5 papers
Better Together, in the Right Order: Classical-then-LLM Optimization for SE
Srinath Srinivasan, Tim Menzies
A growing body of work combines large language models (LLMs) with classical optimizers for software engineering (SE) configuration tasks. Often, the classical optimizer is in charg…
Can AI be Easy? Lessons Learned from the EZR.py Toolkit
Tim Menzies, Srinath Srinivasan
Much recent press claims that developers no longer need to read code. We disagree, at least within the domain of tabular software-engineering (SE) optimization tasks: rows of a…
From Brittle to Robust: Improving LLM Annotations for SE Optimization
Lohith Senthilkumar, Tim Menzies
Software analytics often builds from labeled data. Labeling can be slow, error prone, and expensive. When human expertise is scarce, SE researchers sometimes ask large language mod…
Beyond the Prompt: Assessing Domain Knowledge Strategies for High-Dimensional LLM Optimization in Software Engineering
Srinath Srinivasan, Tim Menzies
Background/Context: Large Language Models (LLMs) demonstrate strong performance on low-dimensional software engineering optimization tasks (11 features) but consistently under…
SmartOracle -- An Agentic Approach to Mitigate Noise in Differential Oracles
Srinath Srinivasan, Tim Menzies, Marcelo D'Amorim
Differential fuzzers detect bugs by executing identical inputs across distinct implementations of the same specification, such as JavaScript interpreters. Validating the outputs re…