This short paper takes initial steps towards developing a novel approach, called log slicing, that aims to answer a practical question in the field of log analysis: Can we automatically identify log messages related to a specific message (e.g., an error message)? The basic idea behind log slicing is that we can consider how different log messages are “computationally related” to each other by looking at the corresponding logging statements in the source code. These logging statements are identified by 1) computing a backwards program slice, using as criterion the logging statement that generated a problematic log message; and 2) extending that slice to include relevant logging statements. The paper presents a problem definition of log slicing, describes an initial approach for log slicing, and discusses a key open issue that can lead towards new research directions.
CITATION STYLE
Dawes, J. H., Shin, D., & Bianculli, D. (2023). Towards Log Slicing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13991 LNCS, pp. 249–259). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-30826-0_14
Mendeley helps you to discover research relevant for your work.