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Miriam Lagunes-Rochin

dblp:423/7407 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0008-9482-3900ORCID · reported

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

Software engineering, systems software and programming languages · 1 · 1 since 2021

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
1 paper
Program verification · 61% Concurrent programming · 30% Program analysis · 9%

Topics — the 2 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Program verification
concurrent program verification
1.012026
The Ghosts of Empires: Extracting Modularity from Interleaving-Based Proofs · Proc. ACM Program. Lang. 2026
Concurrent programming › concurrency verification
thread-modular reasoning
1.012026
The Ghosts of Empires: Extracting Modularity from Interleaving-Based Proofs · Proc. ACM Program. Lang. 2026

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

owicki-gries reasoning · 1.0ghost variable synthesis · 1.0
YearPublicationVenuePosition
2026 The Ghosts of Empires: Extracting Modularity from Interleaving-Based Proofs
abstract
Implementation bugs threaten the soundness of algorithmic software verifiers. Generating correctness certificates for correct programs allows for efficient independent validation of verification results, and thus helps to reveal such bugs. Automatic generation of small, compact correctness proofs for concurrent programs is challenging, as the correctness arguments may depend on the particular interleaving, which can lead to exponential explosion. We present an approach that converts an interleaving-based correctness proof, as generated by many algorithmic verifiers, into a thread-modular correctness proof in the style of Owicki and Gries. We automatically synthesize ghost variables that capture the relevant interleaving information, and abstract away irrelevant details. Our evaluation shows that the approach is efficient in practice and generates compact proofs, compared to a baseline.
Frank Schüssele, Matthias Zumkeller, Miriam Lagunes-Rochin, Dominik Klumpp
Proc. ACM Program. Lang.3