International Journal of Information System Modeling and Design 

About: International Journal of Information System Modeling and Design is an academic journal published by IGI Global. The journal publishes majorly in the area(s): Computer science & Information system. It has an ISSN identifier of 1947-8186. Over the lifetime, 241 publications have been published receiving 2194 citations. The journal is also known as: IJISMD.

The Anatomy of the ArchiMate Language

Abstract: In current business practice, an integrated approach to business and IT is indispensable. In many enterprises, however, such an integrated view of the entire enterprise is still far from reality. To deal with these challenges, an integrated view of the enterprise is needed, enabling impact/change analysis covering all relevant aspects. This need sparked the development of the ArchiMate language, which was developed with the explicit intention of becoming an open standard, and as such has been designed such that it is extendable while still maintaining a clear and orthogonal structure. This article is concerned with documenting some of the key structures and design principles underlying the ArchiMate language. ArchiMate is designed as an architecture description language ADL for enterprise architectures. The authors will start by discussing the challenges facing the design of an architecture description language. Consequently we discuss how the design principles of the ArchiMate language aim to tackle these challenges. They then continue with a discussion of the modelling concepts needed. In this, we make a distinction between concepts needed to model domains in general, the modelling of dynamic systems, and the modelling of enterprise architectures.

Object-Aware Business Processes: Fundamental Requirements and their Support in Existing Approaches

Abstract: Despite the increasing maturity of process management technology not all business processes are adequately supported by it. Support for unstructured and knowledge-intensive processes is missing, especially since they cannot be straight-jacketed into predefined activities. A common characteristic of these processes is the role of business objects and data as drivers for process modeling and enactment. This paper elicits fundamental requirements for effectively supporting such object-aware processes; i.e., their modeling, execution, and monitoring. Imperative, declarative, and data-driven process support approaches are evaluated and how well they support object-aware processes are investigated. A tight integration of process and data as major steps towards further maturation of process management technology is considered.

On the Usage of Labels and Icons in Business Process Modeling

Abstract: The value of business process models is dependent on the choice of graphical elements in the model and their annotation with additional textual and graphical information. This research discusses the use of text and icons for labeling the graphical constructs in a process model. The authors use two established verb classification schemes to examine the choice of activity labels in process modeling practice. Based on the author's findings, this paper synthesizes a set of twenty-five activity label categories. Proposed is a systematic approach for graphically representing these label categories through the use of graphical icons, such that the resulting process models are easier and more readily understandable by end users. The author's findings contribute to an ongoing stream of research investigating the practice of process modeling and thereby contribute to the body of knowledge about conceptual modeling quality overall.

EA Anamnesis: An Approach for Decision Making Analysis in Enterprise Architecture

Abstract: Enterprise Architecture (EA) modeling languages can express the business-to-IT-stack for an organization, showing how changes in the IT landscape impact business aspects and vice versa. Yet EA languages provide only the final architectural design, not the rationale behind this design. In earlier work, the authors presented the EA Anamnesis approach for EA rationalization. The authors discussed how EA Anamnesis forms a complement to current EA modeling languages, showing for example design alternatives, EA artifact selection criteria and the decision making strategy that was used. In this paper, the authors extend EA Anamnesis with a capability for organizational learning. In particular, the authors present an integration of two viewpoints presented in earlier work: (1) an ex-ante decision making viewpoint for rationalizing EA during decision making, which for example captures a decision and its anticipated consequences, and (2) an ex-post decision making viewpoint, which for example captures the unanticipated decision consequences, and possible adjustments in criteria. The authors use a fictitious, yet realistic, case study to illustrate our approach.

TESTAR: Tool Support for Test Automation at the User Interface Level

Abstract: Testing applications with a graphical user interface GUI is an important, though challenging and time consuming task. The state of the art in the industry are still capture and replay tools, which may simplify the recording and execution of input sequences, but do not support the tester in finding fault-sensitive test cases and leads to a huge overhead on maintenance of the test cases when the GUI changes. In earlier works the authors presented the TESTAR tool, an automated approach to testing applications at the GUI level whose objective is to solve part of the maintenance problem by automatically generating test cases based on a structure that is automatically derived from the GUI. In this paper they report on their experiences obtained when transferring TESTAR in three different industrial contexts with decreasing involvement of the TESTAR developers and increasing participation of the companies when deploying and using TESTAR during testing. The studies were successful in that they reached practice impact, research impact and give insight into ways to do innovation transfer and defines a possible strategy for taking automated testing tools into the market.