The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
On the Temporal Relations between Logging and Code
Abstract
Prior work shows that misleading logging texts (i.e., the textual descriptions in logging statements) can be counterproductive for developers during their use of logs. One of the most important types of information provided by logs is the temporal information of the recorded system behavior. For example, a logging text may use a perfective aspect to describe a fact that an important system event has finished. Although prior work has performed extensive studies on automated logging suggestions, few of these studies investigate the temporal relations between logging and code. In this work, we make the first attempt to comprehensively study the temporal relations between logging and its corresponding source code. In particular, we focus on two types of temporal relations: (1) logical temporal relations, which can be inferred from the execution order between the logging statement and the corresponding source code; and (2) semantic temporal relations, which can be inferred based on the semantic meaning of the logging text. We first perform qualitative analyses to study these two types of logging-code temporal relations and the inconsistency between them. As a result, we derive rules to detect these two types of temporal relations and their inconsistencies. Based on these rules, we propose a tool named TempoLo to automatically detect the issues of temporal inconsistencies between logging and code. Through an evaluation of four projects, we find that TempoLo can effectively detect t…
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“Logs are a crucial source of information in software systems, capturing system runtime behavior and aiding in software engineering tasks like program comprehension [1], [2], anomaly detection [3]- [6], and failure diagnosis [7], [8].”
From Practitioners’ expectations on log anomaly detection (2025) · cites this paper as [2]
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Cited by
Practitioners’ expectations on log anomaly detection
Ma, X., Li, Y., Keung, J., Yu, X., Zou, H., Yang, Z., Sarro, F., & Barr, E. T. (2025) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2025.3586700 · Cited by 21
LogUpdater : Automated Detection and Repair of Specific Defects in Logging Statements
Zhong, R., Li, Y., Kuang, J., Gu, W., Huo, Y., & Lyu, M. R. (2026) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3731754 · Cited by 7
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Metadata
- Authors
- Ding, Z., Tang, Y., Li, Y., Li, H., & Shang, W.
- Venue
- 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)
- Publisher
- IEEE
- Published
- 2023-05
- Pages
- 843-854
- Cited by
- 14
- References
- 43
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- Ding, Z., Tang, Y., Li, Y., Li, H., & Shang, W. (2023). On the Temporal Relations between Logging and Code. 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE). https://doi.org/10.1109/icse48619.2023.00079
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