Demo Data from EDBT 2026 / reviewers in the wild / expert
Aditya Senthilnathan
dblp:330/8747
· DBLP profile ↗
3ranked-venue papers
0as first author
3since 2021 · last 2024
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 3 · 3 since 2021Theory of computation · 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 |
Software maintenance and evolution · 77% Program analysis · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software maintenance and evolution › software dependencies › software dependency management
dependency update |
0.6 | 1 | 2022 | UPGRADVISOR: Early Adopting Dependency Updates Using Hybrid Program Analysis and Hardware Tracing · OSDI 2022 |
Program analysis
dynamic analysis |
0.2 | 1 | 2022 | UPGRADVISOR: Early Adopting Dependency Updates Using Hybrid Program Analysis and Hardware Tracing · OSDI 2022 |
Methods — techniques the papers use, named apart from their topics
program analysis · 0.6hardware tracing · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Leveraging LLMs for Program Verification
Adharsh Kamath, J. Nausheen Mohammed, Aditya Senthilnathan, Saikat Chakraborty 0001, Pantazis Deligiannis, Shuvendu K. Lahiri, Akash Lal, Aseem Rastogi, Subhajit Roy 0001, Rahul Sharma 0001 |
FMCAD | 3 |
| 2023 | Industrial-Strength Controlled Concurrency Testing for sc C tt # Programs with sc CoyoteabstractAbstract This paper describes the design and implementation of the open-source tool $$\textsc {Coyote} $$ for testing concurrent programs written in the $$\textsc {C}{} \texttt {\#} $$ language. $$\textsc {Coyote} $$ provides algorithmic capabilities to explore the state-space of interleavings of a concurrent program, with deterministic repro for any bug that it finds. $$\textsc {Coyote} $$ encapsulates multiple ideas from the research community to offer state-of-the-art testing for $$\textsc {C}{} \texttt {\#} $$ programs, as well as an efficiently engineered implementation that has been shown robust enough to support industrial use. Pantazis Deligiannis, Aditya Senthilnathan, Fahad Nayyar, Chris Lovett, Akash Lal |
TACAS (2) | 2 |
| 2022 | UPGRADVISOR: Early Adopting Dependency Updates Using Hybrid Program Analysis and Hardware Tracing
Yaniv David, Xudong Sun 0019, Raphael J. Sofaer, Aditya Senthilnathan, Zhiqiang Zuo 0002, Guoqing Harry Xu, Jason Nieh, Ronghui Gu |
OSDI | 4 |