An experimental Study using ACSL and Frama-C to formulate and verify Low-Level Requirements from a DO-178C compliant Avionics Project

Safety critical avionics software is a natural application area for formal verification. This is reflected in the formal method's inclusion into the certification guideline DO-178C and its formal methods supplement DO-333. Airbus and Dassault-Aviation, for example, have conducted studies in using formal verification. A large German national research project, Verisoft XT, also examined the application of formal methods in the avionics domain. However, formal methods are not yet mainstream, and it is questionable if formal verification, especially formal deduction, can be integrated into the software development processes of a resource constrained small or medium enterprise (SME). ESG, a Munich based medium sized company, has conducted a small experimental study on the application of formal verification on a small portion of a real avionics project. The low level specification of a software function was formalized with ACSL, and the corresponding source code was partially verified using Frama-C and the WP plugin, with Alt-Ergo as automated prover. We established a couple of criteria which a method should meet to be fit for purpose for industrial use in SME, and evaluated these criteria with the experience gathered by using ACSL with Frama-C on a real world example. The paper reports on the results of this study but also highlights some issues regarding the method in general which, in our view, will typically arise when using the method in the domain of embedded real-time programming.Comment: In Proceedings F-IDE 2015, arXiv:1508.0338

Formally verifying Ada programs which use real number types

Formal verification is applied to programs which use real number arithmetic operations (mathematical programs). Formal verification of a program P consists of creating a mathematical model of F, stating the desired properties of P in a formal logical language, and proving that the mathematical model has the desired properties using a formal proof calculus. The development and verification of the mathematical model are discussed

Formal verification of AI software

The application of formal verification techniques to Artificial Intelligence (AI) software, particularly expert systems, is investigated. Constraint satisfaction and model inversion are identified as two formal specification paradigms for different classes of expert systems. A formal definition of consistency is developed, and the notion of approximate semantics is introduced. Examples are given of how these ideas can be applied in both declarative and imperative forms

A Vision of Collaborative Verification-Driven Engineering of Hybrid Systems

Abstract. Hybrid systems with both discrete and continuous dynamics are an important model for real-world physical systems. The key challenge is how to ensure their correct functioning w.r.t. safety requirements. Promising techniques to ensure safety seem to be model-driven engineering to develop hybrid systems in a well-defined and traceable manner, and formal verification to prove their correctness. Their combination forms the vision of verification-driven engineering. Despite the remarkable progress in automating formal verification of hybrid systems, the construction of proofs of complex systems often requires significant human guidance, since hybrid systems verification tools solve undecidable problems. It is thus not uncommon for verification teams to consist of many players with diverse expertise. This paper introduces a verification-driven engineering toolset that extends our previous work on hybrid and arithmetic verification with tools for (i) modeling hybrid systems, (ii) exchanging and comparing models and proofs, and (iii) managing verification tasks. This toolset makes it easier to tackle large-scale verification tasks.

From Event-B models to Dafny code contracts

International audienceThe constructive approach to software correctness aims at formal modelling and verification of the structure and behaviour of a system in different levels of abstraction. In contrast, the analytical approach to software verification focuses on code level correctness and its verification. Therefore it would seem that the constructive and analytical approaches should complement each other well. To demonstrate this idea we present a case for linking two existing verification methods, Event-B (constructive) and Dafny (analytical). This approach combines the power of Event-B abstraction and its stepwise refinement with the verification capabilities of Dafny. We presented a small case study to demonstrate this approach and outline of the rules for transforming Event-B events to Dafny contracts. Finally, a tool for automatic generation of Dafny contracts from Event-B formal models is presented

Simulator Semantics for System Level Formal Verification

Many simulation based Bounded Model Checking approaches to System Level Formal Verification (SLFV) have been devised. Typically such approaches exploit the capability of simulators to save computation time by saving and restoring the state of the system under simulation. However, even though such approaches aim to (bounded) formal verification, as a matter of fact, the simulator behaviour is not formally modelled and the proof of correctness of the proposed approaches basically relies on the intuitive notion of simulator behaviour. This gap makes it hard to check if the optimisations introduced to speed up the simulation do not actually omit checking relevant behaviours of the system under verification. The aim of this paper is to fill the above gap by presenting a formal semantics for simulators.Comment: In Proceedings GandALF 2015, arXiv:1509.0685

Verifying the Safety of a Flight-Critical System

This paper describes our work on demonstrating verification technologies on a flight-critical system of realistic functionality, size, and complexity. Our work targeted a commercial aircraft control system named Transport Class Model (TCM), and involved several stages: formalizing and disambiguating requirements in collaboration with do- main experts; processing models for their use by formal verification tools; applying compositional techniques at the architectural and component level to scale verification. Performed in the context of a major NASA milestone, this study of formal verification in practice is one of the most challenging that our group has performed, and it took several person months to complete it. This paper describes the methodology that we followed and the lessons that we learned.Comment: 17 pages, 5 figure