2 citations · 2 across the 9 of their papers we have counts for
10 papers
AST-PAC: AST-guided Membership Inference for Code
Roham Koohestani, Ali Al-Kaswan, Jonathan Katzy +1
Code Large Language Models are frequently trained on massive datasets containing restrictively licensed source code. This creates urgent data governance and copyright challenges. M…
TriCEGAR: A Trace-Driven Abstraction Mechanism for Agentic AI
Roham Koohestani, Ateş Görpelioğlu, Egor Klimov +2
Agentic AI systems act through tools and evolve their behavior over long, stochastic interaction traces. This setting complicates assurance, because behavior depends on nondetermin…
Does In-IDE Calibration of Large Language Models work at Scale?
Roham Koohestani, Agnia Sergeyuk, David Gros +4
The introduction of large language models into integrated development environments (IDEs) is revolutionizing software engineering, yet it poses challenges to the usefulness and rel…
Code4MeV2: a Research-oriented Code-completion Platform
Roham Koohestani, Parham Bateni, Aydin Ebrahimi +3
The adoption of AI-powered code completion tools in software development has increased substantially, yet the user interaction data produced by these systems remain proprietary wit…
Are Agents Probabilistic Automata? A Trace-Based, Memory-Constrained Theory of Agentic AI
Roham Koohestani, Ziyou Li, Anton Podkopaev +1
This paper studies standard controller architectures for agentic AI and derives automata-theoretic models of their interaction behavior via trace semantics and abstraction. We mode…
AgentGuard: Runtime Verification of AI Agents
Roham Koohestani
The rapid evolution to autonomous, agentic AI systems introduces significant risks due to their inherent unpredictability and emergent behaviors; this also renders traditional veri…
HyperSeq: A Hyper-Adaptive Representation for Predictive Sequencing of States
Roham Koohestani, Maliheh Izadi
In the rapidly evolving world of software development, the surge in developers' reliance on AI-driven tools has transformed Integrated Development Environments into powerhouses of…
Benchmarking AI Models in Software Engineering: A Review, Search Tool, and Unified Approach for Elevating Benchmark Quality
Roham Koohestani, Philippe de Bekker, Begüm Koç +1
Benchmarks are essential for unified evaluation and reproducibility. The rapid rise of Artificial Intelligence for Software Engineering (AI4SE) has produced numerous benchmarks for…
Rethinking IDE Customization for Enhanced HAX: A Hyperdimensional Perspective
Roham Koohestani, Maliheh Izadi
As Integrated Development Environments (IDEs) increasingly integrate Artificial Intelligence, Software Engineering faces both benefits like productivity gains and challenges like m…
Leveraging Large Language Models for Enhancing the Understandability of Generated Unit Tests
Amirhossein Deljouyi, Roham Koohestani, Maliheh Izadi +1
Automated unit test generators, particularly search-based software testing tools like EvoSuite, are capable of generating tests with high coverage. Although these generators allevi…