The adoption of blockchain based distributed ledgers is growing fast due to their ability to provide reliability, integrity, and auditability without trusted entities. One of the key capabilities of these emerging platforms is the ability to create self-enforcing smart contracts. However, the development of smart contracts has proven to be error-prone in practice, and as a result, contracts deployed on public platforms are often riddled with security vulnerabilities. This issue is exacerbated by the design of these platforms, which forbids updating contract code and rolling back malicious transactions. In light of this, it is crucial to ensure that a smart contract is secure before deploying it and trusting it with significant amounts of cryptocurrency. To this end, we introduce the VeriSolid framework for the formal verification of contracts that are specified using a transition-system based model with rigorous operational semantics. Our model-based approach allows developers to reason about and verify contract behavior at a high level of abstraction. VeriSolid allows the generation of Solidity code from the verified models, which enables the correct-by-design development of smart contracts.

The focus of this work is the on-demand resource provisioning in cloud computing, which is commonly referred to as cloud elasticity. Although a lot of effort has been invested in developing systems and mechanisms that enable elasticity, the elasticity decision policies tend to be designed without quantifying or guaranteeing the quality of their operation. We present an approach towards the development of more formalized and dependable elasticity policies. We make two distinct contributions. First, we propose an extensible approach to enforcing elasticity through the dynamic instantiation and online quantitative verification of Markov Decision Processes (MDP) using probabilistic model checking. Second, various concrete elasticity models and elasticity policies are studied. We evaluate the decision policies using traces from a real NoSQL database cluster under constantly evolving external load. We reason about the behaviour of different modeling and elasticity policy options and we show that our proposal can improve upon the state-of-the-art in significantly decreasing under-provisioning while avoiding over-provisioning.

In this case study, we apply the architecture-based design approach to the control software of the CubETH satellite. Architectures are a means for ensuring global coordination properties and thus, achieving correctness of complex systems by construction. We illustrate the following three steps of the design approach: 1) definition of a domain-specific taxonomy of architecture styles; 2) design of the software model by applying architectures to enforce the required properties; 3) deadlock-freedom analysis of the resulting model. We provide a taxonomy of architecture styles for satellite on-board software, formally defined by architecture diagrams in the BIP component-based framework. We show how architectures are instantiated from the diagrams and applied to a set of atomic components. Deadlock-freedom of the resulting model is verified using DFinder from the BIP tool-set. We provide additional validation of our approach by using the nuXmv model checker to verify that the properties enforced by the architectures are, indeed, satisfied by the model.

The early validation of requirements aims to reduce the need for the high-cost validation testing and corrective measures at late development stages. This work introduces a systematic process for the unambiguous specification of system requirements and the guided derivation of formal properties, which should be implied by the system 's structure and behavior in conjunction with its external stimuli. This rigorous design takes place through the incremental construction of a model using the BIP (Behavior-Interaction-Priorities) component framework. It allows building complex designs by composing simpler reusable designs enforcing given properties. If some properties are neither enforced nor verified, the model is refined or certain requirements are revised. A validated model provides evidence of requirements' consistency and design correctness. The process is semi-automated through a new tool and existing verification tools. Its effectiveness was evaluated on a set of requirements for the control software of the CubETH nanosatellite and an extract of software requirements for a Low Earth Orbit observation satellite. Our experience and obtained results helped in identifying open challenges for applying the method in industrial context. These challenges concern with the domain knowledge representation, the expressiveness of used specification languages, the library of reusable designs and scalability.

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