George Zakhour
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Item type:Publication, Metamorphic Testing for Infrastructure-as-Code Engines(2026); ; ; Meier, RolandInfrastructure-as-Code (IaC) engines, such as Terraform, OpenTofu, and Pulumi, automate the provisioning and management of cloud resources. They parse IaC specifications and orchestrate the required actions, making them the backbone of modern clouds, and critical to the reliability of both the underlying infrastructure and the software that depends on it. Despite this importance, this class of systems has received little attention: prior work largely targets the correctness of IaC programs rather than the IaC engines themselves. Existing test suites rely on manually written oracles and struggle to expose faults that manifest across multiple executions, leaving a significant reliability gap. We present EMIaC, a metamorphic testing framework for IaC engines. EMIaC defines metamorphic relations as graph-based transformations of IaC programs and checks invariants across executions of the original and transformed programs. A central novelty is our use of e-graphs in software testing, as both a test-input generator and an equivalence oracle. E-graphs compactly represent program equivalences, enabling the systematic generation of large spaces of equivalent IaC programs. To ground these relations, we analyze 43,593 real-world Terraform programs and show that IaC dependency graphs are typically small and sparse, making e-graphs a natural fit. Evaluating EMIaC on Pulumi, Terraform, and OpenTofu, we show that it complements existing test suites by exercising engine-critical code paths and covering 98 previously untested statements in Terraform and 1,313 in Pulumi. EMIaC also uncovers previously unknown issues in all three test suites, improving their adequacy. Three test cases have been merged into Terraform's main branch, and Pulumi has merged a specification fix.Type:conference paper - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Type-Checking CRDT Convergence(2023-06-06); ; Conflict-Free Replicated Data Types (CRDTs) are a recent approach for keeping replicated data consistent while guaranteeing the absence of conflicts among replicas. For correct operation, CRDTs rely on a merge function that is commutative, associative and idempotent. Ensuring that such algebraic properties are satisfied by implementations, however, is left to the programmer, resulting in a process that is complex and error-prone. While techniques based on testing, automatic verification of a model, and mechanized or handwritten proofs are available, we lack an approach that is able to verify such properties on concrete CRDT implementations. In this paper, we present Propel, a programming language with a type system that captures the algebraic properties required by a correct CRDT implementation. The Propel type system deduces such properties by case analysis and induction: sum types guide the case analysis and algebraic properties in function types enable induction for free. Propel’s key feature is its capacity to reason about algebraic properties (a) in terms of rewrite rules and (b) to derive the equality or inequality of expressions from the properties. We provide an implementation of Propel as a Scala embedding, we implement several CRDTs, verify them with Propel and compare the verification process with four state-of-the-art verification tools. Our evaluation shows that Propel is able to automatically deduce the properties that are relevant for common CRDT implementations found in open-source libraries even in cases in which competitors timeout.Type:conference paperJournal:Proceedings of the ACM on Programming LanguagesVolume:7Issue:PLDIDOI:10.1145/3591276Scopus© Citations 11