Write a Blog >>
ICPC 2022
Mon 16 - Tue 17 May 2022
co-located with ICSE 2022

Just-In-Time (JIT) defect prediction aims to automatically predict whether a commit is defective or not, and has been widely studied in recent years. In general, most studies can be classified into two categories: 1) simple models using traditional machine learning classifiers with hand-crafted features, and 2) complex models using deep learning techniques to automatically extract features. Hand-crafted features used by simple models are based on expert knowledge but may not fully represent the semantic meaning of the commits. On the other hand, deep learning-based features used by complex models represent the semantic meaning of commits but may not reflect useful expert knowledge. Simple models and complex models seem complementary to each other to some extent. To utilize the advantages of both simple and complex models, we propose a combined model namely SimCom by fusing the prediction scores of one simple and one complex model. The experimental results show that our approach can significantly outperform the state-of-the-art by 6.0–18.1%. In addition, our experimental results confirm that the simple model and complex model are complementary to each other.

Simple or Complex? Together for a More Accurate Just-In-Time Defect Predictor (2022060424.pdf)1014KiB

Mon 16 May

Displayed time zone: Eastern Time (US & Canada) change

08:40 - 09:30
Session 6: Measuring and Improving QualityResearch / Journal First / Tool Demonstration at ICPC room
Chair(s): Mohamed Wiem Mkaouer Rochester Institute of Technology
08:40
7m
Talk
An Approach to Automatically Assess Method Names
Research
Reem S. Alsuhaibani Kent State University, Christian D. Newman Rochester Institute of Technology, Michael J. Decker Bowling Green State University, Michael L. Collard The University of Akron, Jonathan I. Maletic Kent State University
DOI Pre-print Media Attached
08:47
7m
Talk
An Empirical Investigation on the Trade-off between Smart Contract Readability and Gas Consumption
Research
Anna Vacca University of Sannio, Italy, Michele Fredella University of Sannio, Italy, Andrea Di Sorbo University of Sannio, Corrado A. Visaggio University of Sannio, Italy, Gerardo Canfora University of Sannio
Pre-print Media Attached
08:54
4m
Talk
CodePanorama: a language agnostic tool for visual code inspection
Tool Demonstration
Marc Etter OST Eastern Switzerland University of Applied Sciences, Farhad Mehta University of Applied Sciences Rapperswil, Switzerland
Media Attached File Attached
08:58
7m
Talk
Simple or Complex? Together for a More Accurate Just-In-Time Defect Predictor
Research
Xin Zhou , DongGyun Han Singapore Management University, David Lo Singapore Management University
Media Attached File Attached
09:05
7m
Talk
SAVALAN: Multi Objective and Homogeneous Method for Software Modules Clustering
Journal First
Bahman Arasteh Istinye University, Ahmad Fatolahzadeh Islamic Azad University, Farzad Kiani Istinye University
Pre-print Media Attached
09:12
18m
Live Q&A
Q&A-Paper Session 6
Research


Information for Participants