Towards a Taxonomy of Software Log Smells
Nyyti Saarim\"aki, Donghwan Shin, Domenico Bianculli

TL;DR
This paper develops a comprehensive taxonomy of log smells in software logging, categorizing common issues and mapping them to existing tools, thereby aiding developers in improving log quality and guiding future research.
Contribution
It introduces the first taxonomy of nine log smells, derived from literature review and coding methods, and analyzes the coverage of current tools for addressing these issues.
Findings
Identified nine distinct log smells affecting log quality.
Mapped existing tools to these smells, revealing gaps in coverage.
Highlighted the importance of addressing log smells throughout the logging lifecycle.
Abstract
Context: Logging is an important part of modern software projects; logs are used in several tasks such as debugging and testing. Due to the complex nature of logging, it remains a difficult task with several pitfalls that could have serious consequences. Several other domains of software engineering have mitigated such threats by identifying the early signs of more serious issues, i.e., 'smells'. However, this concept is not yet properly defined for logging. Objective: The goal of this study is to create a taxonomy of log smells that can help developers write better logging code. To further help the developers and to identify issues that need more attention from the research community, we also map the identified smells to existing tools repairing them. Methods: We conducted a survey of the scientific literature to identify logging issues and related tools. After extracting relevant data…
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Taxonomy
TopicsSoftware System Performance and Reliability · Service-Oriented Architecture and Web Services · Advanced Software Engineering Methodologies
