Second Workshop on Modelling of Objects, Components and Agents

This report contains the proceedings of the workshop Modelling of Objects, Components, and Agents (MOCA'02), August 26-27, 2002.The workshop is organized by the 'Coloured Petri Net' Group at the University of Aarhus, Denmark and the 'Theoretical Foundations of Computer Science' Group at the University of Hamburg, Germany. The homepage of the workshop is: http://www.daimi.au.dk/CPnets/workshop02

Developing a distributed electronic health-record store for India

The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

Agents and Robots for Reliable Engineered Autonomy

This book contains the contributions of the Special Issue entitled "Agents and Robots for Reliable Engineered Autonomy". The Special Issue was based on the successful first edition of the "Workshop on Agents and Robots for reliable Engineered Autonomy" (AREA 2020), co-located with the 24th European Conference on Artificial Intelligence (ECAI 2020). The aim was to bring together researchers from autonomous agents, as well as software engineering and robotics communities, as combining knowledge from these three research areas may lead to innovative approaches that solve complex problems related to the verification and validation of autonomous robotic systems

A Runtime Verification and Validation Framework for Self-Adaptive Software

The concepts that make self-adaptive software attractive also make it more difficult for users to gain confidence that these systems will consistently meet their goals under uncertain context. To improve user confidence in self-adaptive behavior, machine-readable conceptual models have been developed to instrument the adaption behavior of the target software system and primary feedback loop. By comparing these machine-readable models to the self-adaptive system, runtime verification and validation may be introduced as another method to increase confidence in self-adaptive systems; however, the existing conceptual models do not provide the semantics needed to institute this runtime verification or validation. This research confirms that the introduction of runtime verification and validation for self-adaptive systems requires the expansion of existing conceptual models with quality of service metrics, a hierarchy of goals, and states with temporal transitions. Based on this expanded semantics, runtime verification and validation was introduced as a second-level feedback loop to improve the performance of the primary feedback loop and quantitatively measure the quality of service achieved in a state-based, self-adaptive system. A web-based purchasing application running in a cloud-based environment was the focus of experimentation. In order to meet changing customer purchasing demand, the self-adaptive system monitored external context changes and increased or decreased available application servers. The runtime verification and validation system operated as a second-level feedback loop to monitor quality of service goals based on internal context, and corrected self-adaptive behavior when goals are violated. Two competing quality of service goals were introduced to maintain customer satisfaction while minimizing cost. The research demonstrated that the addition of a second-level runtime verification and validation feedback loop did quantitatively improve self-adaptive system performance even with simple, static monitoring rules