Using formal metamodels to check consistency of functional views in information systems specification

UML notations require adaptation for applications such as Information Systems (IS). Thus we have defined IS-UML. The purpose of this article is twofold. First, we propose an extension to this language to deal with functional aspects of IS. We use two views to specify IS transactions: the first one is defined as a combination of behavioural UML diagrams (collaboration and state diagrams), and the second one is based on the definition of specific classes of an extended class diagram. The final objective of the article is to consider consistency issues between the various diagrams of an IS-UML specification. In common with other UML languages, we use a metamodel to define IS-UML. We use class diagrams to summarize the metamodel structure and a formal language, B, for the full metamodel. This allows us to formally express consistency checks and mapping rules between specific metamodel concepts. (C) 2007 Elsevier B.V. All rights reserved

Lessons from Formally Verified Deployed Software Systems (Extended version)

The technology of formal software verification has made spectacular advances, but how much does it actually benefit the development of practical software? Considerable disagreement remains about the practicality of building systems with mechanically-checked proofs of correctness. Is this prospect confined to a few expensive, life-critical projects, or can the idea be applied to a wide segment of the software industry? To help answer this question, the present survey examines a range of projects, in various application areas, that have produced formally verified systems and deployed them for actual use. It considers the technologies used, the form of verification applied, the results obtained, and the lessons that can be drawn for the software industry at large and its ability to benefit from formal verification techniques and tools. Note: a short version of this paper is also available, covering in detail only a subset of the considered systems. The present version is intended for full reference.Comment: arXiv admin note: text overlap with arXiv:1211.6186 by other author

The use of data-mining for the automatic formation of tactics

This paper discusses the usse of data-mining for the automatic formation of tactics. It was presented at the Workshop on Computer-Supported Mathematical Theory Development held at IJCAR in 2004. The aim of this project is to evaluate the applicability of data-mining techniques to the automatic formation of tactics from large corpuses of proofs. We data-mine information from large proof corpuses to find commonly occurring patterns. These patterns are then evolved into tactics using genetic programming techniques

A proof repository for formal verification of software

We present a proof repository that provides a uniform theorem proving interface to virtually any first-order theorem prover. Instead of taking the greatest common divisor of features supported by the first-order theorem provers, the design allows us to support any extension of the logic that can be expressed in first-order logic. If a theorem prover has native support for such a logic, this is exploited. If the prover has no such support, the repository automatically uses the first-order encoding of the extension. A built-in proof assistant is provided that allows the user to manually guide the proving process when all provers fail to prove a theorem. To prove sub-theorems, the proof assistant is able to use the repository’s full capabilities. The repository also maintains a database of proven theorems. When a requested theorem has been proved before, the result from the database is re-used instead of reconstructing the proof all over again. To test the repository, we constructed a tool for static verification of a basic programming language. This language is also described in this paper

A proof repository for formal verification of software

We present a proof repository that provides a uniform theorem proving interface to virtually any first-order theorem prover. Instead of taking the greatest common divisor of features supported by the first-order theorem provers, the design allows us to support any extension of the logic that can be expressed in first-order logic. If a theorem prover has native support for such a logic, this is exploited. If the prover has no such support, the repository automatically uses the first-order encoding of the extension. A built-in proof assistant is provided that allows the user to manually guide the proving process when all provers fail to prove a theorem. To prove sub-theorems, the proof assistant is able to use the repository’s full capabilities. The repository also maintains a database of proven theorems. When a requested theorem has been proved before, the result from the database is re-used instead of reconstructing the proof all over again. To test the repository, we constructed a tool for static verification of a basic programming language. This language is also described in this paper

Collaborative Verification-Driven Engineering of Hybrid Systems

Hybrid systems with both discrete and continuous dynamics are an important model for real-world cyber-physical systems. The key challenge is 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. Often, hybrid systems are rather complex in that they require expertise from many domains (e.g., robotics, control systems, computer science, software engineering, and mechanical engineering). Moreover, despite the remarkable progress in automating formal verification of hybrid systems, the construction of proofs of complex systems often requires nontrivial human guidance, since hybrid systems verification tools solve undecidable problems. It is, thus, not uncommon for development and 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) graphical (UML) and textual modeling of 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