DRS: Derivational Reasoning System

The high reliability requirements for airborne systems requires fault-tolerant architectures to address failures in the presence of physical faults, and the elimination of design flaws during the specification and validation phase of the design cycle. Although much progress has been made in developing methods to address physical faults, design flaws remain a serious problem. Formal methods provides a mathematical basis for removing design flaws from digital systems. DRS (Derivational Reasoning System) is a formal design tool based on advanced research in mathematical modeling and formal synthesis. The system implements a basic design algebra for synthesizing digital circuit descriptions from high level functional specifications. DRS incorporates an executable specification language, a set of correctness preserving transformations, verification interface, and a logic synthesis interface, making it a powerful tool for realizing hardware from abstract specifications. DRS integrates recent advances in transformational reasoning, automated theorem proving and high-level CAD synthesis systems in order to provide enhanced reliability in designs with reduced time and cost

Compositional Reactive Synthesis for Multi-Agent Systems

With growing complexity of systems and guarantees they are required to provide, the need for automated and formal design approaches that can guarantee safety and correctness of the designed system is becoming more evident. To this end, an ambitious goal in system design and control is to automatically synthesize the system from a high-level specification given in a formal language such as linear temporal logic. The goal of this dissertation is to investigate and develop the necessary tools and methods for automated synthesis of controllers from high-level specifications for multi-agent systems. We consider systems where a set of controlled agents react to their environment that includes other uncontrolled, dynamic and potentially adversarial agents. We are particularly interested in studying how the existing structure in systems can be exploited to achieve more efficient synthesis algorithms through compositional reasoning. We explore three different frameworks for compositional synthesis of controllers for multi-agent systems. In the first framework, we decompose the global specification into local ones, we then refine the local specifications until they become realizable, and we show that under certain conditions, the strategies synthesized for the local specifications guarantee the satisfaction of the global specification. In the second framework, we show how parametric and reactive controllers can be specified and synthesized, and how they can be automatically composed to enforce a high-level objective. Finally, in the third framework, we focus on a special but practically useful class of multi-agent systems, and show how by taking advantage of the structure in the system and its objective we can achieve significantly better scalability and can solve problems where the centralized synthesis algorithm is infeasible

Guarded atomic actions and refinement in a system-on-chip development flow: bridging the specification gap with Event-B

Modern System-on-chip (SoC) hardware design puts considerable pressure on existing design and verification flows, languages and tools. The Register Transfer Level (RTL)description, which forms the input for synchronous, logic synthesis-driven design is at too low a level of abstraction for efficient architectural exploration and re-use. The existing methods for taking a high-level paper specification and refining this specification to an implementation that meets its performance criteria is largely manual and error-prone and as RTL descriptions get larger, a systematic design method is necessary to address explicitly the timing issues that arise when applying logic synthesis to such large blocks.Guarded Atomic Actions have been shown to offer a convenient notation for describing microarchitectures that is amenable to formal reasoning and high-level synthesis. Event-B is a language and method that supports the development of specifications with automatic proof and refinement, based on guarded atomic actions. Latency-insensitive design ensures that a design composed of functionally correct components will be independent of communication latency. A method has been developed which uses Event-B for latency-insensitive SoC component and sub-system design which can be combined with high-level, component synthesis to enable architectural exploration and re-use at the specification level and to close the specification gap in the SoC hardware flow

A Very High Level Logic Synthesis

The evolution of Computer Aided Design (CAD) calls for the incorporation of design specifications into a microelectronics system development cycle. This expansion requires the establishment of a new generation of CAD procedures, defined as Very High Level Logic Synthesis (VHLLS). The fundamental characteristics of open-ended VHLLS are: (1) front-end graphical interface; (2) time encapsulation; and (3) automatic translation into a behavioral description. Consequently, the VHLLS paradigm represents an advanced category of CAD-based microelectronics system design, built on a deep usage of expert systems and intelligent methods. Artificial Intelligence (AI) formalisms such as Knowledge Representation System (KRS) are necessary to model properties related to the very high level of specification such as: dealing with ambiguities and inconsistencies, reasoning, computing high-level specification, etc. A prototype VHLLS design suite, called Specification Procedure for Electronic Circuits in Automation Language (SPECIAL), is defined, compared with today\u27s commercial tools and verified using numerous design examples. As a result, a new family of formal and accelerated development methodologies has become feasible with a better understanding of formalized knowledge driving these design processes

