21 citations · 21 across the 6 of their papers we have counts for
6 papers
SkillMOO: Multi-Objective Optimization of Agent Skills for Software Engineering
Jingzhi Gong, Ruizhen Gu, Zhiwei Fei +7
Agent skills are increasingly used to configure coding agents for software engineering (SE) tasks, yet current practice treats them as static, hand-crafted assets, or evolved on pa…
ROIDS: Robust Outlier-Aware Informed Down-Sampling
Alina Geiger, Martin Briesch, Dominik Sobania +1
Informed down-sampling (IDS) is known to improve performance in symbolic regression when combined with various selection strategies, especially tournament selection. However, recen…
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…
Was Tournament Selection All We Ever Needed? A Critical Reflection on Lexicase Selection
Alina Geiger, Martin Briesch, Dominik Sobania +1
The success of lexicase selection has led to various extensions, including its combination with down-sampling, which further increased performance. However, recent work found that…
A Performance Analysis of Lexicase-Based and Traditional Selection Methods in GP for Symbolic Regression
Alina Geiger, Dominik Sobania, Franz Rothlauf
In recent years, several new lexicase-based selection variants have emerged due to the success of standard lexicase selection in various application domains. For symbolic regressio…
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…