LTLf and LDLf Monitoring: A Technical Report

Runtime monitoring is one of the central tasks to provide operational decision support to running business processes, and check on-the-fly whether they comply with constraints and rules. We study runtime monitoring of properties expressed in LTL on finite traces (LTLf) and in its extension LDLf. LDLf is a powerful logic that captures all monadic second order logic on finite traces, which is obtained by combining regular expressions and LTLf, adopting the syntax of propositional dynamic logic (PDL). Interestingly, in spite of its greater expressivity, LDLf has exactly the same computational complexity of LTLf. We show that LDLf is able to capture, in the logic itself, not only the constraints to be monitored, but also the de-facto standard RV-LTL monitors. This makes it possible to declaratively capture monitoring metaconstraints, and check them by relying on usual logical services instead of ad-hoc algorithms. This, in turn, enables to flexibly monitor constraints depending on the monitoring state of other constraints, e.g., "compensation" constraints that are only checked when others are detected to be violated. In addition, we devise a direct translation of LDLf formulas into nondeterministic automata, avoiding to detour to Buechi automata or alternating automata, and we use it to implement a monitoring plug-in for the PROM suite

Runtime Verification of Temporal Properties over Out-of-order Data Streams

We present a monitoring approach for verifying systems at runtime. Our approach targets systems whose components communicate with the monitors over unreliable channels, where messages can be delayed or lost. In contrast to prior works, whose property specification languages are limited to propositional temporal logics, our approach handles an extension of the real-time logic MTL with freeze quantifiers for reasoning about data values. We present its underlying theory based on a new three-valued semantics that is well suited to soundly and completely reason online about event streams in the presence of message delay or loss. We also evaluate our approach experimentally. Our prototype implementation processes hundreds of events per second in settings where messages are received out of order.Comment: long version of the CAV 2017 pape

Semantic-based decision support for remote care of dementia patients

This paper investigates the challenges in developing a semantic-based Dementia Care Decision Support System based on the non-intrusive monitoring of the patient's behaviour. Semantic-based approaches are well suited for modelling context-aware scenarios similar to Dementia care systems, where the patient's dynamic behaviour observations (occupants movement, equipment use) need to be analysed against the semantic knowledge about the patient's condition (illness history, medical advice, known symptoms) in an integrated knowledgebase. However, our research findings establish that the ability of semantic technologies to reason upon the complex interrelated events emanating from the behaviour monitoring sensors to infer knowledge assisting medical advice represents a major challenge. We attempt to address this problem by introducing a new approach that relies on propositional calculus modelling to segregate complex events that are amenable for semantic reasoning from events that require pre-processing outside the semantic engine before they can be reasoned upon. The event pre-processing activity also controls the timing of triggering the reasoning process in order to further improve the efficiency of the inference process. Using regression analysis, we evaluate the response-time as the number of monitored patients increases and conclude that the incurred overhead on the response time of the prototype decision support systems remains tolerable

Is my configuration any good: checking usability in an interactive sensor-based activity monitor

We investigate formal analysis of two aspects of usability in a deployed interactive, configurable and context-aware system: an event-driven, sensor-based homecare activity monitor system. The system was not designed from formal requirements or specification: we model the system as it is in the context of an agile development process. Our aim was to determine if formal modelling and analysis can contribute to improving usability, and if so, which style of modelling is most suitable. The purpose of the analysis is to inform configurers about how to interact with the system, so the system is more usable for participants, and to guide future developments. We consider redundancies in configuration rules defined by carers and participants and the interaction modality of the output messages.Two approaches to modelling are considered: a deep embedding in which devices, sensors and rules are represented explicitly by data structures in the modelling language and non-determinism is employed to model all possible device and sensor states, and a shallow embedding in which the rules and device and sensor states are represented directly in propositional logic. The former requires a conventional machine and a model-checker for analysis, whereas the latter is implemented using a SAT solver directly on the activity monitor hardware. We draw conclusions about the role of formal models and reasoning in deployed systems and the need for clear semantics and ontologies for interaction modalities

The Linguistic Determination of Conscious Thought Contents

In this paper we address the question of what determines the content of our conscious episodes of thinking, considering recent claims that phenomenal character individuates thought contents. We present one prominent way for defenders of phenomenal intentionality to develop that view and then examine ‘sensory inner speech views’, which provide an alternative way of accounting for thought-content determinacy. We argue that such views fare well with inner speech thinking but have problems accounting for unsymbolized thinking. Within this dialectic, we present an account of the nature of unsymbolized thinking that accords with and can be seen as a continuation of the activity of inner speech, while offering a way of explaining thought-content determinacy in terms of linguistic structures and representation

A Story of Parametric Trace Slicing, Garbage and Static Analysis

This paper presents a proposal (story) of how statically detecting unreachable objects (in Java) could be used to improve a particular runtime verification approach (for Java), namely parametric trace slicing. Monitoring algorithms for parametric trace slicing depend on garbage collection to (i) cleanup data-structures storing monitored objects, ensuring they do not become unmanageably large, and (ii) anticipate the violation of (non-safety) properties that cannot be satisfied as a monitored object can no longer appear later in the trace. The proposal is that both usages can be improved by making the unreachability of monitored objects explicit in the parametric property and statically introducing additional instrumentation points generating related events. The ideas presented in this paper are still exploratory and the intention is to integrate the described techniques into the MarQ monitoring tool for quantified event automata.Comment: In Proceedings PrePost 2017, arXiv:1708.0688

An information processing view of fringe consciousness

Commentary on: Mangan, B. (2001) Sensation's ghost: the non-sensory "fringe" of consciousness. Psyche, 7(18), October 2001 http://psyche.cs.monash.edu.au/v7/psyche-7-18-mangan.html In posing the sense of 'Rightness' as a quality-of-processing measure, Mangan runs the risk of a homuncular argument, since some process needs to observe Rightness, as well as the sensory qualia. Interacting Cognitive Subsystems (ICS) is an information processing account of cognitive activity that is concordant with Mangan's arguments, but which avoids the need for any supervisory system or central executive. The approach models thought as the flow of information between nine different levels of mental representation, and includes a distinction between an unselective diffuse awareness of all active levels of representation, and a selective focal awareness of a single topic of processing. A distinction is introduced between two non-sensory representations: propositional and implicational meaning. While the propositional representations can be easily verbalised, the sensory and implicational representations can only be verbalised via propositional representations. All representations are accessible, although implications and sensory representations are harder to express verbally. As a principled model, ICS can be mapped into anatomical and neural models, supporting argumentation about physical pathways in the brain and functional pathways in the mind

Intention and motor representation in purposive action

Are there distinct roles for intention and motor representation in explaining the purposiveness of action? Standard accounts of action assign a role to intention but are silent on motor representation. The temptation is to suppose that nothing need be said here because motor representation is either only an enabling condition for purposive action or else merely a variety of intention. This paper provides reasons for resisting that temptation. Some motor representations, like intentions, coordinate actions in virtue of representing outcomes; but, unlike intentions, motor representations cannot feature as premises or conclusions in practical reasoning. This implies that motor representation has a distinctive role in explaining the purposiveness of action. It also gives rise to a problem: were the roles of intention and motor representation entirely independent, this would impair effective action. It is therefore necessary to explain how intentions interlock with motor representations. The solution, we argue, is to recognise that the contents of intentions can be partially determined by the contents of motor representations. Understanding this content-determining relation enables better understanding how intentions relate to actions