A Temporal Logic for Hyperproperties

Hyperproperties, as introduced by Clarkson and Schneider, characterize the correctness of a computer program as a condition on its set of computation paths. Standard temporal logics can only refer to a single path at a time, and therefore cannot express many hyperproperties of interest, including noninterference and other important properties in security and coding theory. In this paper, we investigate an extension of temporal logic with explicit path variables. We show that the quantification over paths naturally subsumes other extensions of temporal logic with operators for information flow and knowledge. The model checking problem for temporal logic with path quantification is decidable. For alternation depth 1, the complexity is PSPACE in the length of the formula and NLOGSPACE in the size of the system, as for linear-time temporal logic

Neural Dynamics Underlying Impaired Autonomic and Conditioned Responses Following Amygdala and Orbitofrontal Lesions

A neural model is presented that explains how outcome-specific learning modulates affect, decision-making and Pavlovian conditioned approach responses. The model addresses how brain regions responsible for affective learning and habit learning interact, and answers a central question: What are the relative contributions of the amygdala and orbitofrontal cortex to emotion and behavior? In the model, the amygdala calculates outcome value while the orbitofrontal cortex influences attention and conditioned responding by assigning value information to stimuli. Model simulations replicate autonomic, electrophysiological, and behavioral data associated with three tasks commonly used to assay these phenomena: Food consumption, Pavlovian conditioning, and visual discrimination. Interactions of the basal ganglia and amygdala with sensory and orbitofrontal cortices enable the model to replicate the complex pattern of spared and impaired behavioral and emotional capacities seen following lesions of the amygdala and orbitofrontal cortex.National Science Foundation (SBE-0354378; IIS-97-20333); Office of Naval Research (N00014-01-1-0624); Defense Advanced Research Projects Agency and the Office of Naval Research (N00014-95-1-0409); National Institutes of Health (R29-DC02952

TCTL model checking of Time Petri Nets

International audienceIn this paper, we consider \emph{subscript} TCTL for Time Petri Nets (TPN-TCTL) for which temporal operators are extended with a time interval, specifying a time constraint on the firing sequences. We prove that the model-checking of a TPN-TCTL formula on a bounded TPN is decidable and is a PSPACE-complete problem. We propose a zone based state space abstraction that preserves marking reachability and traces of the TPN. As for Timed Automata (TA), the abstraction may use an over-approximation operator on zones to enforce the termination. A coarser (and efficient) abstraction is then provided and proved exact w.r.t. marking reachability and traces (LTL properties). Finally, we consider a subset of TPN-TCTL properties for which it is possible to propose efficient on-the-fly model-checking algorithms. Our approach consists in computing and exploring the zone based state space abstractio

Doctor of Philosophy

dissertationThe increasing demand for smaller, more efficient circuits has created a need for both digital and analog designs to scale down. Digital technologies have been successful in meeting this challenge, but analog circuits have lagged behind due to smaller transistor sizes having a disproportionate negative affect. Since many applications require small, low-power analog circuits, the trend has been to take advantage of digital's ability to scale by replacing as much of the analog circuitry as possible with digital counterparts. The results are known as \emph{digitally-intensive analog/mixed-signal} (AMS) circuits. Though such circuits have helped the scaling problem, they have further complicated verification. This dissertation improves on techniques for AMS property specifications, as well as, develops sound, efficient extensions to formal AMS verification methods. With the \emph{language for analog/mixed-signal properties} (LAMP), one has a simple intuitive language for specifying AMS properties. LAMP provides a more procedural method for describing properties that is more straightforward than temporal logic-like languages. However, LAMP is still a nascent language and is limited in the types of properties it is capable of describing. This dissertation extends LAMP by adding statements to ignore transient periods and be able to reset the property check when the environment conditions change. After specifying a property, one needs to verify that the circuit satisfies the property. An efficient method for formally verifying AMS circuits is to use the restricted polyhedral class of \emph{zones}. Zones have simple operations for exploring the reachable state space, but they are only applicable to circuit models that utilize constant rates. To extend zones to more general models, this dissertation provides the theory and implementation needed to soundly handle models with ranges of rates. As a second improvement to the state representation, this dissertation describes how octagons can be adapted to model checking AMS circuit models. Though zones have efficient algorithms, it comes at a cost of over-approximating the reachable state space. Octagons have similarly efficient algorithms while adding additional flexibility to reduce the necessary over-approximations. Finally, the full methodology described in this dissertation is demonstrated on two examples. The first example is a switched capacitor integrator that has been studied in the context of transforming the original formal model to use only single rate assignments. Th property of not saturating is written in LAMP, the circuit is learned, and the property is checked against a faulty and correct circuit. In addition, it is shown that the zone extension, and its implementation with octagons, recovers all previous conclusions with the switched capacitor integrator without the need to translate the model. In particular, the method applies generally to all the models produced and does not require the soundness check needed by the translational approach to accept positive verification results. As a second example, the full tool flow is demonstrated on a digital C-element that is driven by a pair of RC networks, creating an AMS circuit. The RC networks are chosen so that the inputs to the C-element are ordered. LAMP is used to codify this behavior and it is verified that the input signals change in the correct order for the provided SPICE simulation traces

Clafer: Lightweight Modeling of Structure, Behaviour, and Variability

Embedded software is growing fast in size and complexity, leading to intimate mixture of complex architectures and complex control. Consequently, software specification requires modeling both structures and behaviour of systems. Unfortunately, existing languages do not integrate these aspects well, usually prioritizing one of them. It is common to develop a separate language for each of these facets. In this paper, we contribute Clafer: a small language that attempts to tackle this challenge. It combines rich structural modeling with state of the art behavioural formalisms. We are not aware of any other modeling language that seamlessly combines these facets common to system and software modeling. We show how Clafer, in a single unified syntax and semantics, allows capturing feature models (variability), component models, discrete control models (automata) and variability encompassing all these aspects. The language is built on top of first order logic with quantifiers over basic entities (for modeling structures) combined with linear temporal logic (for modeling behaviour). On top of this semantic foundation we build a simple but expressive syntax, enriched with carefully selected syntactic expansions that cover hierarchical modeling, associations, automata, scenarios, and Dwyer's property patterns. We evaluate Clafer using a power window case study, and comparing it against other notations that substantially overlap with its scope (SysML, AADL, Temporal OCL and Live Sequence Charts), discussing benefits and perils of using a single notation for the purpose

Using Probabilistic Temporal Logic PCTL and Model Checking for Context Prediction

Context prediction is a promoting research topic with a lot of challenges and opportunities. Indeed, with the constant evolution of context-aware systems, context prediction remains a complex task due to the lack of formal approach. In this paper, we propose a new approach to enhance context prediction using a probabilistic temporal logic and model checking. The probabilistic temporal logic PCTL is used to provide an efficient expressivity and a reasoning based on temporal logic in order to fit with the dynamic and non-deterministic nature of the system's environment. Whereas, the probabilistic model checking is used for automatically verifying that a probabilistic system satisfies a property with a given likelihood. Our new approach allows a formal expressivity of a multidimensional context prediction. Tested on real data our model was able to achieve 78% of the future activities prediction accuracy