Causality-Based Game Solving

We present a causality-based algorithm for solving two-player reachability games represented by logical constraints. These games are a useful formalism to model a wide array of problems arising, e.g., in program synthesis. Our technique for solving these games is based on the notion of subgoals, which are slices of the game that the reachability player necessarily needs to pass through in order to reach the goal. We use Craig interpolation to identify these necessary sets of moves and recursively slice the game along these subgoals. Our approach allows us to infer winning strategies that are structured along the subgoals. If the game is won by the reachability player, this is a strategy that progresses through the subgoals towards the final goal; if the game is won by the safety player, it is a permissive strategy that completely avoids a single subgoal. We evaluate our prototype implementation on a range of different games. On multiple benchmark families, our prototype scales dramatically better than previously available tools.

Interpolation and Amalgamation for Arrays with MaxDiff

In this paper, the theory of McCarthy’s extensional arrays enriched with a maxdiff operation (this operation returns the biggest index where two given arrays differ) is proposed. It is known from the literature that a diff operation is required for the theory of arrays in order to enjoy the Craig interpolation property at the quantifier-free level. However, the diff operation introduced in the literature is merely instrumental to this purpose and has only a purely formal meaning (it is obtained from the Skolemization of the extensionality axiom). Our maxdiff operation significantly increases the level of expressivity; however, obtaining interpolation results for the resulting theory becomes a surprisingly hard task. We obtain such results via a thorough semantic analysis of the models of the theory and of their amalgamation properties. The results are modular with respect to the index theory and it is shown how to convert them into concrete interpolation algorithms via a hierarchical approach.

RESTRICTED INTERPOLATION AND LACK THEREOF IN STIT LOGIC

We consider the propositional logic equipped with Chellas stit operators for a finite set of individual agents plus the historical necessity modality. We settle the question of whether such a logic enjoys restricted interpolation property, which requires the existence of an interpolant only in cases where the consequence contains no Chellas stit operators occurring in the premise. We show that if action operators count as logical symbols, then such a logic has restricted interpolation property iff the number of agents does not exceed three. On the other hand, if action operators are considered to be nonlogical symbols, then the restricted interpolation fails for any number of agents exceeding one. It follows that unrestricted Craig interpolation also fails for almost all versions of stit logic.

Localizing predicate activity in resolution proofs

A theorem is proven regarding our ability to construct resolution proofs with certain structural properties. This theorem is then used to provide a new constructive proof of the Craig Interpolation Theorem for Classical First Order Logic.

Algebraic Characterization of the Local Craig Interpolation Property

The sole purpose of this paper is to give an algebraic characterization, in terms of a superamalgamation property, of a local version of Craig interpolation theorem that has been introduced and studied in earlier papers. We continue ongoing research in abstract algebraic logic and use the framework developed by Andréka– Németi and Sain.

Quantified Heap Invariants for Object-Oriented Programs

Heap and data structures represent one of the biggest challenges when applying model checking to the analysis of software programs: in order to verify (unbounded) safety of a program, it is typically necessary to formulate quantified inductive invariants that state properties about an unbounded number of heap locations. Methods like Craig interpolation, which are commonly used to infer invariants in model checking, are often ineffective when a heap is involved. To address this challenge, we introduce a set of new proof and program transformation rules for verifying object-oriented programs with the help of space invariants, which (implicitly) give rise to quantified invariants. Leveraging advances in Horn solving, we show how space invariants can be derived fully automatically, and how the framework can be used to effectively verify safety of Java programs.

Craig Interpolation for the Integers: Results, Implementation, and Experiences

Craig interpolation is a versatile tool in formal verification, in particular for generating intermediate assertions in safety analysis and model checking. Over the last years, a variety of interpolation procedures for linear integer arithmetic (and extensions) have been developed. I will give an overview of the existing algorithms and design choices, and then discuss implementations of such procedures within theorem provers and SMT solvers. In particular, I will describe an implementation done using the multi-paradigm language Scala, which is built on top of the Java runtime infrastructure, and evaluate performance and engineering aspects.

Program Verification via Craig Interpolation for Presburger Arithmetic with Arrays

Craig interpolation has become a versatile tool in formal verification, in particular for generating intermediate assertions in safety analysis and model checking. In this paper, we present a novel interpolation procedure for the theory of arrays, extending an interpolating calculus for the full theory of quantifier-free Presburger arithmetic, which will be presented at IJCAR this year. We investigate the use of this procedure in a software model checker for C programs. A distinguishing feature of the model checker is its ability to faithfully model machine arithmetic with an encoding into Presburger arithmetic with uninterpreted predicates. The interpolation procedure allows the synthesis of quantified invariants about arrays. This paper presents work in progress; we include initial experiments to demonstrate the potential of our method.