The presence of autonomous systems is growing at a fast pace and it is impacting many aspects of our lives. Designed to learn and act independently, these systems operate and perform decision-making without human intervention. However, they lack the ability to incorporate users’ ethical preferences, which are unique for each individual in society and are required to personalize the decision-making processes. This reduces user trust and prevents autonomous systems from behaving according to the moral beliefs of their end-users. When multiple systems interact with differing ethical preferences, they must negotiate to reach an agreement that satisfies the ethical beliefs of all the parties involved and adjust their behavior consequently. To address this challenge, this paper proposes RobEthiChor , an approach that enables autonomous systems to incorporate user ethical preferences and contextual factors into their decision-making through ethics-based negotiation. RobEthiChor features a domain-agnostic reference architecture for designing autonomous systems capable of ethic-based negotiating. The paper also presents RobEthiChor-Ros , an implementation of RobEthiChor within the Robot Operating System (ROS), which can be deployed on robots to provide them with ethics-based negotiation capabilities. To evaluate our approach, we deployed RobEthiChor-Ros on real robots and ran scenarios where a pair of robots negotiate upon resource contention. Experimental results demonstrate the feasibility and effectiveness of the system in realizing ethics-based negotiation. RobEthiChor allowed robots to reach an agreement in more than 73 % of the scenarios with an acceptable negotiation time (0.67s on average). Experiments also demonstrate that the negotiation approach implemented in RobEthiChor is scalable.

This paper briefly outlines a high-level architecture of a context-aware ethics-based negotiation approach in which autonomous systems utilize user ethical profiles, together with contextual factors and user status, to control their autonomy while collaboratively negotiating to reach an ethical agreement that satisfies the ethical beliefs of all parties involved.

Migrating from a legacy monolithic system to a microservice architecture is a complex and time-consuming process. Software engineers may strongly benefit from automated support to identify a high-cohesive and loose-coupled set of microservices with proper granularity. The automated approach proposed in this paper extracts microservices by using graph clustering and combinatorial optimization to maximize cohesion and minimize coupling. The approach performs static analysis of the code to obtain a graph representation of the monolithic system. Then, it uses graph clustering to detect high-cohesive communities of nodes using the Louvain community algorithm. In parallel, the tool clusters the domain entities (i.e., classes representing uniquely identifiable concepts in a system domain) within bounded contexts to identify the required service granularity. Finally, it uses combinatorial optimization to minimize the coupling, hence deriving the microservice architecture. The approach is fully implemented. We applied it over four different monolithic systems and found valuable results. We evaluated the identified architectures through cohesion and coupling metrics, along with a comparison with other state-of-the-art approaches based on features such as granularity level, number of produced services, and methods applied. The approach implementation and the experimental results are publicly available.

Abstract Modern technologies and emerging wireless communication solutions in the Information and Communications Technology (ICT) world are empowering the spread of the most disparate ready‐to‐use software services distributed over the globe and accessed by an increasing number of users. This state of affairs encourages the development of systems based on the reuse of existing services through composition approaches, notably choreographies. Also Public Administrations are driven towards a digitalization process which exploits composition approaches to build complex and interoperable systems that can be remotely accessed by citizens and authorities. However, an automatic support is needed in order to realize the service composition and the distributed coordination logic that enforces the correct choreography realization. Moreover, the need for building dynamic and user‐centered systems calls for the realization of choreographies capable to adjust their behavior to the surrounding context. This work presents our proposal for addressing the choreography realization problem, by describing an automated process for the synthesis of choreography‐based systems. The synthesized systems are location‐aware and able to adapt the services' interaction according to the user's needs and context conditions. We show and evaluate our approach at work on a real use case scenario in the Public Administration domain.