Runtime Contracts Checker: Increasing Robustness of Component-Based Software Systems

Software Systems are becoming increasingly complex leading to new Validation &Verification challenges. Model checking and testing techniques are used at development time while runtime verification aims to verify that a system satisfies a given property at runtime. This second technique complements the first one. This paper presents a runtime contract checker (RCC) which checks a component-based software system's contracts defined at design phase. We address embedded systems whose software components are designed by Unified Modelling Language-State Machines (UML-SM) and their internal information can be observable in terms of model elements at runtime. Our previous research work, CRESCO (C++ REflective State-Machines based observable software COmponents) framework, generates software components that provide this observability. The checker uses software components' internal status information to check system level safety contracts. The checker detects when a system contract is violated and starts a safeStop process to prevent the hazardous scenario. Thus, the robustness of the system is increased

Compositional Verification for Autonomous Systems with Deep Learning Components

As autonomy becomes prevalent in many applications, ranging from recommendation systems to fully autonomous vehicles, there is an increased need to provide safety guarantees for such systems. The problem is difficult, as these are large, complex systems which operate in uncertain environments, requiring data-driven machine-learning components. However, learning techniques such as Deep Neural Networks, widely used today, are inherently unpredictable and lack the theoretical foundations to provide strong assurance guarantees. We present a compositional approach for the scalable, formal verification of autonomous systems that contain Deep Neural Network components. The approach uses assume-guarantee reasoning whereby {\em contracts}, encoding the input-output behavior of individual components, allow the designer to model and incorporate the behavior of the learning-enabled components working side-by-side with the other components. We illustrate the approach on an example taken from the autonomous vehicles domain

Requirements Analysis of a Quad-Redundant Flight Control System

In this paper we detail our effort to formalize and prove requirements for the Quad-redundant Flight Control System (QFCS) within NASA's Transport Class Model (TCM). We use a compositional approach with assume-guarantee contracts that correspond to the requirements for software components embedded in an AADL system architecture model. This approach is designed to exploit the verification effort and artifacts that are already part of typical software verification processes in the avionics domain. Our approach is supported by an AADL annex that allows specification of contracts along with a tool, called AGREE, for performing compositional verification. The goal of this paper is to show the benefits of a compositional verification approach applied to a realistic avionics system and to demonstrate the effectiveness of the AGREE tool in performing this analysis.Comment: Accepted to NASA Formal Methods 201

A Concurrent Perspective on Smart Contracts

In this paper, we explore remarkable similarities between multi-transactional behaviors of smart contracts in cryptocurrencies such as Ethereum and classical problems of shared-memory concurrency. We examine two real-world examples from the Ethereum blockchain and analyzing how they are vulnerable to bugs that are closely reminiscent to those that often occur in traditional concurrent programs. We then elaborate on the relation between observable contract behaviors and well-studied concurrency topics, such as atomicity, interference, synchronization, and resource ownership. The described contracts-as-concurrent-objects analogy provides deeper understanding of potential threats for smart contracts, indicate better engineering practices, and enable applications of existing state-of-the-art formal verification techniques.Comment: 15 page