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Anthony Vandikas

dblp:241/7113 · DBLP profile ↗
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3ranked-venue papers
1as first author
1since 2021 · last 2026
0009-0001-3926-149XORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 3 · 1 first-author · 1 since 2021Theory of computation · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
2 papers
Program verification · 76% Debugging and program repair · 24%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 100%

Topics — the 4 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Program verification › concurrent program verification
commutativity-based reduction
0.412020
Reductions for safety proofs · Proc. ACM Program. Lang. 2020
Program verification
concurrent program verification
0.412020
Reductions for safety proofs · Proc. ACM Program. Lang. 2020
Debugging and program repair
program reduction
0.412020
Reductions for safety proofs · Proc. ACM Program. Lang. 2020
Program verification › abstraction refinement
counterexample-guided abstraction refinement
0.112019
Automated Hypersafety Verification · CAV (1) 2019

Methods — techniques the papers use, named apart from their topics

floyd-hoare logic · 0.9context-based reduction · 0.9counterexample-guided refinement · 0.4
YearPublicationVenuePosition
2026 Compositional Generator Equivalence
abstract
Property-based testing (PBT) is a powerful technique for software verification that relies on random input generators and ”shrinking” processes to find and minimize counterexamples to executable specifications called properties. While optimizing these generators is crucial for testing efficiency, formally justifying such optimizations is currently difficult because existing languages lack a compositional semantics that is coarse-grained enough for high-level reasoning. In this paper, we first provide a formal account of the syntax and semantics of Hedgehog, a popular PBT framework. We demonstrate that Hedgehog’s distribution semantics — which models how users typically reason about generators — is non-compositional. Furthermore, we prove that any sound and complete compositional semantics for Hedgehog must necessarily be equivalent to its sampling semantics, which is too fine-grained to justify common program optimizations. To resolve this dilemma, we introduce Hedgehog → , a restricted version of the language based on the arrow calculus, and prove that Hedgehog → possesses a compositional distribution semantics. We evaluate Hedgehog → through a Haskell implementation and show that it remains expressive enough to capture generators of practical interest, while providing the formal foundation needed for compositional generator equivalence proofs.
Anthony Vandikas, Kiarash Sotoudeh, Marsha Chechik
Proc. ACM Program. Lang.1
2020 Reductions for safety proofs
abstract
Program reductions are used widely to simplify reasoning about the correctness of concurrent and distributed programs. In this paper, we propose a general approach to proof simplification of concurrent programs based on exploring generic classes of reductions. We introduce two classes of sound program reductions, study their theoretical properties, show how they can be effectively used in algorithmic verification, and demonstrate that they are very effective in producing proofs of a diverse class of programs without targeting specific syntactic properties of these programs. The most novel contribution of this paper is the introduction of the concept of context in the definition of program reductions. We demonstrate how commutativity of program steps in some program contexts can be used to define a generic class of sound reductions which can be used to automatically produce proofs for programs whose complete Floyd-Hoare style proofs are theoretically beyond the reach of automated verification technology of today.
Azadeh Farzan, Anthony Vandikas
Proc. ACM Program. Lang.2
2019 Automated Hypersafety Verification
abstract
We propose an automated verification technique for hypersafety properties, which express sets of valid interrelations between multiple finite runs of a program. The key observation is that constructing a proof for a small representative set of the runs of the product program (i.e. the product of the several copies of the program by itself), called a reduction, is sufficient to formally prove the hypersafety property about the program. We propose an algorithm based on a counterexample-guided refinement loop that simultaneously searches for a reduction and a proof of the correctness for the reduction. We demonstrate that our tool Weaver is very effective in verifying a diverse array of hypersafety properties for a diverse class of input programs.
Azadeh Farzan, Anthony Vandikas
CAV (1)2