8 papers
Agentic Planning for Symbolic Execution
Daniel Koh Ji Yang, Yannic Noller, Corina S. Pasareanu +1
Symbolic execution seeks to explore feasible program paths, yet a practical run may exhaust its resources while much program behaviour remains unreached. We investigate a complemen…
Making Embodied AI Reliable: A Community Agenda from Testing to Formal Verification
Xi Zheng, Dulanga Weerakoon, Yintong Huo +8
Embodied AI systems are increasingly deployed in open-world environments, yet ensuring their reliability remains a fundamental challenge. Drawing on discussions from the AAAI'26 Br…
CONCUR: Benchmarking LLMs for Concurrent Code Generation
Jue Huang, Tarek Mahmud, Corina Pasareanu +1
Leveraging Large Language Models (LLMs) for code generation has increasingly emerged as a common practice in the domain of software engineering. Relevant benchmarks have been estab…
Microsaccade-Inspired Probing: Positional Encoding Perturbations Reveal LLM Misbehaviours
Rui Melo, Rui Abreu, Corina S. Pasareanu
We draw inspiration from microsaccades, tiny involuntary eye movements that reveal hidden dynamics of human perception, to propose an analogous probing method for large language mo…
Agentic AI Software Engineers: Programming with Trust
Abhik Roychoudhury, Corina Pasareanu, Michael Pradel +1
Large Language Models (LLMs) have shown surprising proficiency in generating code snippets, promising to automate large parts of software engineering via artificial intelligence (A…
Worst-Case Symbolic Constraints Analysis and Generalisation with Large Language Models
Daniel Koh, Yannic Noller, Corina S. Pasareanu +2
Large language models (LLMs) have demonstrated strong performance on coding tasks such as generation, completion and repair, but their ability to handle complex symbolic reasoning…