3 papers
cs.SE2026
A Preliminary Study on Explaining Risk of Code Changes using LLM-Based Prediction Models
Yalin Liu, Kosay Jabre, Rui Abreu +10
Predictions by machine learning (ML) and artificial intelligence (AI) models are often received skeptically unless they are paired with intelligible explanations. In the context of…
cs.SE2025
What's DAT? Three Case Studies of Measuring Software Development Productivity at Meta With Diff Authoring Time
Moritz Beller, Amanda Park, Karim Nakad +8
This paper introduces Diff Authoring Time (DAT), a powerful, yet conceptually simple approach to measuring software development productivity that enables rigorous experimentation.…
stat.ML2017
Transfer Learning for Performance Modeling of Configurable Systems: An Exploratory Analysis
Pooyan Jamshidi, Norbert Siegmund, Miguel Velez +3
Modern software systems provide many configuration options which significantly influence their non-functional properties. To understand and predict the effect of configuration opti…