Verification of Shared-Reading Synchronisers

Synchronisation classes are an important building block for shared memory concurrent programs. Thus to reason about such programs, it is important to be able to verify the implementation of these synchronisation classes, considering atomic operations as the synchronisation primitives on which the implementations are built. For synchronisation classes controlling exclusive access to a shared resource, such as locks, a technique has been proposed to reason about their behaviour. This paper proposes a technique to verify implementations of both exclusive access and shared-reading synchronisers. We use permission-based Separation Logic to describe the behaviour of the main atomic operations, and the basis for our technique is formed by a specification for class AtomicInteger, which is commonly used to implement synchronisation classes in java.util.concurrent. To demonstrate the applicability of our approach, we mechanically verify the implementation of various synchronisation classes like Semaphore, CountDownLatch and Lock.Comment: In Proceedings MeTRiD 2018, arXiv:1806.0933

Evolving models in Model-Driven Engineering : State-of-the-art and future challenges

The artefacts used in Model-Driven Engineering (MDE) evolve as a matter of course: models are modified and updated as part of the engineering process; metamodels change as a result of domain analysis and standardisation efforts; and the operations applied to models change as engineering requirements change. MDE artefacts are inter-related, and simultaneously constrain each other, making evolution a challenge to manage. We discuss some of the key problems of evolution in MDE, summarise the key state-of-the-art, and look forward to new challenges in research in this area

A high-level and scalable approach for generating scale-free graphs using active objects

The Barabasi-Albert model (BA) is designed to generate scale-free networks using the preferential attachment mechanism. In the preferential attachment (PA) model, new nodes are sequentially introduced to the network and they attach preferentially to existing nodes. PA is a classical model with a natural intuition, great explanatory power and a simple mechanism. Therefore, PA is widely-used for network generation. However the sequential mechanism used in the PA model makes it an inefficient algorithm. The existing parallel approaches, on the other hand, suffer from either changing the original model or explicit complex low-level synchronization mechanisms. In this paper we investigate a high-level Actor-based model of the parallel algorithm of network generation and its scalable multicore implementation in Haskell

The early bird catches the worm: First verify, then monitor!

© 2018 Elsevier B.V. Trace expressions are a compact and expressive formalism, initially devised for runtime verification of agent interactions in multiagent systems, which has been successfully employed to model real-world protocols, and to generate monitors for mainstream multiagent system platforms, and generalized to support runtime verification of different kinds of properties and systems. In this paper, we propose an algorithm to check Linear Temporal Logic (LTL) properties satisfiability on trace expressions. To do this, we show how to translate a trace expression into a Büchi Automaton in order to realize an Automata-Based Model Checking. We show that this translation generates an over-approximation of our trace expression leading us to obtain a sound procedure to verify LTL properties. Once we have statically checked a set of LTL properties, we can conclude that: (1) our trace expression is formally correct (2) since we use this trace expression to generate monitors checking the runtime behavior of the system, the LTL properties verified by this trace expression are also verified by the monitored system

RML: Runtime Monitoring Language

Runtime verification is a relatively new software verification technique that aims to prove the correctness of a specific run of a program, rather than statically verify the code. The program is instrumented in order to collect all the relevant information, and the resulting trace of events is inspected by a monitor that verifies its compliance with respect to a specification of the expected properties of the system under scrutiny. Many languages exist that can be used to formally express the expected behavior of a system, with different design choices and degrees of expressivity. This thesis presents RML, a specification language designed for runtime verification, with the goal of being completely modular and independent from the instrumentation and the kind of system being monitored. RML is highly expressive, and allows one to express complex, parametric, non-context-free properties concisely. RML is compiled down to TC, a lower level calculus, which is fully formalized with a deterministic, rewriting-based semantics. In order to evaluate the approach, an open source implementation has been developed, and several examples with Node.js programs have been tested. Benchmarks show the ability of the monitors automatically generated from RML specifications to effectively and efficiently verify complex properties

Symbolic execution formally explained

In this paper, we provide a formal explanation of symbolic execution in terms of a symbolic transition system and prove its correctness and completeness with respect to an operational semantics which models the execution on concrete values.We first introduce a formalmodel for a basic programming languagewith a statically fixed number of programming variables. This model is extended to a programming language with recursive procedures which are called by a call-by-value parameter mechanism. Finally, we present a more general formal framework for proving the soundness and completeness of the symbolic execution of a basic object-oriented language which features dynamically allocated variables.Computer Science

Automatic Selection of Statistical Model Checkers for Analysis of Biological Models

Statistical Model Checking (SMC) blends the speed of simulation with the rigorous analytical capabilities of model checking, and its success has prompted researchers to implement a number of SMC tools whose availability provides flexibility and fine-tuned control over model analysis. However, each tool has its own practical limitations, and different tools have different requirements and performance characteristics. The performance of different tools may also depend on the specific features of the input model or the type of query to be verified. Consequently, choosing the most suitable tool for verifying any given model requires a significant degree of experience, and in most cases, it is challenging to predict the right one. The aim of our research has been to simplify the model checking process for researchers in biological systems modelling by simplifying and rationalising the model selection process. This has been achieved through delivery of the various key contributions listed below. • We have developed a software component for verification of kernel P (kP) system models, using the NuSMV model checker. We integrated it into a larger software platform (www.kpworkbench.org). • We surveyed five popular SMC tools, comparing their modelling languages, external dependencies, expressibility of specification languages, and performance. To best of our knowledge, this is the first known attempt to categorise the performance of SMC tools based on the commonly used property specifications (property patterns) for model checking. • We have proposed a set of model features which can be used for predicting the fastest SMC for biological model verification, and have shown, moreover, that the proposed features both reduce computation time and increase predictive power. • We used machine learning algorithms for predicting the fastest SMC tool for verification of biological models, and have shown that this approach can successfully predict the fastest SMC tool with over 90% accuracy. • We have developed a software tool, SMC Predictor, that predicts the fastest SMC tool for a given model and property query, and have made this freely available to the wider research community (www.smcpredictor.com). Our results show that using our methodology can generate significant savings in the amount of time and resources required for model verification