Introduction
Small models beat big ones, on real SE tasks. Rigorously empirical. Proudly irrational. Directed by Tim Menzies, CS, NC State.

Join
reading group, Fall 2026 — easiest way into the lab; open to NC State students and industrial partners

Projects
MOOT benchmark: paper, code explanation & causality: causal graphs, explaining optimizers, ICSE'26 talk optimization: DRR effect, zoom, don't wander, BINGO, how low can you go? agentic systems: AI & productivity, can AI be easy?, warm-up active learning testing: data-centric fuzzing

People
Tim Menzies — director Amirali Rayegan — Ph.D. 2027, causal & explainable analytics Kishan Kumar Ganguly — Ph.D. 2027, sample-efficient optimization Srinath Srinivasan — Ph.D. 2028, agentic LLM systems

Collaborators
Jacky Keung (City U. Hong Kong), Tao Chen (Birmingham), Robert Feldt (Chalmers), Jane Cleland-Huang (Notre Dame)