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An Empirical Study on Logging Evolution On Stack Overflow: Trends, Topics, and Challenges
Patrick Loic Foalem, Andre Nguimbous, Foutse Khomh +2
Context: Logging is a crucial practice in software engineering, aiding developers in debugging applications when errors occur. While existing research has explored logging challeng…
Empirical Characterization of Logging Smells in Machine Learning Code
Patrick Loic Foalem, Leuson Da Silva, Foutse Khomh +2
Logging plays a central role in ensuring reproducibility, observability, and reliability in machine learning (ML) systems. While logging is generally considered a good engineering…
An Empirical Study of Policy-as-Code Adoption in Open-Source Software Projects
Patrick Loic Foalem, Foutse Khomh, Leuson Da Silva +1
\textbf{Context:} Policy-as-Code (PaC) has become a foundational approach for embedding governance, compliance, and security requirements directly into software systems. While orga…
Empirical Characterization of Logging Smells in Machine Learning Code
Patrick Loic Foalem, Leuson Da Silva, Foutse Khomh +2
\underline{Context:} Logging is a fundamental yet complex practice in software engineering, essential for monitoring, debugging, and auditing software systems. With the increasing…
A Story About Cohesion and Separation: Label-Free Metric for Log Parser Evaluation
Qiaolin Qin, Jianchen Zhao, Heng Li +2
Log parsing converts log messages into structured event templates, allowing for automated log analysis and reducing manual inspection effort. To select the most compatible parser f…
Logging Requirement for Continuous Auditing of Responsible Machine Learning-based Applications
Patrick Loic Foalem, Leuson Da Silva, Foutse Khomh +2
Machine learning (ML) is increasingly applied across industries to automate decision-making, but concerns about ethical and legal compliance remain due to limited transparency, fai…
Plug it and Play on Logs: A Configuration-Free Statistic-Based Log Parser
Qiaolin Qin, Xingfang Wu, Heng Li +1
Log parsing is an essential task in log analysis, and many tools have been designed to accomplish it. Existing log parsers can be categorized into statistic-based and semantic-base…
Preprocessing is All You Need: Boosting the Performance of Log Parsers With a General Preprocessing Framework
Qiaolin Qin, Roozbeh Aghili, Heng Li +1
Log parsing has been a long-studied area in software engineering due to its importance in identifying dynamic variables and constructing log templates. Prior work has proposed many…
Automated, Unsupervised, and Auto-parameterized Inference of Data Patterns and Anomaly Detection
Qiaolin Qin, Heng Li, Ettore Merlo +1
With the advent of data-centric and machine learning (ML) systems, data quality is playing an increasingly critical role in ensuring the overall quality of software systems. Data p…