Sharing Data and Models in Software Engineering

Chapter 19

Sharing Models

Challenges and Methods

Abstract

This part of Data Science for Software Engineering: Sharing Data and Models explores ensemble learners and multiobjective optimizers as applied to software engineering. Novel incremental ensemble learners are explained along with one of the largest ensemble learning (in effort estimation) experiments yet attempted. It turns out that the specific goals of the learning has an effect on what is learned and, for this reason, this part also explores multigoal reasoning. We show that multigoal optimizers can significantly improve effort estimation results.

So far, we have been concerned with sharing data from one project to another. Now we turn to a more complex issue—how to share models ...