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Mohammad Omidvar Tehrani

dblp:351/6692 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2025
0009-0004-0078-0366ORCID · corroborated

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

Computer networks · 1 · 1 since 2021Software 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.

Software engineering, system software, and programming languages
2 papers
Program verification · 47% Software testing · 36% Program analysis · 18%
Network and information security
1 paper
Network security · 100%
Theoretical computer science
1 paper
Automata and formal languages · 100%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Program verification › refinement
refinement proof
0.912025
Formalization, Implementation, and Verification of the Bluetooth L2CAP State Machine · MobiCom 2025
Program verification › model-based verification
state machine verification
0.912025
Formalization, Implementation, and Verification of the Bluetooth L2CAP State Machine · MobiCom 2025
Program analysis › symbolic execution
dynamic symbolic execution
0.712023
SymRustC: A Hybrid Fuzzer for Rust · ISSTA 2023
Software testing
fuzzing
0.712023
SymRustC: A Hybrid Fuzzer for Rust · ISSTA 2023
Software testing › fuzzing
hybrid fuzzing
0.712023
SymRustC: A Hybrid Fuzzer for Rust · ISSTA 2023
Network security › wireless network security
bluetooth security
0.312025
Formalization, Implementation, and Verification of the Bluetooth L2CAP State Machine · MobiCom 2025
Automata and formal languages
finite automata
0.312025
Formalization, Implementation, and Verification of the Bluetooth L2CAP State Machine · MobiCom 2025

Methods — techniques the papers use, named apart from their topics

refinement · 2.6formal specification · 2.6dafny · 2.6fuzzing · 0.7concolic execution · 0.7
YearPublicationVenuePosition
2025 Formalization, Implementation, and Verification of the Bluetooth L2CAP State Machine
abstract
The Logical Link Control and Adaptation Protocol (L2CAP) is a core Bluetooth component, and verifying its correctness is crucial for reliable and secure connectivity. However, verification can be challenging due to the complexity and ambiguities in its natural language (English) specification. In this paper, we present a formally verified implementation of the L2CAP state machine. Our approach introduces the Specification State Machine (SSM) to formalize the L2CAP state machine in the specification and the Operational State Machine (OSM) as an abstraction of the implementation. We then formally prove that (i) OSM refines SSM, and (ii) our implementation semantically conforms to OSM. By combining these two proofs, we verify that our implementation complies with our formalization of the specification. Furthermore, we define critical safety and liveness properties and formally prove that our implementation satisfies these guarantees. To ensure practicality, we implement the L2CAP state machine in Dafny and integrate it into Android's Fluoride Bluetooth stack. Our evaluation demonstrates that our formally verified implementation maintains competitive performance while ensuring formal correctness.
Tan Khang Le, Mohammad Omidvar Tehrani, Yuepeng Wang 0001, Jianliang Wu 0002, Steven Y. Ko
MobiCom2
2023 SymRustC: A Hybrid Fuzzer for Rust
abstract
We present SymRustC, a hybrid fuzzer for Rust. SymRustC is hybrid in the sense that it combines fuzzing and concolic execution. SymRustC leverages an existing tool called SymCC for its concolic execution capability and another existing tool called LibAFL for its fuzzing capability. Since SymCC instruments LLVM IR (Intermediate Representation) for concolic execution and the Rust compiler uses LLVM as a backend, we integrate SymCC with the Rust compiler to instrument Rust programs for concolic execution. LibAFL provides a framework to develop a fuzzer, and we use it to develop a hybrid fuzzer that combines fuzzing and our concolic execution. We discuss our implementation as well as four case studies to demonstrate that SymRustC can generate inputs that discover errors in Rust programs.
Frédéric Tuong, Mohammad Omidvar Tehrani, Marco Gaboardi, Steven Y. Ko
ISSTA2