usually not created by one single developer, but within a team. To coordinate team work, versioning systems have proven to be indispensable for managing modifications performed by different modelers at the same time. When concurrently performed modifications are contradicting each other, the standard versioning paradigm requires the person who detected the conflict to resolve it immediately in order to keep the evolved artifacts in a consistent state. Whereas this approach works well in later phases of the software development process, in early phases, when the development team had not established a consolidated view on the system under development yet, the conflicts might provide valuable information on the various intentions of the modelers. This information might be lost if removed in an undocumented manner by a single modeler. We propose an alternative versioning paradigm for models, where conflicts are temporarily tolerated and discuss its technical realization for current modeling languages such as the UML. The resolution of conflicts is then not performed by one single modeler but within a team so that a consolidated version of the model is obtained.

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Astract: As every software artifact, also software models are subject to continuous evolution. The operations applied between two successive versions of a model are crucial for understanding its evolution. Generic approaches for detecting operations a posteriori identify atomic operations, but neglect composite operations, such as refactorings, which leads to cluttered difference reports. To tackle this limitation, we present an orthogonal extension of existing atomic operation detection approaches for detecting also composite operations. Our approach searches for occurrences of composite operations within a set of detected atomic operations in a post-processing manner. One major benefit is the reuse of specifications available for executing composite operations also for detecting applications of them. We evaluate the accuracy of the approach in a real-world case study and investigate the scalability of our implementation in an experiment.

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