Bounded saturation-based CTL model checking

Formal verification is becoming a fundamental step of safety-critical and model-based software development. As part of the verification process, model checking is one of the current advanced techniques to analyze the behavior of a system. Symbolic model checking is an efficient approach to handling even complex models with huge state spaces. Saturation is a symbolic algorithm with a special iteration strategy, which is efficient for asynchronous models. Recent advances have resulted in many new kinds of saturation-based algorithms for state space generation and bounded state space generation and also for structural model checking. In this paper, we examine how the combination of two advanced model checking algorithms – bounded saturation and saturation-based structural model checking – can be used to verify systems. Our work is the first attempt to combine these approaches, and this way we are able to handle and examine complex or even infinite state systems. Our measurements show that we can exploit the efficiency of saturation in bounded model checking

Component-wise incremental LTL model checking

Efficient symbolic and explicit-state model checking approaches have been developed for the verification of linear time temporal logic (LTL) properties. Several attempts have been made to combine the advantages of the various algorithms. Model checking LTL properties usually poses two challenges: one must compute the synchronous product of the state space and the automaton model of the desired property, then look for counterexamples that is reduced to finding strongly connected components (SCCs) in the state space of the product. In case of concurrent systems, where the phenomenon of state space explosion often prevents the successful verification, the so-called saturation algorithm has proved its efficiency in state space exploration. This paper proposes a new approach that leverages the saturation algorithm both as an iteration strategy constructing the product directly, as well as in a new fixed-point computation algorithm to find strongly connected components on-the-fly by incrementally processing the components of the model. Complementing the search for SCCs, explicit techniques and component-wise abstractions are used to prove the absence of counterexamples. The resulting on-the-fly, incremental LTL model checking algorithm proved to scale well with the size of models, as the evaluation on models of the Model Checking Contest suggests

Verification and synthesis of asynchronous control circuits using petri net unfoldings

PhD ThesisDesign of asynchronous control circuits has traditionally been associated with application of formal methods. Event-based models, such as Petri nets, provide a compact and easy to understand way of specifying asynchronous behaviour. However, analysis of their behavioural properties is often hindered by the problem of exponential growth of reachable state space. This work proposes a new method for analysis of asynchronous circuit models based on Petri nets. The new approach is called PN-unfolding segment. It extends and improves existing Petri nets unfolding approaches. In addition, this thesis proposes a new analysis technique for Signal Transition Graphs along with an efficient verification technique which is also based on the Petri net unfolding. The former is called Full State Graph, the latter - STG-unfolding segment. The boolean logic synthesis is an integral part of the asynchronous circuit design process. In many cases, even if the verification of an asynchronous circuit specification has been performed successfully, it is impossible to obtain its implementation using existing methods because they are based on the reachability analysis. A new approach is proposed here for automated synthesis of speed-independent circuits based on the STG-unfolding segment constructed during the verification of the circuit's specification. Finally, this work presents experimental results showing the need for the new Petri net unfolding techniques and confirming the advantages of application of partial order approach to analysis, verification and synthesis of asynchronous circuits.The Research Committee, Newcastle University: Overseas Research Studentship Award

Advanced semantics for accelerated graph processing

Large-scale graph applications are of great national, commercial, and societal importance, with direct use in fields such as counter-intelligence, proteomics, and data mining. Unfortunately, graph-based problems exhibit certain basic characteristics that make them a poor match for conventional computing systems in terms of structure, scale, and semantics. Graph processing kernels emphasize sparse data structures and computations with irregular memory access patterns that destroy the temporal and spatial locality upon which modern processors rely for performance. Furthermore, applications in this area utilize large data sets, and have been shown to be more data intensive than typical floating-point applications, two properties that lead to inefficient utilization of the hierarchical memory system. Current approaches to processing large graph data sets leverage traditional HPC systems and programming models, for shared memory and message-passing computation, and are thus limited in efficiency, scalability, and programmability. The research presented in this thesis investigates the potential of a new model of execution that is hypothesized as a promising alternative for graph-based applications to conventional practices. A new approach to graph processing is developed and presented in this thesis. The application of the experimental ParalleX execution model to graph processing balances continuation-migration style fine-grain concurrency with constraint-based synchronization through embedded futures. A collection of parallel graph application kernels provide experiment control drivers for analysis and evaluation of this innovative strategy. Finally, an experimental software library for scalable graph processing, the ParalleX Graph Library, is defined using the HPX runtime system, providing an implementation of the key concepts and a framework for development of ParalleX-based graph applications

