Demo Data from SIGIR 2026 / reviewers in the wild / expert
Lizzie Hernandez
dblp:339/6475
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0000-1823-9990ORCID · 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.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Distributed systems · 100% | |
| Software engineering, system software, and programming languages
1 paper |
Program verification · 100% | |
| Theoretical computer science
1 paper |
Distributed computing theory · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Distributed systems
concurrency |
0.8 | 1 | 2024 | A Universal, Sound, and Complete Forward Reasoning Technique for Machine-Verified Proofs of Linearizability · Proc. ACM Program. Lang. 2024 |
Distributed systems › consistency models
linearizability |
0.8 | 1 | 2024 | A Universal, Sound, and Complete Forward Reasoning Technique for Machine-Verified Proofs of Linearizability · Proc. ACM Program. Lang. 2024 |
Distributed computing theory › shared memory consistency › linearizability
strong linearizability |
0.2 | 1 | 2024 | A Universal, Sound, and Complete Forward Reasoning Technique for Machine-Verified Proofs of Linearizability · Proc. ACM Program. Lang. 2024 |
Methods — techniques the papers use, named apart from their topics
forward reasoning · 2.3TLAPS · 2.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | A Universal, Sound, and Complete Forward Reasoning Technique for Machine-Verified Proofs of LinearizabilityabstractWe introduce simple, universal , sound , and complete proof methods for producing machine-verifiable proofs of linearizability and strong linearizability. Universality means that our method works for any object type; soundness means that an algorithm can be proved correct by our method only if it is linearizable (resp. strong linearizable); and completeness means that any linearizable (resp. strong linearizable) implementation can be proved so using our method. We demonstrate the simplicity and power of our method by producing proofs of linearizability for the Herlihy-Wing queue and Jayanti's single-scanner snapshot, as well as a proof of strong linearizability of the Jayanti-Tarjan union-find object. All three of these proofs are machine-verified by TLAPS (the TLA+ Proof System). Prasad Jayanti, Siddhartha Jayanti, Ugur Y. Yavuz, Lizzie Hernandez |
Proc. ACM Program. Lang. | 4 |