Smart contracts (SCs) are software systems that monitor and control the execution of legal contracts to ensure compliance with the contracts' terms and conditions. They often exploit Internet-of-Things technologies to support their monitoring functions, and blockchain technology to ensure the integrity of their data. Ethereum and business blockchain platforms, such as Hyperledger Fabric, are popular choices for SC development. However, there is a gap in the knowledge of SCs between developers and legal experts. Symboleo is a formal specification language for legal contracts that was introduced to address this issue. Symboleo specifications directly encode legal concepts such as parties, obligations, and powers. In this paper, we propose a tool-supported method for translating Symboleo specifications into smart contracts. We have extended the current Symboleo IDE, implemented the ontology and semantics of Symboleo into a reusable library, and developed the Symboleo2SC tool to generate Hyperledger Fabric code exploiting this library. Symboleo2SC was evaluated with three sample contracts. The results shows that legal contract specifications in Symboleo can be fully converted to SCs for monitoring purposes. Moreover, Symboleo2SC helps simplify the SC development process, saves development effort, and helps reduce risks of coding errors.

Many Cyber-Physical Systems (CPSs) today are self-adaptive, in order to handle frequent changes in environmental conditions and requirements. In CPSs, goal-based reasoning is often used to include stakeholder and social concerns in decision making during design and runtime adaptation activities. To better support some of these activities, arithmetic semantics for goal models were proposed to enable the generation of mathematical functions usable by systems. However, goal models often allow invalid combinations of alternatives, which can be prevented by companion feature models. In this paper, to enable the generation of valid and optimal configurations for adaptive CPSs, we propose new arithmetic semantics for feature models that enable their transformations to mathematical functions (in several programming languages) further restricting the ones generated from goal models. The composition of feature and goal functions results in a smaller design space, leading to fewer but valid solutions that can be generated (e.g., through optimization) and used in simulations and running adaptive CPSs with social concerns. Finally, a simulation model in SysML is proposed in this paper to demonstrate the feasibility and usefulness of this composition.

Socio-cyber-physical systems (SCPSs) are cyber-physical systems (CPSs) with a socio-technical system (STS) aspect. Several SCPSs need to adapt dynamically to changing situations in order to reach an optimal symbiosis with users in their contexts. Tailoring requirements engineering activities and modeling techniques is needed for developing SCPSs and supporting their runtime adaptability. The proposed thesis aims to combine a common way of modeling STSs (i.e., goal modeling with the Goal-oriented Requirement Language - GRL) to a conventional way of modeling CPSs (i.e., SysML and feature models) in order to integrate social concepts early in SCPS requirements, design, simulation, and implementation activities. To help guarantee system quality and compliance during both design time and runtime adaptations, the thesis proposes to translate goal and feature models to mathematical functions used to validate possible design and adaptation alternatives both during simulations at design time and adaptations at runtime. These functions can be used outside goal modeling tools and be combined to SysML models, simulations, problem solvers, and implementation tools. Furthermore, an integration between GRL and SysML models via a third-party requirements management system is proposed in order to strengthen system traceability and help ensure that stakeholder goals were considered properly during the SCPS development process.

The Systems Modeling Language (SysML) is a popular and standardized UML profile for systems engineering applications. In addition to seven conventional UML diagram types, SysML supports requirement diagrams and tables that can be used to capture requirements, their attributes, and their relationships. However, several important concepts such as goals and contributions are not predefined in SysML, hindering the reasoning about tradeoffs and adaptation, especially in emerging socio-cyber-physical systems such as smart cities. In this paper, we provide a preliminary investigation of different ways of combining SysML with the User Requirements Notation (URN), a standard that focuses on the modeling and analysis of goals and scenarios. We argue that SysML and URN are complementary and synergistic, and that their combination enables new requirements modeling, analysis, and management opportunities for new types of systems. Examples of potential integration approaches are discussed, briefly assessed, and illustrated with existing tools for SysML, URN, and requirements management.