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Sai Ritvik Tanksalkar

dblp:354/4479 · DBLP profile ↗
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3ranked-venue papers
1as first author
3since 2021 · last 2025
0009-0008-6428-0511ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 3 · 1 first-author · 3 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
2 papers
Software testing · 64% Operating systems · 19% Programming languages and type systems · 17%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 100%

Topics — the 2 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Operating systems › operating system family
linux
0.312025
LEMIX: Enabling Testing of Embedded Applications as Linux Applications · USENIX Security Symposium 2025
Programming languages and type systems › language-based security
memory safety
0.212024
Rust for Embedded Systems: Current State and Open Problems · CCS 2024
YearPublicationVenuePosition
2025 LEMIX: Enabling Testing of Embedded Applications as Linux Applications
Sai Ritvik Tanksalkar, Siddharth Muralee, Srihari Danduri, Paschal C. Amusuo, Antonio Bianchi, James C. Davis 0001, Aravind Machiry
USENIX Security Symposium1
2024 Fuzzing API Error Handling Behaviors using Coverage Guided Fault Injection
abstract
Incorrect handling of Software Application Programming Interfaces (APIs) errors results in bugs or security vulnerabilities that are hard to trigger during regular testing. Most of the existing techniques to detect such errors are based on static analysis and fail to identify certain cases where API return values are incorrectly handled. Furthermore, most of these techniques suffer from a very high false positive rate (≥50%), raising concerns regarding their practical use. We propose a dynamic analysis approach to detect API error handling bugs based on coverage-guided software fault injection. Specifically, we inject faults into APIs and observe how a program handles them. Our fault injection mechanism is generic and targeted to explore a given program's error handling behavior effectively. We avoid false positives by proactively filtering out crashes caused by infeasible faults. We implemented our technique in an automated pipeline called FuzzERR and applied it to 20 different programs spanning 444 APIs. Our evaluation shows that FuzzERR found 31 new and previously unknown bugs resulting from incorrect handling of API errors. Moreover, a comparative evaluation showed that FuzzERR significantly outperformed the state-of-the-art tools.
Shashank Sharma 0003, Sai Ritvik Tanksalkar, Sourag Cherupattamoolayil, Aravind Machiry
AsiaCCS2
2024 Rust for Embedded Systems: Current State and Open Problems
Ayushi Sharma 0001, Shashank Sharma 0003, Sai Ritvik Tanksalkar, Santiago Torres-Arias, Aravind Machiry
CCS3