ESEIW 2022
Sun 18 - Fri 23 September 2022 Helsinki, Finland
Thu 22 Sep 2022 16:49 - 17:00 at Sonck - Session 3B - Registered Reports 1 Chair(s): Sérgio Soares

Background: Machine Learning (ML) systems rely on data to make predictions, the systems have many added components compared to traditional software systems such as the data processing pipeline, serving pipeline, and model training. Existing research on software maintenance has studied the issue-reporting needs and resolution process for different types of issues, such as performance and security issues. However, ML systems have specific classes of faults, and reporting ML issues requires domain-specific information. Because of the different characteristics between ML and traditional Software Engineering systems, we do not know to what extent the reporting needs are different, and to what extent these differences impact the issue resolution process.

Objective: Our objective is to investigate whether there is a discrepancy in the distribution of resolution time between ML and non-ML issues and whether certain categories of ML issues require a longer time to resolve based on real issue reports in open-source applied ML projects. We further investigate the size of fix of ML issues and non-ML issues.

Method: We extract issues reports, pull requests, and code files in recent active applied ML projects from Github and use an automatic approach to filter ML and non-ML issues. We manually label the issues using a known taxonomy of deep learning bugs. We measure the resolution time and size of fix of ML and non-ML issues on a controlled sample and compare the distributions for each category of issue.

Thu 22 Sep

Displayed time zone: Athens change

15:45 - 17:00
Session 3B - Registered Reports 1ESEM Registered Reports at Sonck
Chair(s): Sérgio Soares Universidade Federal de Pernambuco
The Relevance of Model Transformation Language Features on Qualitative Properties of MTLs: A Study Protocol
ESEM Registered Reports
Stefan Höppner Ulm University, Matthias Tichy Ulm University, Germany
On the acceptance by code reviewers of candidate security patches suggested by Automated Program Repair tools
ESEM Registered Reports
Aurora Papotti Vrije Universiteit Amsterdam, Ranindya Paramitha University of Trento, Fabio Massacci University of Trento; Vrije Universiteit Amsterdam
DOI Pre-print
Does Road Diversity Really Matter in Testing Automated Driving Systems? A Registered Report
ESEM Registered Reports
Stefan Klikovits , Vincenzo Riccio USI Lugano, Ezequiel Castellano National Institute of Informatics, Ahmet Cetinkaya Shibaura Institute of Technology, Alessio Gambi IMC University of Applied Sciences Krems, Paolo Arcaini National Institute of Informatics
Link to publication
A Unified and Holistic Classification Scheme for Software Engineering Research
ESEM Registered Reports
Angelika Kaplan Karlsruhe Institute of Technology, Thomas Kühn Karlsruhe Institute of Technology, Ralf Reussner Karlsruhe Institute of Technology (KIT) and FZI - Research Center for Information Technology (FZI)
Studying the explanations for the automated prediction of bug and non-bug issues using LIME and SHAP
ESEM Registered Reports
Benjamin Ledel TU Clausthal, Steffen Herbold TU Clausthal
Team performance and large-scale agile software development
ESEM Registered Reports
Muhammad Ovais Ahmad Karlstad University, Hadi Ghanbari Aalto University, Tomas Gustavsson Karlstad University
Research paper
Comparative analysis of real bugs in open-source Machine Learning projects - A Registered Report
ESEM Registered Reports
Tuan Dung Lai Deakin University, Anj Simmons Deakin University, Scott Barnett Deakin University, Jean-Guy Schneider Deakin University, Rajesh Vasa Deakin University, Australia
Link to publication Pre-print