An official website of the United States government
We consider the problem of synthesizing good-enough (GE)-strategies for linear temporal logic (LTL) over finite traces or LTLf for short.The problem of synthesizing GE-strategies for an LTL formula φ over infinite traces reduces to the problem of synthesizing winning strategies for the formula (∃Oφ)⇒φ where O is the set of propositions controlled by the system.We first prove that this reduction does not work for LTLf formulas.Then we show how to synthesize GE-strategies for LTLf formulas via the Good-Enough (GE)-synthesis of LTL formulas.Unfortunately, this requires to construct deterministic parity automata on infinite words, which is computationally expensive.We then show how to synthesize GE-strategies for LTLf formulas by a reduction to solving games played on deterministic Büchi automata, based on an easier construction of deterministic automata on finite words.We show empirically that our specialized synthesis algorithm for GE-strategies outperforms the algorithms going through GE-synthesis of LTL formulas by orders of magnitude.
more »
« less
Quantified Linear Arithmetic Satisfiability via Fine-Grained Strategy Improvement
Abstract Checking satisfiability of formulae in the theory of linear arithmetic has far reaching applications, including program verification and synthesis. Many satisfiability solvers excel at proving and disproving satisfiability of quantifier-free linear arithmetic formulas and have recently begun to support quantified formulas. Beyond simply checking satisfiability of formulas, fine-grained strategies for satisfiability games enables solving additional program verification and synthesis tasks. Quantified satisfiability games are played between two players—SAT and UNSAT—who take turns instantiating quantifiers and choosing branches of boolean connectives to evaluate the given formula. A winning strategy for SAT (resp. UNSAT) determines the choices of SAT (resp. UNSAT) as a function of UNSAT ’s (resp. SAT ’s) choices such that the given formula evaluates to true (resp. false) no matter what choices UNSAT (resp. SAT) may make. As we are interested in both checking satisfiabilityandsynthesizing winning strategies, we must avoid conversion to normal-forms that alter the game semantics of the formula (e.g. prenex normal form). We present fine-grained strategy improvement and strategy synthesis, the first technique capable of synthesizing winning fine-grained strategies for linear arithmetic satisfiability games, which may be used in higher-level applications. We experimentally evaluate our technique and find it performs favorably compared with state-of-the-art solvers.
more »
« less
- Award ID(s):
- 1942537
- PAR ID:
- 10616927
- Publisher / Repository:
- Springer Nature Switzerland
- Date Published:
- Page Range / eLocation ID:
- 89 to 109
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Program verification languages such as Dafny and F$$ ^\star $$ often rely heavily on Satisfiability Modulo Theories (SMT) solvers for proof automation. However, SMT-based verification suffers from instability, where semantically irrelevant changes in the source program can cause spurious proof failures. While existing mitigation techniques emphasize preemptive measures, we propose a complementary approach that focuses on diagnosing and repairing specific instances of instability-induced failures. Our key technique is a novel differential analysis to pinpoint problematic quantified formulas in an unstable query. We implement this technique in Cazamariposas, a tool that automatically identifies such quantified formulas and suggests fixes. We evaluate Cazamariposas on multiple large-scale systems verification projects written in three different program verification languages. Our results demonstrate Cazamariposas ’ effectiveness as an instability debugger. In the majority of cases, Cazamariposas successfully isolates the issue to a single problematic quantifier, while providing a stabilizing fix.more » « less
-
Verification of program safety is often reducible to proving the unsatisfiability (i.e., validity) of a formula in Satisfiability Modulo Theories (SMT): Boolean logic combined with theories that formalize arbitrary first-order fragments. Zeroknowledge (ZK) proofs allow SMT formulas to be validated without revealing the underlying formulas or their proofs to other parties, which is a crucial building block for proving the safety of proprietary programs. Recently, Luo et al. studied the simpler problem of proving the unsatisfiability of pure Boolean formulas but does not support proofs generated by SMT solvers. This work presents ZKSMT, a novel framework for proving the validity of SMT formulas in ZK. We design a virtual machine (VM) tailored to efficiently represent the verification process of SMT validity proofs in ZK. Our VM can support the vast majority of popular theories when proving program safety while being complete and sound. To demonstrate this, we instantiate the commonly used theories of equality and linear integer arithmetic in our VM with theory-specific optimizations for proving them in ZK. ZKSMT achieves high practicality even when running on realistic SMT formulas generated by Boogie, a common tool for software verification. It achieves a three-order-of-magnitude improvement compared to a baseline that executes the proof verification code in a general ZK system.more » « less
-
We present DRYADdec, a decidable logic that allows reasoning about tree data-structures with measurements. This logic supports user-defined recursive measure functions based on Max or Sum, and recursive predicates based on these measure functions, such as AVL trees or red-black trees. We prove that the logic’s satisfiability is decidable. The crux of the decidability proof is a small model property which allows us to reduce the satisfiability of DRYADdec to quantifier-free linear arithmetic theory which can be solved efficiently using SMT solvers. We also show that DRYADdec can encode a variety of verification and synthesis problems, including natural proof verification conditions for functional correctness of recursive tree-manipulating programs, legality conditions for fusing tree traversals, synthesis conditions for conditional linear-integer arithmetic functions. We developed the decision procedure and successfully solved 220+ DRYADdec formulae raised from these application scenarios, including verifying functional correctness of programs manipulating AVL trees, red-black trees and treaps, checking the fusibility of height-based mutually recursive tree traversals, and counterexample-guided synthesis from linear integer arithmetic specifications. To our knowledge, DRYADdec is the first decidable logic that can solve such a wide variety of problems requiring flexible combination of measure-related, data-related and shape-related properties for trees.more » « less
-
Satisfiability (SAT) solvers have been using the same input format for decades: a formula in conjunctive normal form. Cardinality constraints appear frequently in problem descriptions: over 64% of the SAT Competition formulas contain at least one cardinality constraint, while over 17% contain many large cardinality constraints. Allowing general cardinality constraints as input would simplify encodings and enable the solver to handle constraints natively or to encode them using different (and possibly dynamically changing) clausal forms. We modify the modern SAT solver CaDiCaL to handle cardinality constraints natively. Unlike the stronger cardinality reasoning in pseudo-Boolean (PB) or other systems, our incremental approach with cardinality-based propagation requires only moderate changes to a SAT solver, preserves the ability to run important inprocessing techniques, and is easily combined with existing proof-producing and validation tools. Our experimental evaluation on SAT Competition formulas shows our solver configurations with cardinality support consistently outperform other SAT and PB solvers.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Book Chapter:
- https://doi.org/10.1007/978-3-031-65627-9_5
