Abstraction and Learning for Infinite-State Compositional Verification

Despite many advances that enable the application of model checking techniques to the verification of large systems, the state-explosion problem remains the main challenge for scalability. Compositional verification addresses this challenge by decomposing the verification of a large system into the verification of its components. Recent techniques use learning-based approaches to automate compositional verification based on the assume-guarantee style reasoning. However, these techniques are only applicable to finite-state systems. In this work, we propose a new framework that interleaves abstraction and learning to perform automated compositional verification of infinite-state systems. We also discuss the role of learning and abstraction in the related context of interface generation for infinite-state components.Comment: In Proceedings Festschrift for Dave Schmidt, arXiv:1309.455

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

Scheduler-specific Confidentiality for Multi-Threaded Programs and Its Logic-Based Verification

Observational determinism has been proposed in the literature as a way to ensure confidentiality for multi-threaded programs. Intuitively, a program is observationally deterministic if the behavior of the public variables is deterministic, i.e., independent of the private variables and the scheduling policy. Several formal definitions of observational determinism exist, but all of them have shortcomings; for example they accept insecure programs or they reject too many innocuous programs. Besides, the role of schedulers was ignored in all the proposed definitions. A program that is secure under one kind of scheduler might not be secure when executed with a different scheduler. The existing definitions do not ensure that an accepted program behaves securely under the scheduler that is used to deploy the program. Therefore, this paper proposes a new formalization of scheduler-specific observational determinism. It accepts programs that are secure when executed under a specific scheduler. Moreover, it is less restrictive on harmless programs under a particular scheduling policy. In addition, we discuss how compliance with our definition can be verified, using model checking. We use the idea of self-composition and we rephrase the observational determinism property for a single program $C$ as a temporal logic formula over the program $C$ executed in parallel with an independent copy of itself. Thus two states reachable during the execution of $C$ are combined into a reachable program state of the self-composed program. This allows to compare two program executions in a single temporal logic formula. The actual characterization is done in two steps. First we discuss how stuttering equivalence can be characterized as a temporal logic formula. Observational determinism is then expressed in terms of the stuttering equivalence characterization. This results in a conjunction of an LTL and a CTL formula, that are amenable to model checking

Quantitative Information Flow as Safety and Liveness Hyperproperties

We employ Clarkson and Schneider's "hyperproperties" to classify various verification problems of quantitative information flow. The results of this paper unify and extend the previous results on the hardness of checking and inferring quantitative information flow. In particular, we identify a subclass of liveness hyperproperties, which we call "k-observable hyperproperties", that can be checked relative to a reachability oracle via self composition.Comment: In Proceedings QAPL 2012, arXiv:1207.055