Failure Prediction by Utilizing Log Analysis: A Systematic Mapping Study

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F20%3A00352540" target="_blank" >RIV/68407700:21230/20:00352540 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1145/3400286.3418263" target="_blank" >https://doi.org/10.1145/3400286.3418263</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3400286.3418263" target="_blank" >10.1145/3400286.3418263</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Failure Prediction by Utilizing Log Analysis: A Systematic Mapping Study

Popis výsledku v původním jazyce

In modern computing, log files provide a wealth of information regarding the past of a system, including the system failures and security breaches that cost companies and developers a fortune in both time and money. While this information can be used to attempt to recover from a problem, such an approach merely mitigates the damage that has already been done. Detecting problems, however, is not the only information that can be gathered from log files. It is common knowledge that segments of log files, if analyzed correctly, can yield a good idea of what the system is likely going to do next in real-time, allowing a system to take corrective action before any negative actions occur. In this paper, the authors put forth a systematic map of this field of log prediction, screening several hundred papers and finally narrowing down the field to approximately 30 relevant papers. These papers, when broken down, give a good idea of the state of the art, methodologies employed, and future challenges that still must be overcome. Findings and conclusions of this study can be applied to a variety of software systems and components, including classical software systems, as well as software parts of control, or the Internet of Things (IoT) systems.

Název v anglickém jazyce

Failure Prediction by Utilizing Log Analysis: A Systematic Mapping Study

Popis výsledku anglicky

In modern computing, log files provide a wealth of information regarding the past of a system, including the system failures and security breaches that cost companies and developers a fortune in both time and money. While this information can be used to attempt to recover from a problem, such an approach merely mitigates the damage that has already been done. Detecting problems, however, is not the only information that can be gathered from log files. It is common knowledge that segments of log files, if analyzed correctly, can yield a good idea of what the system is likely going to do next in real-time, allowing a system to take corrective action before any negative actions occur. In this paper, the authors put forth a systematic map of this field of log prediction, screening several hundred papers and finally narrowing down the field to approximately 30 relevant papers. These papers, when broken down, give a good idea of the state of the art, methodologies employed, and future challenges that still must be overcome. Findings and conclusions of this study can be applied to a variety of software systems and components, including classical software systems, as well as software parts of control, or the Internet of Things (IoT) systems.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the International Conference on Research in Adaptive and Convergent Systems

ISBN

978-1-4503-8025-6

ISSN

2153-1633

e-ISSN

—

Počet stran výsledku

8

Strana od-do

188-195

Název nakladatele

ACM

Místo vydání

New York

Místo konání akce

Gwangju

Datum konání akce

13. 10. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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