Faster Algorithms for Weighted Recursive State Machines

Pushdown systems (PDSs) and recursive state machines (RSMs), which are linearly equivalent, are standard models for interprocedural analysis. Yet RSMs are more convenient as they (a) explicitly model function calls and returns, and (b) specify many natural parameters for algorithmic analysis, e.g., the number of entries and exits. We consider a general framework where RSM transitions are labeled from a semiring and path properties are algebraic with semiring operations, which can model, e.g., interprocedural reachability and dataflow analysis problems. Our main contributions are new algorithms for several fundamental problems. As compared to a direct translation of RSMs to PDSs and the best-known existing bounds of PDSs, our analysis algorithm improves the complexity for finite-height semirings (that subsumes reachability and standard dataflow properties). We further consider the problem of extracting distance values from the representation structures computed by our algorithm, and give efficient algorithms that distinguish the complexity of a one-time preprocessing from the complexity of each individual query. Another advantage of our algorithm is that our improvements carry over to the concurrent setting, where we improve the best-known complexity for the context-bounded analysis of concurrent RSMs. Finally, we provide a prototype implementation that gives a significant speed-up on several benchmarks from the SLAM/SDV project

Taming Numbers and Durations in the Model Checking Integrated Planning System

The Model Checking Integrated Planning System (MIPS) is a temporal least commitment heuristic search planner based on a flexible object-oriented workbench architecture. Its design clearly separates explicit and symbolic directed exploration algorithms from the set of on-line and off-line computed estimates and associated data structures. MIPS has shown distinguished performance in the last two international planning competitions. In the last event the description language was extended from pure propositional planning to include numerical state variables, action durations, and plan quality objective functions. Plans were no longer sequences of actions but time-stamped schedules. As a participant of the fully automated track of the competition, MIPS has proven to be a general system; in each track and every benchmark domain it efficiently computed plans of remarkable quality. This article introduces and analyzes the most important algorithmic novelties that were necessary to tackle the new layers of expressiveness in the benchmark problems and to achieve a high level of performance. The extensions include critical path analysis of sequentially generated plans to generate corresponding optimal parallel plans. The linear time algorithm to compute the parallel plan bypasses known NP hardness results for partial ordering by scheduling plans with respect to the set of actions and the imposed precedence relations. The efficiency of this algorithm also allows us to improve the exploration guidance: for each encountered planning state the corresponding approximate sequential plan is scheduled. One major strength of MIPS is its static analysis phase that grounds and simplifies parameterized predicates, functions and operators, that infers knowledge to minimize the state description length, and that detects domain object symmetries. The latter aspect is analyzed in detail. MIPS has been developed to serve as a complete and optimal state space planner, with admissible estimates, exploration engines and branching cuts. In the competition version, however, certain performance compromises had to be made, including floating point arithmetic, weighted heuristic search exploration according to an inadmissible estimate and parameterized optimization

Geometry-Oblivious FMM for Compressing Dense SPD Matrices

We present GOFMM (geometry-oblivious FMM), a novel method that creates a hierarchical low-rank approximation, "compression," of an arbitrary dense symmetric positive definite (SPD) matrix. For many applications, GOFMM enables an approximate matrix-vector multiplication in $N \log N$ or even $N$ time, where $N$ is the matrix size. Compression requires $N \log N$ storage and work. In general, our scheme belongs to the family of hierarchical matrix approximation methods. In particular, it generalizes the fast multipole method (FMM) to a purely algebraic setting by only requiring the ability to sample matrix entries. Neither geometric information (i.e., point coordinates) nor knowledge of how the matrix entries have been generated is required, thus the term "geometry-oblivious." Also, we introduce a shared-memory parallel scheme for hierarchical matrix computations that reduces synchronization barriers. We present results on the Intel Knights Landing and Haswell architectures, and on the NVIDIA Pascal architecture for a variety of matrices.Comment: 13 pages, accepted by SC'1

Model checking probabilistic and stochastic extensions of the pi-calculus

We present an implementation of model checking for probabilistic and stochastic extensions of the pi-calculus, a process algebra which supports modelling of concurrency and mobility. Formal verification techniques for such extensions have clear applications in several domains, including mobile ad-hoc network protocols, probabilistic security protocols and biological pathways. Despite this, no implementation of automated verification exists. Building upon the pi-calculus model checker MMC, we first show an automated procedure for constructing the underlying semantic model of a probabilistic or stochastic pi-calculus process. This can then be verified using existing probabilistic model checkers such as PRISM. Secondly, we demonstrate how for processes of a specific structure a more efficient, compositional approach is applicable, which uses our extension of MMC on each parallel component of the system and then translates the results into a high-level modular description for the PRISM tool. The feasibility of our techniques is demonstrated through a number of case studies from the pi-calculus literature