Demo Data from SIGIR 2026 / reviewers in the wild / expert
Emil Tsalapatis
dblp:294/0842
· DBLP profile ↗
3ranked-venue papers
3as first author
3since 2021 · last 2024
0000-0003-2185-2029ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 3 · 3 first-author · 3 since 2021Systems, architecture and hardware · 1 · 1 first-author · 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
2 papers |
Memory systems · 71% Storage systems · 29% | |
| Software engineering, system software, and programming languages
2 papers |
Operating systems · 100% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Operating systems › fault tolerance
checkpoint and rollback |
0.8 | 1 | 2024 | MemSnap μCheckpoints: A Data Single Level Store for Fearless Persistence · ASPLOS (3) 2024 |
Memory systems › memory management
single level store |
0.8 | 1 | 2024 | MemSnap μCheckpoints: A Data Single Level Store for Fearless Persistence · ASPLOS (3) 2024 |
Operating systems › resource management › memory management › virtual memory
single-level store |
0.5 | 1 | 2021 | The Aurora Single Level Store Operating System · SOSP 2021 |
Storage systems › logging
write-ahead logging |
0.2 | 1 | 2024 | MemSnap μCheckpoints: A Data Single Level Store for Fearless Persistence · ASPLOS (3) 2024 |
Storage systems
file systems |
0.1 | 1 | 2021 | The Aurora Single Level Store Operating System · SOSP 2021 |
Memory systems › non-volatile memory
persistent memory |
0.1 | 1 | 2021 | The Aurora Single Level Store Operating System · SOSP 2021 |
Methods — techniques the papers use, named apart from their topics
data checkpointing · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | MemSnap μCheckpoints: A Data Single Level Store for Fearless PersistenceabstractSingle level stores (SLSes) have recently resurfaced as a system for persisting application data. SLSes like EROS, Aurora, and TreeSLS use application checkpointing to replace file-based APIs. These systems checkpoint at a coarse granularity and must be combined with file persistence mechanisms like WALs, undermining the benefits of their SLS design. Emil Tsalapatis, Ryan Hancock, Rakeeb Hossain, Ali José Mashtizadeh |
ASPLOS (3) | 1 |
| 2021 | The Aurora operating system: revisiting the single level storeabstractApplications on modern operating systems manage their ephemeral state in memory, and persistent state on disk. Ensuring consistency between them is a source of significant developer effort, yet still a source of significant bugs in mature applications. We present the Aurora single level store (SLS), an OS that simplifies persistence by automatically persisting all traditionally ephemeral application state. With recent storage hardware like NVMe SSDs and NVDIMMs, Aurora is able to continuously checkpoint entire applications with millisecond granularity. Emil Tsalapatis, Ryan Hancock, Tavian Barnes, Ali José Mashtizadeh |
HotOS | 1 |
| 2021 | The Aurora Single Level Store Operating SystemabstractApplications on modern operating systems manage their ephemeral state in memory and persistent state on disk. Ensuring consistency between them is a source of significant developer effort and application bugs. We present the Aurora single level store, an OS that eliminates the distinction between ephemeral and persistent application state. Emil Tsalapatis, Ryan Hancock, Tavian Barnes, Ali José Mashtizadeh |
SOSP | 1 |