Thu 8 Nov 2018 10:52 - 11:15 at Horizons 10-11 - Models Chair(s): Maurício Aniche

According to
psychological scientists, humans understand models that most match their own internal models,
which they characterize as lists of "heuristic"s (i.e. lists of very succinct rules).
One such heuristic rule generator is the Fast-and-Frugal Trees (FFT) preferred by psychological scientists.
Despite their successful use in many applied domains, FFTs have not been applied in software
Accordingly, this paper assesses FFTs for software analytics.

We find that FFTs are remarkably effective in that their models are very succinct (5 lines or less describing a binary decision tree) while also
outperforming result from very recent, top-level,
conference papers.
Also, when we restrict training data to operational attributes (i.e., those attributes that are frequently changed by developers), the performance of FFTs are not effected
(while the performance of other learners can vary wildly).

Our conclusions are two-fold. Firstly,
there is much that software analytics community could learn from psychological science.
Secondly, proponents of complex methods should always baseline those methods against simpler alternatives.
For example, FFTs could be used as a standard baseline learner against which other software analytics tools are compared.

Thu 8 Nov

Displayed time zone: Guadalajara, Mexico City, Monterrey change

10:30 - 12:00
ModelsResearch Papers / Journal-First at Horizons 10-11
Chair(s): Maurício Aniche Delft University of Technology, Netherlands
The modular and feature toggle architectures of Google Chrome
Applications of Psychological Science for Actionable Analytics
Research Papers
Di Chen North Carolina State University, USA, Wei Fu , Rahul Krishna NC State University, Tim Menzies North Carolina State University
Putback-Based Bidirectional Model Transformations
Research Papers
Xiao He University of Science and Technology Beijing, China, Zhenjiang Hu National Institute of Informatics
Model Transformation Languages under a Magnifying Glass: A Controlled Experiment with Xtend, ATL, and QVT
Research Papers
Regina Hebig Chalmers University of Technology & University of Gothenburg, Christoph Seidl Technische Universität Braunschweig, Thorsten Berger Chalmers University of Technology, Sweden / University of Gothenburg, Sweden, John Kook Pedersen IT University of Copenhagen, Denmark, Andrzej Wąsowski IT University of Copenhagen, Denmark