11 citations · 23 across the 15 of their papers we have counts for
16 papers
Do Agents Dream of Root Shells? Partial-Credit Evaluation of LLM Agents in Capture the Flag Challenges
Ali Al-Kaswan, Maksim Plotnikov, Maxim Hájek +3
Large Language Model (LLM) agents are increasingly proposed for autonomous cybersecurity tasks, but their capabilities in realistic offensive settings remain poorly understood. We…
Automated Attention Pattern Discovery at Scale in Large Language Models
Jonathan Katzy, Razvan-Mihai Popescu, Erik Mekkes +2
Large language models have found success by scaling up capabilities to work in general settings. The same can unfortunately not be said for interpretability methods. The current tr…
Investigating Autonomous Agent Contributions in the Wild: Activity Patterns and Code Change over Time
Razvan Mihai Popescu, David Gros, Andrei Botocan +3
The rise of large language models for code has reshaped software development. Autonomous coding agents, able to create branches, open pull requests, and perform code reviews, now a…
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…
Developer Interaction Patterns with Proactive AI: A Five-Day Field Study
Nadine Kuo, Agnia Sergeyuk, Valerie Chen +1
Current in-IDE AI coding tools typically rely on time-consuming manual prompting and context management, whereas proactive alternatives that anticipate developer needs without expl…
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…
Prompt-with-Me: in-IDE Structured Prompt Management for LLM-Driven Software Engineering
Ziyou Li, Agnia Sergeyuk, Maliheh Izadi
Large Language Models are transforming software engineering, yet prompt management in practice remains ad hoc, hindering reliability, reuse, and integration into industrial workflo…
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…
Human-AI Experience in Integrated Development Environments: A Systematic Literature Review
Agnia Sergeyuk, Ilya Zakharov, Ekaterina Koshchenko +1
The integration of Artificial Intelligence (AI) into Integrated Development Environments (IDEs) is reshaping software development, fundamentally altering how developers interact wi…
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…
Automating the Detection of Code Vulnerabilities by Analyzing GitHub Issues
Daniele Cipollone, Changjie Wang, Mariano Scazzariello +4
In today's digital landscape, the importance of timely and accurate vulnerability detection has significantly increased. This paper presents a novel approach that leverages transfo…
Developer Needs and Feasible Features for AI Assistants in IDEs
Agnia Sergeyuk, Ekaterina Koshchenko, Ilya Zakharov +2
Despite the increasing presence of AI assistants in Integrated Development Environments (IDEs), it remains unclear what different groups of developers actually need from these tool…
Creativity, Generative AI, and Software Development: A Research Agenda
Victoria Jackson, Bogdan Vasilescu, Daniel Russo +7
Creativity has always been considered a major differentiator to separate the good from the great, and we believe the importance of creativity for software development will only inc…