VLDB 2026 Research / reviewers in the wild / expert
Sunny Wadkar
dblp:281/6601
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none
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 |
Storage systems · 70% Memory systems · 30% | |
| Software engineering, system software, and programming languages
1 paper |
Software testing · 100% |
Topics — the 6 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Storage systems › crash consistency
crash consistency testing |
0.5 | 1 | 2021 | Witcher: Systematic Crash Consistency Testing for Non-Volatile Memory Key-Value Stores · SOSP 2021 |
Storage systems
key-value storage |
0.5 | 1 | 2021 | Witcher: Systematic Crash Consistency Testing for Non-Volatile Memory Key-Value Stores · SOSP 2021 |
Memory systems
non-volatile memory |
0.5 | 1 | 2021 | Witcher: Systematic Crash Consistency Testing for Non-Volatile Memory Key-Value Stores · SOSP 2021 |
Software testing › system software testing
crash consistency testing |
0.1 | 1 | 2021 | Witcher: Systematic Crash Consistency Testing for Non-Volatile Memory Key-Value Stores · SOSP 2021 |
Software testing
systematic testing |
0.1 | 1 | 2021 | Witcher: Systematic Crash Consistency Testing for Non-Volatile Memory Key-Value Stores · SOSP 2021 |
Storage systems
storage reliability |
0.1 | 1 | 2021 | Witcher: Systematic Crash Consistency Testing for Non-Volatile Memory Key-Value Stores · SOSP 2021 |
Methods — techniques the papers use, named apart from their topics
dependency analysis · 1.0crash consistency testing · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Witcher: Systematic Crash Consistency Testing for Non-Volatile Memory Key-Value StoresabstractThe advent of non-volatile main memory (NVM) enables the development of crash-consistent software without paying storage stack overhead. However, building a correct crash-consistent program remains very challenging in the presence of a volatile cache. This paper presents Witcher, a systematic crash consistency testing framework, which detects both correctness and performance bugs in NVM-based persistent key-value stores and underlying NVM libraries, without test space explosion and without manual annotations or crash consistency checkers. To detect correctness bugs, Witcher automatically infers likely correctness conditions by analyzing data and control dependencies between NVM accesses. Then Witcher validates if any violation of them is a true crash consistency bug by checking output equivalence between executions with and without a crash. Moreover, Witcher detects performance bugs by analyzing the execution traces. Evaluation with 20 NVM key-value stores based on Intel's PMDK library shows that Witcher discovers 47 (36 new) correctness consistency bugs and 158 (113 new) performance bugs in both applications and PMDK. Xinwei Fu, Wook-Hee Kim, Ajay Paddayuru Shreepathi, Mohannad Ismail, Sunny Wadkar, Changwoo Min |
SOSP | 5 |