This paper investigates the role of AI assistants, specifically OpenAI's ChatGPT, in teaching formal methods (FM) to undergraduate students, using the B-method as a formal specification technique. While existing studies demonstrate the effectiveness of AI in coding tasks, no study reports on its impact on formal specifications. We examine whether ChatGPT provides an advantage when writing B-specifications and analyse student trust in its outputs. Our findings indicate that the AI does not help students to enhance the correctness of their specifications, with low trust correlating to better outcomes. Additionally, we identify a behavioural pattern with which to interact with ChatGPT which may influence the correctness of B-specifications.

Abstract StartSet l o g EndSet { l o g } $\{log\}$ (read ‘setlog’) was born as a Constraint Logic Programming (CLP) language where sets and binary relations are first-class citizens, thus fostering set programming. Internally, StartSet l o g EndSet { l o g } $\{log\}$ is a constraint satisfiability solver implementing decision procedures for several fragments of set theory. Hence, StartSet l o g EndSet { l o g } $\{log\}$ can be used as a declarative, set, logic programming language and as an automated theorem prover for set theory. Over time StartSet l o g EndSet { l o g } $\{log\}$ has been extended with some components integrated to the satisfiability solver thus providing a formal verification environment. In this paper we make a comprehensive presentation of this environment which includes a language for the description of state machines based on set theory, an interactive environment for the execution of functional scenarios over state machines, a generator of verification conditions for state machines, automated verification of state machines, and test case generation. State machines are both, programs and specifications; exactly the same code works as a program and as its specification. In this way, with a few additions, a CLP language turned into a seamlessly integrated programming and automated proof system.

This paper revisits the Brewer-Nash security policy model inspired by ethical Chinese Wall policies. We draw attention to the fact that write access can be revoked in the Brewer-Nash model. The semantics of write access were underspecified originally, leading to multiple interpretations for which we provide a modern operational semantics. We go on to modernise the analysis of information flow in the Brewer-Nash model, by adopting a more precise definition adapted from Kessler. For our modernised reformulation, we provide full mechanised coverage for all theorems proposed by Brewer & Nash. Most theorems are established automatically using the tool {log} with the exception of a theorem regarding information flow, which combines a lemma in {log} with a theorem mechanised in Coq. Having covered all theorems originally posed by Brewer-Nash, achieving modern precision and mechanisation, we propose this work as a step towards a methodology for automated checking of more complex security policy models.

This tool paper presents the design and tool-support of Messir, an approach centered on textual domain-specific languages supported by our open-source UML requirements engineering tool, named Excalibur. The novelty of our approach is the actual integration in a single workbench (Excalibur) of textual DSLs richly covering the requirements and analysis phases, i.e. improved use-cases, environment, conceptual and operations models; and the read-only visualisation of the requirements with UML-compliant views; and the generation of scientific requirements analysis documents in LATEX; and the formal simulation of test cases requirements.

This paper presents an implementation framework, called CAA-DRIP, that has been defined to allow a straightforward implementation of dependable distributed applications designed using the coordinated atomic action (CAA) paradigm. CAAs provide a coherent set of concepts adapted to the design of fault tolerant distributed systems that includes: structured transactions, distribution, cooperation, competition, and forward and backward error recovery mechanisms triggered by exceptions. DRIP (dependable remote interacting processes) is an efficient Java implementation framework, which provides support for implementing "dependable multiparty interactions (DMI)" which includes a general exception handling mechanism. As DMI has a softer exception handling semantics with respect to CAA semantics, a CAA design can be implemented by DRIP. The aim of the CAA-DRIP framework is to provide a set of Java classes that allows programmers to implement only the semantics of CAAs with the same terminology and concepts at the design and implementation levels. The new framework simplifies the implementation phase and at the same time reduces the size of the final system since it requires fewer number of instances for creating a CAA at runtime. Details of these improvements as well as a precise description of the CAAs behaviour in terms of state charts, which is used as a reference model to define the CAA-DRIP framework, are presented in this paper