Rodin: an open toolset for modelling and reasoning in Event-B

Event-B is a formal method for system-level modelling and analysis. Key features of Event-B are the use of set theory as a modelling notation, the use of refinement to represent systems at different abstraction levels and the use of mathematical proof to verify consistency between refinement levels. In this article we present the Rodin modelling tool that seamlessly integrates modelling and proving. We outline how the Event-B language was designed to facilitate proof and how the tool has been designed to support changes to models while minimising the impact of changes on existing proofs. We outline the important features of the prover architecture and explain how well-definedness is treated. The tool is extensible and configurable so that it can be adapted more easily to different application domains and development methods

An open extensible tool environment for Event-B

Abstract. We consider modelling indispensable for the development of complex systems. Modelling must be carried out in a formal notation to reason and make meaningful conjectures about a model. But formal modelling of complex systems is a difficult task. Even when theorem provers improve further and get more powerful, modelling will remain difficult. The reason for this that modelling is an exploratory activity that requires ingenuity in order to arrive at a meaningful model. We are aware that automated theorem provers can discharge most of the onerous trivial proof obligations that appear when modelling systems. In this article we present a modelling tool that seamlessly integrates modelling and proving similar to what is offered today in modern integrated development environments for programming. The tool is extensible and configurable so that it can be adapted more easily to different application domains and development methods.

HeteroGenius: A Framework for Hybrid Analysis of Heterogeneous Software Specifications

Nowadays, software artifacts are ubiquitous in our lives being an essential part of home appliances, cars, cell phones, and even in more critical activities like aeronautics and health sciences. In this context software failures may produce enormous losses, either economical or, in the worst case, in human lives. Software analysis is an area in software engineering concerned with the application of diverse techniques in order to prove the absence of errors in software pieces. In many cases different analysis techniques are applied by following specific methodological combinations that ensure better results. These interactions between tools are usually carried out at the user level and it is not supported by the tools. In this work we present HeteroGenius, a framework conceived to develop tools that allow users to perform hybrid analysis of heterogeneous software specifications. HeteroGenius was designed prioritising the possibility of adding new specification languages and analysis tools and enabling a synergic relation of the techniques under a graphical interface satisfying several well-known usability enhancement criteria. As a case-study we implemented the functionality of Dynamite on top of HeteroGenius.Comment: In Proceedings LAFM 2013, arXiv:1401.056

Practical Theory Extension in Event-B

Abstract. The Rodin tool for Event-B supports formal modelling and proof using a mathematical language that is based on predicate logic and set theory. Although Rodin has in-built support for a rich set of operators and proof rules, for some application areas there may be a need to extend the set of operators and proof rules supported by the tool. This paper outlines a new feature of the Rodin tool, the theory component, that allows users to extend the mathematical language supported by the tool. Using theories, Rodin users may define new data types and polymorphic operators in a systematic and practical way. Theories also allow users to extend the proof capabilities of Rodin by defining new proof rules that get incorporated into the proof mechanisms. Soundness of new definitions and rules is provided through validity proof obligations.

Reasoning about order errors in interaction

Reliability of an interactive system depends on users as well as the device implementation. User errors can result in catastrophic system failure. However, work from the field of cognitive science shows that systems can be designed so as to completely eliminate whole classes of user errors. This means that user errors should also fall within the remit of verification methods. In this paper we demonstrate how the HOL theorem prover [7] can be used to detect and prove the absence of the family of errors known as order errors. This is done by taking account of the goals and knowledge of users. We provide an explicit generic user model which embodies theory from the cognitive sciences about the way people are known to act. The user model describes action based on user communication goals. These are goals that a user adopts based on their knowledge of the task they must perform to achieve their goals. We use a simple example of a vending machine to demonstrate the approach. We prove that a user does achieve their goal for a particular design of machine. In doing so we demonstrate that communication goal based errors cannot occur

Mining State-Based Models from Proof Corpora

Interactive theorem provers have been used extensively to reason about various software/hardware systems and mathematical theorems. The key challenge when using an interactive prover is finding a suitable sequence of proof steps that will lead to a successful proof requires a significant amount of human intervention. This paper presents an automated technique that takes as input examples of successful proofs and infers an Extended Finite State Machine as output. This can in turn be used to generate proofs of new conjectures. Our preliminary experiments show that the inferred models are generally accurate (contain few false-positive sequences) and that representing existing proofs in such a way can be very useful when guiding new ones.Comment: To Appear at Conferences on Intelligent Computer Mathematics 201