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1. An Algebra of Alignment for Relational Verification

   https://doi.org/10.1145/3571213  

   Antonopoulos, Timos; Koskinen, Eric; Le, Ton Chanh; Nagasamudram, Ramana; Naumann, David A.; Ngo, Minh (January 2023, Proceedings of the ACM on Programming Languages)

   Relational verification encompasses information flow security, regression verification, translation validation for compilers, and more. Effective alignment of the programs and computations to be related facilitates use of simpler relational invariants and relational procedure specs, which in turn enables automation and modular reasoning. Alignment has been explored in terms of trace pairs, deductive rules of relational Hoare logics (RHL), and several forms of product automata. This article shows how a simple extension of Kleene Algebra with Tests (KAT), called BiKAT, subsumes prior formulations, including alignment witnesses for forall-exists properties, which brings to light new RHL-style rules for such properties. Alignments can be discovered algorithmically or devised manually but, in either case, their adequacy with respect to the original programs must be proved; an explicit algebra enables constructive proof by equational reasoning. Furthermore our approach inherits algorithmic benefits from existing KAT-based techniques and tools, which are applicable to a range of semantic models. 

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2. On incorrectness logic and Kleene algebra with top and tests

   https://doi.org/10.1145/3498690  

   Zhang, Cheng; de_Amorim, Arthur_Azevedo; Gaboardi, Marco (January 2022, Proceedings of the ACM on Programming Languages)

   Kleene algebra with tests (KAT) is a foundational equational framework for reasoning about programs, which has found applications in program transformations, networking and compiler optimizations, among many other areas. In his seminal work, Kozen proved that KAT subsumes propositional Hoare logic, showing that one can reason about the (partial) correctness of while programs by means of the equational theory of KAT. In this work, we investigate the support that KAT provides for reasoning about incorrectness, instead, as embodied by O'Hearn's recently proposed incorrectness logic. We show that KAT cannot directly express incorrectness logic. The main reason for this limitation can be traced to the fact that KAT cannot express explicitly the notion of codomain, which is essential to express incorrectness triples. To address this issue, we study Kleene Algebra with Top and Tests (TopKAT), an extension of KAT with a top element. We show that TopKAT is powerful enough to express a codomain operation, to express incorrectness triples, and to prove all the rules of incorrectness logic sound. This shows that one can reason about the incorrectness of while-like programs by means of the equational theory of TopKAT. 

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3. A Kleene Algebra with Tests for Union Bound Reasoning About Probabilistic Programs

   https://doi.org/10.4230/LIPIcs.CSL.2025.35  

   Gomes, Leandro; Baillot, Patrick; Gaboardi, Marco (January 2025, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Endrullis, Jörg; Schmitz, Sylvain (Ed.)

   Kleene Algebra with Tests (KAT) provides a framework for algebraic equational reasoning about imperative programs. The recent variant Guarded KAT (GKAT) allows to reason on non-probabilistic properties of probabilistic programs. Here we introduce an extension of this framework called approximate GKAT (aGKAT), which equips GKAT with a partially ordered monoid (real numbers) enabling to express satisfaction of (deterministic) properties except with a probability up to a certain bound. This allows to represent in equational reasoning "à la KAT" proofs of probabilistic programs based on the union bound, a technique from basic probability theory. We show how a propositional variant of approximate Hoare Logic (aHL), a program logic for union bound, can be soundly encoded in our system aGKAT. We then illustrate the use of aGKAT with an example of accuracy analysis from the field of differential privacy. 

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4. BiGKAT: An Algebraic Framework for Relational Verification of Probabilistic Programs

   https://doi.org/10.1007/978-3-031-90897-2_12  

   Gomes, Leandro; Baillot, Patrick; Gaboardi, Marco (January 2025, Springer Nature Switzerland)

   Abstract This work is devoted to formal reasoning on relational properties of probabilistic imperative programs. Relational properties are properties which relate the execution of two programs (possibly the same one) on two initial memories. We aim at extending the algebraic approach of Kleene Algebras with Tests (KAT) to relational properties of probabilistic programs. For that we consider the approach of Guarded Kleene Algebras with Tests (GKAT), which can be used for representing probabilistic programs, and define a relational version of it, called Bi-guarded Kleene Algebras with Tests (BiGKAT) together with a semantics. We show that the setting of BiGKAT is expressive enough to encode a finitary version of probabilistic Relational Hoare Logic (pRHL) (without the While rule), a program logic that has been introduced in the literature for the verification of relational properties of probabilistic programs. We also discuss the additional expressivity brought by BiGKAT. 

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5. Augmented example-based synthesis using relational perturbation properties

   https://doi.org/10.1145/3371124  

   An, Shengwei; Singh, Rishabh; Misailovic, Sasa; Samanta, Roopsha (December 2019, Proceedings of the ACM on Programming Languages)

   Example-based specifications for program synthesis are inherently ambiguous and may cause synthesizers to generate programs that do not exhibit intended behavior on unseen inputs. Existing synthesis techniques attempt to address this problem by either placing a domain-specific syntactic bias on the hypothesis space or heavily relying on user feedback to help resolve ambiguity. We present a new framework to address the ambiguity/generalizability problem in example-based synthesis. The key feature of our framework is that it places a semantic bias on the hypothesis space using relational perturbation properties that relate the perturbation/change in a program output to the perturbation/change in a program input. An example of such a property is permutation invariance: the program output does not change when the elements of the program input (array) are permuted. The framework is portable across multiple domains and synthesizers and is based on two core steps: (1) automatically augment the set of user-provided examples by applying relational perturbation properties and (2) use a generic example-based synthesizer to generate a program consistent with the augmented set of examples. Our framework can be instantiated with three different user interfaces, with varying degrees of user engagement to help infer relevant relational perturbation properties. This includes an interface in which the user only provides examples and our framework automatically infers relevant properties. We implement our framework in a tool SKETCHAX specialized to the SKETCH synthesizer and demonstrate that SKETCHAX is effective in significantly boosting the performance of SKETCH for all three user interfaces. 

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