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A Search-based Approach for Accurate Identification of Log Message Formats
Messaoudi, Salma; Panichella, Annibale; Bianculli, Domenico et al.
2018In Proceedings of the 26th IEEE/ACM International Conference on Program Comprehension (ICPC ’18)
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Keywords :
log parsing; log analysis; log message format; NSGA-II
Abstract :
[en] Many software engineering activities process the events contained in log files. However, before performing any processing activity, it is necessary to parse the entries in a log file, to retrieve the actual events recorded in the log. Each event is denoted by a log message, which is composed of a fixed part-called (event) template-that is the same for all occurrences of the same event type, and a variable part, which may vary with each event occurrence. The formats of log messages, in complex and evolving systems, have numerous variations, are typically not entirely known, and change on a frequent basis; therefore, they need to be identified automatically. The log message format identification problem deals with the identification of the different templates used in the messages of a log. Any solution to this problem has to generate templates that meet two main goals: generating templates that are not too general, so as to distinguish different events, but also not too specific, so as not to consider different occurrences of the same event as following different templates; however, these goals are conflicting. In this paper, we present the MoLFI approach, which recasts the log message identification problem as a multi-objective problem. MoLFI uses an evolutionary approach to solve this problem, by tailoring the NSGA-II algorithm to search the space of solutions for a Pareto optimal set of message templates. We have implemented MoLFI in a tool, which we have evaluated on six real-world datasets, containing log files with a number of entries ranging from 2K to 300K. The experiments results show that MoLFI extracts by far the highest number of correct log message templates, significantly outperforming two state-of-the-art approaches on all datasets.
Research center :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Software Verification and Validation Lab (SVV Lab)
Disciplines :
Computer science
Author, co-author :
Messaoudi, Salma ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Panichella, Annibale ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Bianculli, Domenico  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Briand, Lionel ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Sasnauskas, Raimondas;  Société Européenne des Satellites - SES
External co-authors :
no
Language :
English
Title :
A Search-based Approach for Accurate Identification of Log Message Formats
Publication date :
2018
Event name :
26th IEEE/ACM International Conference on Program Comprehension (ICPC ’18)
Event organizer :
IEEE/ACM
Event place :
Gothenburg, Sweden
Event date :
from 27-05–2018 to 28-05-2018
Audience :
International
Main work title :
Proceedings of the 26th IEEE/ACM International Conference on Program Comprehension (ICPC ’18)
Publisher :
ACM
Pages :
167-177
Peer reviewed :
Peer reviewed
Focus Area :
Security, Reliability and Trust
European Projects :
H2020 - 694277 - TUNE - Testing the Untestable: Model Testing of Complex Software-Intensive Systems
FnR Project :
FNR11602677 - Log-driven, Search-based Test Generation For Ground Control Systems, 2017 (01/01/2018-30/06/2021) - Lionel Briand
Funders :
FNR - Fonds National de la Recherche [LU]
CE - Commission Européenne [BE]
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