Demo Data from SIGIR 2026 / reviewers in the wild / expert
Diptanshu Kakwani
dblp:241/6310
· 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.
| Databases, data mining, and information retrieval
1 paper |
Transaction processing and concurrency control · 100% | |
| Software engineering, system software, and programming languages
1 paper |
Software testing · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Storage systems · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Transaction processing and concurrency control
isolation levels |
0.5 | 1 | 2021 | MonkeyDB: effectively testing correctness under weak isolation levels · Proc. ACM Program. Lang. 2021 |
Software testing
test generation |
0.5 | 1 | 2021 | MonkeyDB: effectively testing correctness under weak isolation levels · Proc. ACM Program. Lang. 2021 |
Storage systems
key-value storage |
0.1 | 1 | 2021 | MonkeyDB: effectively testing correctness under weak isolation levels · Proc. ACM Program. Lang. 2021 |
Methods — techniques the papers use, named apart from their topics
random value selection · 1.5logical specification of isolation levels · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | MonkeyDB: effectively testing correctness under weak isolation levelsabstractModern applications, such as social networking systems and e-commerce platforms are centered around using large-scale storage systems for storing and retrieving data. In the presence of concurrent accesses, these storage systems trade off isolation for performance. The weaker the isolation level, the more behaviors a storage system is allowed to exhibit and it is up to the developer to ensure that their application can tolerate those behaviors. However, these weak behaviors only occur rarely in practice and outside the control of the application, making it difficult for developers to test the robustness of their code against weak isolation levels. This paper presents MonkeyDB, a mock storage system for testing storage-backed applications. MonkeyDB supports a key-value interface as well as SQL queries under multiple isolation levels. It uses a logical specification of the isolation level to compute, on a read operation, the set of all possible return values. MonkeyDB then returns a value randomly from this set. We show that MonkeyDB provides good coverage of weak behaviors, which is complete in the limit. We test a variety of applications for assertions that fail only under weak isolation. MonkeyDB is able to break each of those assertions in a small number of attempts. Ranadeep Biswas, Diptanshu Kakwani, Jyothi Vedurada, Constantin Enea, Akash Lal |
Proc. ACM Program. Lang. | 2 |