International Journal of Foundations of Computer Science

Predicate abstraction has become one of the most successful methodologies for proving safety properties of programs. Recently, several abstraction methodologies have been proposed for proving liveness properties. This paper studies "ranking abstraction" where a program is augmented by a non-constraining progress monitor based on a set of ranking functions, and further abstracted by predicate-abstraction, to allow for automatic verification of progress properties. Unlike many liveness methodologies, the augmentation does not require a complete ranking function that is expected to decrease with each helpful step. Rather, adequate user-provided inputs are component rankings from which a complete ranking function may be automatically formed.

The premise of the paper is an analogy between the methods of ranking abstraction and predicate abstraction, one ingredient of which is refinement: When predicate abstraction fails, one can refine it. When ranking abstraction fails, one must determine whether the predicate abstraction, or the ranking abstraction, needs be refined. The paper presents strategies for determining which case is at hand, and methods for performing the apporpriate refinements.

The other part of the analogy is that of automatically deriving deductive proof constructs: Predicate abstraction is often used to derive program invariants for proving safety properties as a boolean combination of the given predicates. Deductive proof of progress properties requires well-founded ranking functions in addition to invariants. We show how the constructs necessary for a deductive proof of an arbitrary LTL formula can be automatically extracted from a successful application of the ranking abstraction method.

Recent advances in scheduling and networking have paved the way for efficient exploitation of large-scale distributed computing platforms such as computational grids and huge clusters. Such infrastructures hold great promise for the highly resource-demanding task of verifying and checking large models, given that model checkers would be designed with a high degree of scalability and flexibility in mind.

In this paper we focus on the mechanisms required to execute a high-performance, distributed, symbolic model checker on top of a large-scale distributed environment. We develop a hybrid algorithm for slicing the state space and dynamically distribute the work among the worker processes. We show that the new approach is faster, more effective, and thus much more scalable than previous slicing algorithms. We then present a checkpoint-restart module that has very low overhead. This module can be used to combat failures, the likelihood of which increases with the size of the computing plat-form. However, checkpoint-restart is even more handy for the scheduling system: it can be used to avoid reserving large numbers of workers, thus making the distributed computation work-efficient. Finally, we discuss for the first time the effect of reorder on the distributed model checker and show how the distributed system performs more efficient reordering than the sequential one.

We implemented our contributions on a network of 200 processors, using a distributed scalable scheme that employs a high-performance industrial model checker from Intel. Our results show that the system was able to verify real-life models much larger than was previously possible.

We present a novel approach to the automatic verification and falsification of LTL requirements of non-linear discrete-time hybrid systems. The verification tool uses an interval-based constraint solver for non-linear robust constraints to compute incrementally refined abstractions. Although the problem is in general undecidable, we prove termination of abstraction refinement based verification and falsification of such properties for the class of non-linear robust discrete-time hybrid systems. We argue, that—in industrial practice—safety critical control applications give rise to hybrid systems that are robust. We give first results on the application of this approach to a variant of an aircraft collision avoidance protocol.

We introduce a family of temporal logics to specify the behavior of systems with Zeno behaviors. We extend linear-time temporal logic LTL to authorize models admitting Zeno sequences of actions and quantitative temporal operators indexed by ordinals replace the standard next-time and until future-time operators. Our aim is to control such systems by designing controllers that safely work on ω-sequences but interact synchronously with the system in order to restrict their behaviors. We show that the satisfiability and model-checking for the logics working on ω^k-sequences is EXPSPACE-complete when the integers are represented in binary, and PSPACE-complete with a unary representation. To do so, we substantially extend standard results about LTL by introducing a new class of succinct ordinal automata that can encode the interaction between the different quantitative temporal operators.

We propose a sound and complete compositional proof rule for distributed synthesis. Applying our proof rule only requires the manual strengthening of the specification into a conjunction of formulas that can be guaranteed by individual black-box processes. All premises of the proof rule can be checked automatically.

For this purpose, we give an automata-theoretic synthesis algorithm for single processes in distributed architectures. The behavior of the local environment of a process is unknown in the process of synthesis and cannot be assumed to be maximal. We therefore consider reactive environments that have the power to disable some of their own actions, and provide methods for synthesis (and realizability checking) in this setting. We establish upper bounds for CTL (2EXPTIME) and CTL* (3EXPTIME) synthesis with incomplete information, matching the known lower bounds for these problems, and provide matching upper and lower bounds for μ-calculus synthesis (2EXPTIME) with complete or incomplete information. Synthesis in reactive environments is harder than synthesis in maximal environments, where CTL, CTL* and μ-calculus synthesis are EXPTIME, 2EXPTIME and EXPTIME complete, respectively.

We show that two data structures, min-augmented range tree and priority search pennant, efficiently support all the required operations for updatable IP router tables and argue that both structures are better suited for the one-dimensional dynamic IP lookup problem than the priority search tree (PST) used in a previous solution. It is possible to maintain both structures in time O(1) after a rotation, while PST with n elements may require Ω(log n) steps for a single rotation. Therefore, the proposed structures can be balanced using a larger class of rebalancing schemes compared to PST. Both structures are also of interest independently of the IP lookup problem and may be used as attractive implementations of priority search queues in other contexts as well.

We investigate tissue P systems with symport/antiport with minimal cooperation, i.e., when only 2 objects may interact. We show that 2 cells are enough in order to generate all recursively enumerable sets of numbers. Moreover, constructed systems simulate register machines and have purely deterministic behavior. We also investigate systems with one cell and we show that they may generate only finite sets of numbers.

Culik II and Harju have shown that the ω-equivalence problem is decidable for D0L systems. We give a new proof of this result.