- Management and evolution of business process variants ( ), Rijksuniversiteit Groningen, 2012.
- Usability Evaluation of a Web-Based Support System for People With a Schizophrenia Diagnosis ( ), In Journal of Medical Internet Research, volume 14, 2012.
- What IS can do for Environmental Sustainability ( ), In Communications of the Association for Information Systems, volume 30, 2012.
- Policy-Based Scheduling of Cloud Services ( ), In Scalable Computing: Practice and Experience, volume 13, 2012.
- Service-Orientation and the Smart Grid: State and Trend ( ), In Service Oriented Computing and Applications, volume 6, 2012.
- Optimizing Energy Costs for Offices Connected to the Smart Grid ( ), In IEEE Transactions on Smart Grid, volume 3, 2012.
- Logic for physical space ( ), In Synthese, volume 18, 2012.
- Forward ( ), In Journal of System Assurance Engineering and Management, volume 3, 2012.
- Reduced Context Consistency Diagrams for Resolving Inconsistent Data ( ), In ICST Transactions on Ubiquitous Environments, volume 12, 2012.
- Business Process Variability: A Tool for Declarative Template Design ( ), In Service-Oriented Computing, Springer, volume 7221, 2012.
To lower both implementation time and cost, many Business Process Management tools use process templates to implement highly recurring processes. However, in order for such templates to be used, a process has to adhere substantially to the template. Therefore, current practice for processes which deviate more than marginally is to either manually implement them at high costs, or for the business to inflexibly comply to the template. In this paper, we describe a tool which demonstrates a variability based solution to process template definition.
- A Machine Learning Approach for Identifying and Classifying Faults in Wireless Sensor Networks ( ), In 10th IEEE International Conference on Embedded and Ubiquitous Computing, 2012.
- Fault Detection in Wireless Sensor Networks: a Hybrid Approach ( ), In ACM Conference on Information Processing in Sensor Networks (IPSN'12 POSTER Session), 2012.
- A Statistical Analysis of Power Grid Vulnerabilities ( ), In Workshops of The seventh CRITIS Conference on Critical Information Infrastructures Security, 2012.
- Service Ecologies for Home/Building Automation ( ), In 10th Int. IFAC Symposium on Robot Control, 2012.
- Adaptive Game-based Agent Negotiation in Deregulated Energy Markets ( ), In Workshop on Adaptive Collaboration at (CTS 2012), 2012.
- An Agent-based Application to Enable Deregulated Energy Markets ( ), In IEEE Computer Software and Applications Conference, 2012.
- Automatic Detection of Business Process Interference ( ), In International Workshop on Knowledge-intensive Business Processes, 2012.
- Beyond Indoor Presence Monitoring with Simple Sensors ( ), In International Conference on Pervasive and Embedded Computing and Communication Systems, 2012.
- Cost-efficient Context-aware Rule Maintenance ( ), In Workshop on Context Modeling and Reasoning, 2012.
- Imperative versus declarative process variability: Why Choose? ( ), 2012.
Variability is a powerful abstraction in software engineering that allows managing product lines and business processes requiring great deals of change, customization and adaptation. In the field of Business Process Management (BPM) the increasing deployment of workflow engines having to handle an increasing number of instances has prompted for the strong need for variability techniques. The idea is that parts of a business process remain either open to change, or notfully dened, in order to support several versions of the same process depending on the intended use or execution context. The goal is to support two major challenges for BPM: re-usability and flexibility. Existing approaches are broadly categorized as Imperative or Declarative. We propose Process Variability through Declarative and Imperative techniques (PVDI), a variability framework which utilizes temporal logic to represent the basic structure of a process, leaving other choices open for later customization and adaptation. We show how both approaches to variability excel for different aspects of the modeling and we highlight PVDI's ability to take the best of both worlds. Furthermore, by enriching the process modeling environment with graphical elements, the complications of temporal logic are hidden from the user. To show the practical viability of PVDI, we present tooling supporting the full PVDI lifecycle and test its feasibility in theform of a performance evaluation.