Abstract-The use of runtime verification, as a lightweight approach to guarantee properties of systems, has been increasingly employed on real-life software. In this paper, we present the tool LARVA, for the runtime verification of properties of Java programs, including real-time properties. Properties can be expressed in a number of notations, including timed-automata enriched with stopwatches, Lustre, and a subset of the duration calculus. The tool has been successfully used on a number of case-studies, including an industrial system handling financial transactions. LARVA also performs analysis of real-time properties, to calculate, if possible, an upper-bound on the memory and temporal overheads induced by monitoring. Moreover, through property analysis, LARVA assesses the impact of slowing down the system through monitoring, on the satisfaction of the properties.

Abstract. Given the intractability of exhaustively verifying software, the use of runtime-verification, to verify single execution paths at runtime, is becoming popular. Although the use of runtime verification is increasing in industrial settings, various challenges still are to be faced to enable it to spread further. We present dynamic communicating automata with timers and events to describe properties of systems, implemented in Larva, an event-based runtime verification tool for monitoring temporal and contextual properties of Java programs. The combination of timers with dynamic automata enables the straightforward expression of various properties, including replication of properties, as illustrated in the use of Larva for the runtime monitoring of a real life case studyan online transaction system for credit card. The features of Larva are also benchmarked and compared to a number of other runtime verification tools, to assess their respective strengths in property expressivity and overheads induced through monitoring.

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In this paper we propose a formal language for writing electronic contracts, based on the deontic notions of obligation, permission, and prohibition. We take an ought-to-do approach, where deontic operators are applied to actions instead of state-of-affairs. We propose an extension of the μ-calculus in order to capture the intuitive meaning of the deontic notions and to express concurrent actions. We provide a translation of the contract language into the logic, the semantics of which faithfully captures the meaning of obligation, permission and prohibition. We also show how our language captures most of the intuitive desirable properties of electronic contracts, as well as how it avoids most of the classical paradoxes of deontic logic. We finally show its applicability on a contract example.

Even though many attempts have been made to define the boundary between decidable and undecidable hybrid systems, the affair is far from being resolved. More and more low dimensional systems are being shown to be undecidable with respect to reachability, and many open problems in between are being discovered. In this paper, we present various two dimensional hybrid systems for which the reachability problem is undecidable. We show their undecidability by simulating Minsky machines. Their proximity to the decidability frontier is understood by inspecting the most parsimonious constraints necessary to make reachability over these automata decidable. We also show that for other two dimensional systems, the reachability question remains unanswered, by proving that it is as hard as the reachability problem for piecewise affine maps on the real line, which is a well known open problem.

Data minimisation is a privacy-enhancing principle considered as one of the pillars of personal data regulations. This principle dictates that personal data collected should be no more than necessary for the specific purpose consented by the user. In this paper we study data minimisation from a programming language perspective. We assume that a given program embodies the purpose of data collection, and define a data minimiser as a pre-processor for the input which reduces the amount of information available to the program without compromising its functionality. In this context we study formal definitions of data minimisation, present different mechanisms and architectures to ensure data minimisation, and provide a procedure to synthesise a correct data minimiser for a given program.

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