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Automated verification of refinement laws
Demonic refinement algebras are variants of Kleene algebras. Introduced by von Wright as a light-weight variant of the refinement calculus, their intended semantics are positively disjunctive predicate transformers, and their calculus is entirely within first-order equational logic. So, for the first time, off-the-shelf automated theorem proving (ATP) becomes available for refinement proofs. We used ATP to verify a toolkit of basic refinement laws. Based on this toolkit, we then verified two classical complex refinement laws for action systems by ATP: a data refinement law and Back's atomicity refinement law. We also present a refinement law for infinite loops that has been discovered through automated analysis. Our proof experiments not only demonstrate that refinement can effectively be automated, they also compare eleven different ATP systems and suggest that program verification with variants of Kleene algebras yields interesting theorem proving benchmarks. Finally, we apply hypothesis learning techniques that seem indispensable for automating more complex proofs
Compensation methods to support cooperative applications: A case study in automated verification of schema requirements for an advanced transaction model
Compensation plays an important role in advanced transaction models, cooperative work and workflow systems. A schema designer is typically required to supply for each transaction another transaction to semantically undo the effects of . Little attention has been paid to the verification of the desirable properties of such operations, however. This paper demonstrates the use of a higher-order logic theorem prover for verifying that compensating transactions return a database to its original state. It is shown how an OODB schema is translated to the language of the theorem prover so that proofs can be performed on the compensating transactions
Completeness for a First-order Abstract Separation Logic
Existing work on theorem proving for the assertion language of separation
logic (SL) either focuses on abstract semantics which are not readily available
in most applications of program verification, or on concrete models for which
completeness is not possible. An important element in concrete SL is the
points-to predicate which denotes a singleton heap. SL with the points-to
predicate has been shown to be non-recursively enumerable. In this paper, we
develop a first-order SL, called FOASL, with an abstracted version of the
points-to predicate. We prove that FOASL is sound and complete with respect to
an abstract semantics, of which the standard SL semantics is an instance. We
also show that some reasoning principles involving the points-to predicate can
be approximated as FOASL theories, thus allowing our logic to be used for
reasoning about concrete program verification problems. We give some example
theories that are sound with respect to different variants of separation logics
from the literature, including those that are incompatible with Reynolds's
semantics. In the experiment we demonstrate our FOASL based theorem prover
which is able to handle a large fragment of separation logic with heap
semantics as well as non-standard semantics.Comment: This is an extended version of the APLAS 2016 paper with the same
titl
Applying Formal Methods to Networking: Theory, Techniques and Applications
Despite its great importance, modern network infrastructure is remarkable for
the lack of rigor in its engineering. The Internet which began as a research
experiment was never designed to handle the users and applications it hosts
today. The lack of formalization of the Internet architecture meant limited
abstractions and modularity, especially for the control and management planes,
thus requiring for every new need a new protocol built from scratch. This led
to an unwieldy ossified Internet architecture resistant to any attempts at
formal verification, and an Internet culture where expediency and pragmatism
are favored over formal correctness. Fortunately, recent work in the space of
clean slate Internet design---especially, the software defined networking (SDN)
paradigm---offers the Internet community another chance to develop the right
kind of architecture and abstractions. This has also led to a great resurgence
in interest of applying formal methods to specification, verification, and
synthesis of networking protocols and applications. In this paper, we present a
self-contained tutorial of the formidable amount of work that has been done in
formal methods, and present a survey of its applications to networking.Comment: 30 pages, submitted to IEEE Communications Surveys and Tutorial
Graph Representations for Higher-Order Logic and Theorem Proving
This paper presents the first use of graph neural networks (GNNs) for
higher-order proof search and demonstrates that GNNs can improve upon
state-of-the-art results in this domain. Interactive, higher-order theorem
provers allow for the formalization of most mathematical theories and have been
shown to pose a significant challenge for deep learning. Higher-order logic is
highly expressive and, even though it is well-structured with a clearly defined
grammar and semantics, there still remains no well-established method to
convert formulas into graph-based representations. In this paper, we consider
several graphical representations of higher-order logic and evaluate them
against the HOList benchmark for higher-order theorem proving
Upside-down Deduction
Over the recent years, several proposals were made to enhance database systems with automated reasoning. In this article we analyze two such enhancements based on meta-interpretation. We consider on the one hand the theorem prover Satchmo, on the other hand the Alexander and Magic Set methods. Although they achieve different goals and are based on distinct reasoning paradigms, Satchmo and the Alexander or Magic Set methods can be similarly described by upside-down meta-interpreters, i.e., meta-interpreters implementing one reasoning principle in terms of the other. Upside-down meta-interpretation gives rise to simple and efficient implementations, but has not been investigated in the past. This article is devoted to studying this technique. We show that it permits one to inherit a search strategy from an inference engine, instead of implementing it, and to combine bottom-up and top-down reasoning. These properties yield an explanation for the efficiency of Satchmo and a justification for the unconventional approach to top-down reasoning of the Alexander and Magic Set methods
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