58 citations · 118 across the 5 of their papers we have counts for
5 papers
What Do AI Agents Actually Change? An Empirical Taxonomy of Mutation Patterns in Performance-Improving Pull Requests
Illia Dovhoshliubnyi, Nima Soroush, Ashkan Sami +1
AI coding agents are black boxes: we cannot inspect how they generate code, but we can inspect what they change. This distinction matters for search-based software engineering (SBS…
LLM-Guided Genetic Improvement: Envisioning Semantic Aware Automated Software Evolution
Karine Even-Mendoza, Alexander Brownlee, Alina Geiger +4
Genetic Improvement (GI) of software automatically creates alternative software versions that are improved according to certain properties of interests (e.g., running-time). Search…
Detection of a facemask in real-time using deep learning methods: Prevention of Covid 19
Gautam Siddharth Kashyap, Jatin Sohlot, Ayesha Siddiqui +4
A health crisis is raging all over the world with the rapid transmission of the novel-coronavirus disease (Covid-19). Out of the guidelines issued by the World Health Organisation…
From Simulations to Reality: Enhancing Multi-Robot Exploration for Urban Search and Rescue
Gautam Siddharth Kashyap, Deepkashi Mahajan, Orchid Chetia Phukan +3
In this study, we present a novel hybrid algorithm, combining Levy Flight (LF) and Particle Swarm Optimization (PSO) (LF-PSO), tailored for efficient multi-robot exploration in unk…
Enhancing Genetic Improvement Mutations Using Large Language Models
Alexander E. I. Brownlee, James Callan, Karine Even-Mendoza +5
Large language models (LLMs) have been successfully applied to software engineering tasks, including program repair. However, their application in search-based techniques such as G…