8 citations · 18 across the 7 of their papers we have counts for
7 papers
LLM Agents for Automated Dependency Upgrades
Vali Tawosi, Salwa Alamir, Xiaomo Liu +1
As a codebase expands over time, its library dependencies can become outdated and require updates to maintain innovation and security. However, updating a library can introduce bre…
Bridging LLM Planning Agents and Formal Methods: A Case Study in Plan Verification
Keshav Ramani, Vali Tawosi, Salwa Alamir +1
We introduce a novel framework for evaluating the alignment between natural language plans and their expected behavior by converting them into Kripke structures and Linear Temporal…
ALMAS: an Autonomous LLM-based Multi-Agent Software Engineering Framework
Vali Tawosi, Keshav Ramani, Salwa Alamir +1
Multi-agent Large Language Model (LLM) systems have been leading the way in applied LLM research across a number of fields. One notable area is software development, where research…
Meta-RAG on Large Codebases Using Code Summarization
Vali Tawosi, Salwa Alamir, Xiaomo Liu +1
Large Language Model (LLM) systems have been at the forefront of applied Artificial Intelligence (AI) research in a multitude of domains. One such domain is software development, w…
Search-based Optimisation of LLM Learning Shots for Story Point Estimation
Vali Tawosi, Salwa Alamir, Xiaomo Liu
One of the ways Large Language Models (LLMs) are used to perform machine learning tasks is to provide them with a few examples before asking them to produce a prediction. This is a…
Software Vulnerability and Functionality Assessment using LLMs
Rasmus Ingemann Tuffveson Jensen, Vali Tawosi, Salwa Alamir
While code review is central to the software development process, it can be tedious and expensive to carry out. In this paper, we investigate whether and how Large Language Models…