Efficient symbolic model checking of concurrent systems

Design errors in software systems consisting of concurrent components are potentially disastrous, yet notoriously difficult to find by testing. Therefore, more rigorous analysis methods are gaining popularity. Symbolic model checking techniques are based on modeling the behavior of the system as a formula and reducing the analysis problem to symbolic manipulation of formulas by computational tools. In this work, the aim is to make symbolic model checking, in particular bounded model checking, more efficient for verifying and falsifying safety properties of highly concurrent system models with high-level data features. The contributions of this thesis are divided to four topics. The first topic is symbolic model checking of UML state machine models. UML is a language widely used in the industry for modeling software-intensive systems. The contribution is an accurate semantics for a subset of the UML state machine language and an automatic translation to formulas, enabling symbolic UML model checking. The second topic is bounded model checking of systems with queues. Queues are frequently used to model, for example, message buffers in distributed systems. The contribution is a variety of ways to encode the behavior of queues in formulas that exploit the features of modern SMT solver tools. The third topic is symbolic partial order methods for accelerated model checking. By exploiting the inherent independence of the components of a concurrent system, the executions of the system are compressed by allowing several actions in different components to occur at the same time. Making the executions shorter increases the performance of bounded model checking. The contribution includes three alternative partial order semantics for compressing the executions, with analytic and experimental evaluation. The work also presents a new variant of bounded model checking that is based on a concurrent instead of sequential view of the events that constitute an execution. The fourth topic is efficient computation of predicate abstraction. Predicate abstraction is a key technique for scalable model checking, based on replacing the system model by a simpler abstract model that omits irrelevant details. In practice, constructing the abstract model can be computationally expensive. The contribution is a combination of techniques that exploit the structure of the underlying system to partition the problem into a sequence of cheaper abstraction problems, thus reducing the total complexity

Automatic Derivation of Abstract Semantics From Instruction Set Descriptions

Abstracted semantics of instructions of processor-based architectures are an invaluable asset for several formal verification techniques, such as software model checking and static analysis. In the field of model checking, abstract versions of instructions can help counter the state explosion problem, for instance by replacing explicit values by symbolic representations of sets of values. Similar to this, static analyses often operate on an abstract domain in order to reduce complexity, guarantee termination, or both. Hence, for a given microcontroller, the task at hand is to find such abstractions. Due to the large number of available microcontrollers, some of which are even created for specific applications, it is impracticable to rely on human developers to perform this step. Therefore, we propose a technique that starts from imperative descriptions of instructions, which allows to automate most of the process

A Faithful Semantics for Generalised Symbolic Trajectory Evaluation

Generalised Symbolic Trajectory Evaluation (GSTE) is a high-capacity formal verification technique for hardware. GSTE uses abstraction, meaning that details of the circuit behaviour are removed from the circuit model. A semantics for GSTE can be used to predict and understand why certain circuit properties can or cannot be proven by GSTE. Several semantics have been described for GSTE. These semantics, however, are not faithful to the proving power of GSTE-algorithms, that is, the GSTE-algorithms are incomplete with respect to the semantics. The abstraction used in GSTE makes it hard to understand why a specific property can, or cannot, be proven by GSTE. The semantics mentioned above cannot help the user in doing so. The contribution of this paper is a faithful semantics for GSTE. That is, we give a simple formal theory that deems a property to be true if-and-only-if the property can be proven by a GSTE-model checker. We prove that the GSTE algorithm is sound and complete with respect to this semantics

Soft Contract Verification

Behavioral software contracts are a widely used mechanism for governing the flow of values between components. However, run-time monitoring and enforcement of contracts imposes significant overhead and delays discovery of faulty components to run-time. To overcome these issues, we present soft contract verification, which aims to statically prove either complete or partial contract correctness of components, written in an untyped, higher-order language with first-class contracts. Our approach uses higher-order symbolic execution, leveraging contracts as a source of symbolic values including unknown behavioral values, and employs an updatable heap of contract invariants to reason about flow-sensitive facts. We prove the symbolic execution soundly approximates the dynamic semantics and that verified programs can't be blamed. The approach is able to analyze first-class contracts, recursive data structures, unknown functions, and control-flow-sensitive refinements of values, which are all idiomatic in dynamic languages. It makes effective use of an off-the-shelf solver to decide problems without heavy encodings. The approach is competitive with a wide range of existing tools---including type systems, flow analyzers, and model checkers---on their own benchmarks.Comment: ICFP '14, September 1-6, 2014, Gothenburg, Swede

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

Using Graph Transformations and Graph Abstractions for Software Verification

In this paper we describe our intended approach for the verification of software written in imperative programming languages. We base our approach on model checking of graph transition systems, where each state is a graph and the transitions are specified by graph transformation rules. We believe that graph transformation is a very suitable technique to model the execution semantics of languages with dynamic memory allocation. Furthermore, such representation allows us to investigate the use of graph abstractions, which can mitigate the combinatorial explosion inherent to model checking. In addition to presenting our planned approach, we reason about its feasibility, and, by providing a brief comparison to other existing methods, we highlight the benefits and drawbacks that are expected

Formal Verification of Security Protocol Implementations: A Survey

Automated formal verification of security protocols has been mostly focused on analyzing high-level abstract models which, however, are significantly different from real protocol implementations written in programming languages. Recently, some researchers have started investigating techniques that bring automated formal proofs closer to real implementations. This paper surveys these attempts, focusing on approaches that target the application code that implements protocol logic, rather than the libraries that implement cryptography. According to these approaches, libraries are assumed to correctly implement some models. The aim is to derive formal proofs that, under this assumption, give assurance about the application code that implements the protocol logic. The two main approaches of model extraction and code generation are presented, along with the main techniques adopted for each approac