On Matching Log Analysis to Source Code: A Systematic Mapping Study
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F20%3A00357796" target="_blank" >RIV/68407700:21230/20:00357796 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1145/3400286.3418262" target="_blank" >https://doi.org/10.1145/3400286.3418262</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3400286.3418262" target="_blank" >10.1145/3400286.3418262</a>
Alternative languages
Result language
angličtina
Original language name
On Matching Log Analysis to Source Code: A Systematic Mapping Study
Original language description
Logging is a vital part of the software development process. Developers use program logging to monitor program execution and identify errors and anomalies. These errors may also cause uncaught exceptions and generate stack traces that help identify the point of error. Both of these sources contain information that can be matched to points in the source code, but manual log analysis is challenging for large systems that create large volumes of logs and have large codebases. In this paper, we contribute a systematic mapping study to determine the state-of-the-art tools and methods used to perform automatic log analysis and stack trace analysis and match the extracted information back to the program's source code. We analyzed 16 publications that address this issue, summarizing their strategies and goals, and we identified open research directions from this body of work.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the International Conference on Research in Adaptive and Convergent Systems
ISBN
978-1-4503-8025-6
ISSN
2153-1633
e-ISSN
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Number of pages
7
Pages from-to
181-187
Publisher name
ACM
Place of publication
New York
Event location
Gwangju
Event date
Oct 13, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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