Optimal temporal logic control of autonomous vehicles

Thesis (Ph.D.)--Boston UniversityTemporal logics, such as Linear Temporal Logic (LTL) and Computation Tree Logic (CTL), are extensions of propositional logic that can capture temporal relations. Even though temporal logics have been used in model checking of finite systems for quite some time, they have gained popularity as a means for specifying complex mission requirements in path planning and control synthesis problems only recently. This dissertation proposes and evaluates methods and algorithms for optimal path planning and control synthesis for autonomous vehicles where a high-level mission specification expressed in LTL (or a fragment of LTL) must be satisfied. In summary, after obtaining a discrete representation of the overall system, ideas and tools from formal verification and graph theory are leveraged to synthesize provably correct and optimal control strategies. The first part of this dissertation focuses on automatic planning of optimal paths for a group of robots that must satisfy a common high level mission specification. The effect of slight deviations in traveling times on the behavior of the team is analyzed and methods that are robust to bounded non-determinism in traveling times are proposed. The second part focuses on the case where a controllable agent is required to satisfy a high-level mission specification in the presence of other probabilistic agents that cannot be controlled. Efficient methods to synthesize control policies that maximize the probability of satisfaction of the mission specification are presented. The focus of the third part is the problem where an autonomous vehicle is required to satisfy a rich mission specification over service requests occurring at the regions of a partitioned environment. A receding horizon control strategy that makes use of the local information provided by the sensors on the vehicle in addition to the a priori information about the environment is presented. For all of the automatic planning and control synthesis problems that are considered, the proposed algorithms are implemented, evaluated, and validated through experiments and/or simulations

Toward a decision support system for the clinical pathways assessment

This paper presents a decision support system to be used in hospital management taskswhich is based on the clinical pathways. We propose a very simple graphical modeling lan-guage based on a small number of primitive elements through which the medical doctorscould introduce a clinical pathway for a specific disease. Three essential aspects relatedto a clinical pathway can be specified in this language: (1) patient flow; (2) resource uti-lization; and (3) information interchange. This high-level language is a domain specificmodeling language calledHealthcare System Specification (HSS), and it is defined as anUnified Modeling Language (UML) profile. A model to model transformation is also pro-posed in order to obtain, from the pathways HSS specification, a Stochastic Well-formedNet (SWN) model that enables a formal analysis of the modeled system and, if needed, toapply synthesis methods enforcing specified requirements. The transformation is based onthe application of local rules. The clinical pathway of hip fracture from the “Lozano Blesa”University hospital in Zaragoza is taken as an example

CONTROLLER SYNTHESIS AND FORMAL BEHAVIOR INFERENCE IN AUTONOMOUS SYSTEMS

Autonomous systems are widely used in crucial applications such as surveillance,defense, reghting, and search & rescue operations. Many of these application require systems to satisfy user-dened requirements describing the desired system behavior. Given high-level requirements, we are interested in the design of controllers that guarantee the compliance of these requirements by the system. However, ensuring that these systems satisfy a given set of requirements is challenging for many reasons, one of which is the large computational cost incurred by having to account for all possible system behaviors and environment conditions. These computational diculties are exacerbated when systems are required to satisfy requirements involving large numbers of tasks emerging from dynamic environments. In addition to computational diculties, scalability issues also arise when dealing with multi-agent applications, in which agents require coordination and communication to satisfy mission requirements. This dissertation is an eort towards addressing the computational and scalability challenges of designing controllers from highlevel requirements by employing reactive synthesis, a formal methods approach, and combining it with other decision-making processes that handle coordination among agents to alleviate the load on reactive synthesis. The proposed framework results in a more scalable solution with lower computational costs while guaranteeing that high-level requirements are met. The practicality of the proposed framework is demonstrated through various types of multi-agent applications including reghting, re monitoring, rescue, search & rescue and ship protection scenarios. Our approach incorporates methodology from computer science and control, including reactive synthesis of discrete systems, metareasoning, reachability analysis and inverse reinforcement learning. This thesis consists of two key parts: reactive synthesis from linear temporal logic specications and specication inference from demonstrations of formal behavior. First, we introduce the reactive synthesis problem for which the desired system behavior species the method by which a multi-agent system solves the problem of decentralized task allocation depending on communication availability conditions. Second, we present the synthesis problem formulated to obtain a high-level mission planner and controller for managing a team of agents ghting a wildre. Third, we present a framework for inferring linear temporal logic specications that succinctly convey and explain the observed behavior. The gained knowledge is leveraged to improve motion prediction for agents behaving according to the learned specication. The eectiveness of the inference process and motion prediction framework are demonstrated through a scenario in which humans practice social norms commonly seen in pedestrian settings

Sciduction: Combining Induction, Deduction, and Structure for Verification and Synthesis

Even with impressive advances in automated formal methods, certain problems in system verification and synthesis remain challenging. Examples include the verification of quantitative properties of software involving constraints on timing and energy consumption, and the automatic synthesis of systems from specifications. The major challenges include environment modeling, incompleteness in specifications, and the complexity of underlying decision problems. This position paper proposes sciduction, an approach to tackle these challenges by integrating inductive inference, deductive reasoning, and structure hypotheses. Deductive reasoning, which leads from general rules or concepts to conclusions about specific problem instances, includes techniques such as logical inference and constraint solving. Inductive inference, which generalizes from specific instances to yield a concept, includes algorithmic learning from examples. Structure hypotheses are used to define the class of artifacts, such as invariants or program fragments, generated during verification or synthesis. Sciduction constrains inductive and deductive reasoning using structure hypotheses, and actively combines inductive and deductive reasoning: for instance, deductive techniques generate examples for learning, and inductive reasoning is used to guide the deductive engines. We illustrate this approach with three applications: (i) timing analysis of software; (ii) synthesis of loop-free programs, and (iii) controller synthesis for hybrid systems. Some future applications are also discussed