Blogs (1) >>
ASE 2019
Sun 10 - Fri 15 November 2019 San Diego, California, United States
Tue 12 Nov 2019 17:20 - 17:40 at Cortez 2&3 - Code and Artifact Analysis Chair(s): Sarah Nadi

Execution logs, which are generated by logging code, are widely used in modern software projects for tasks like monitoring, debugging, and remote issue resolution. Ineffective logging would cause confusion, lack of information during problem diagnosis, or even system crash. However, it is challenging to develop and maintain logging code, as it inter-mixes with the feature code. Furthermore, unlike feature code, it is very challenging to verify the correctness of logging code. Currently developers usually rely on their intuition when performing their logging activities. There are no well established logging guidelines in research and practice. In this paper, we intend to derive such guidelines through mining the historical logging code changes. In particular, we have extracted and studied the Logging-Code-Issue-Introducing (LCII) changes in six popular large-scale Java-based open source software systems. Preliminary studies on this dataset show that: (1) both co-changed and independently changed logging code changes can contain fixes to the LCII changes; (2) the complexity of fixes to LCII changes are similar to regular logging code updates; (3) it takes longer for developers to fix logging code issues than regular bugs; and (4) the state-of-the-art logging code issue detection tools can only detect a small fraction (3%) of the LCII changes. This highlights the urgent need for this area of research and the importance of such a dataset.

Conference Day
Tue 12 Nov

Displayed time zone: Tijuana, Baja California change

16:00 - 17:40
Code and Artifact AnalysisJournal First Presentations / Research Papers at Cortez 2&3
Chair(s): Sarah NadiUniversity of Alberta
16:00
20m
Talk
Emotions Extracted from Text vs. True Emotions –An Empirical Evaluation in SE Context
Research Papers
Yi WangRochester Institute of Technology
16:20
20m
Talk
Collaborative feature location in models through automatic query expansion
Journal First Presentations
Francisca PérezSVIT Research GroupUniversidad San Jorge, Jaime FontSan Jorge University, Spain, Lorena ArcegaSan Jorge University, Carlos CetinaSan Jorge University, Spain
Link to publication
16:40
20m
Talk
Learning from Examples to Find Fully Qualified Names of API Elements in Code Snippets
Research Papers
C M Khaled SaifullahDepartment of Computer Science, University of Saskatchewan, Muhammad AsaduzzamanPostdoctoral Research Fellow, Software Analysis and Intelligence Lab, Queen's University, Canada, Chanchal K. RoyUniversity of Saskatchewan
Pre-print
17:00
20m
Talk
Inferring Program Transformations From Singular Examples via Big Code
Research Papers
Jiajun JiangPeking University, Luyao RenPeking University, Yingfei XiongPeking University, Lingming ZhangThe University of Texas at Dallas
Link to publication Pre-print
17:20
20m
Talk
Extracting and studying the Logging-Code-Issue-Introducing changes in Java-based large-scale open source software systems
Journal First Presentations
Boyuan ChenYork University, Zhen Ming (Jack) JiangYork University
Link to publication