Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Systematic Error: Methodological and Sampling Errors

Systematic Error: Methodological and Sampling Errors

In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...

Applications of Logarithms

Applications of Logarithms

Logarithmic functions are powerful tools for simplifying the mathematical representation of phenomena involving exponential changes. Their ability to convert multiplicative relationships into additive ones is especially valuable in various scientific and engineering contexts. One notable application of logarithms is measuring sound intensity, specifically through the decibel (dB) scale used in acoustics.Sound intensity levels vary over an extensive range, from the faintest audible whisper to...

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device

Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

The effects of change decomposition on code review-a controlled experiment.

PeerJ. Computer science·2021

See all related articles

Search research articles

Related Experiment Video

Updated: Nov 5, 2025

Measuring Light-Switching Behavior Using an Occupancy and Light Data Logger

Measuring Light-Switching Behavior Using an Occupancy and Light Data Logger

Published on: January 16, 2020

Log-based software monitoring: a systematic mapping study.

Jeanderson Cândido^1,2, Maurício Aniche¹, Arie van Deursen¹

¹Department of Software Technology, Delft University of Technology, Delft, Netherlands.

Peerj. Computer Science

|May 20, 2021

Summary

Software logging and analysis are challenging in both industry and open-source projects. Machine learning shows promise for log recommendation, but practical usability requires further study, with opportunities in log analysis and DevOps integration.

Keywords:

DevOps Log analysis Log infrastructure Logging practices Monitoring

More Related Videos

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

Published on: July 27, 2018

High-Throughput Analysis of Optical Mapping Data Using ElectroMap

High-Throughput Analysis of Optical Mapping Data Using ElectroMap

Published on: June 4, 2019

Related Experiment Videos

Last Updated: Nov 5, 2025

Measuring Light-Switching Behavior Using an Occupancy and Light Data Logger

Measuring Light-Switching Behavior Using an Occupancy and Light Data Logger

Published on: January 16, 2020

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

Published on: July 27, 2018

High-Throughput Analysis of Optical Mapping Data Using ElectroMap

High-Throughput Analysis of Optical Mapping Data Using ElectroMap

Published on: June 4, 2019

Area of Science:

Software Engineering
Machine Learning
Systems Research

Background:

Modern software development and operations heavily depend on system monitoring for reliability and issue diagnosis.
Application logs and runtime data are crucial for detecting and resolving system failures, yet extracting insights remains a significant challenge.
Existing log solutions face difficulties in monitoring complex systems and deriving meaningful information.

Purpose of the Study:

To provide a holistic overview of research on logging practices and automated log analysis.
To structure the field based on the log data life-cycle for technology transfer.
To identify challenges and opportunities in log data management and analysis.

Main Methods:

Systematic literature review of 108 papers from diverse research communities (machine learning, software engineering, systems).
Analysis of papers categorized into research track, journals, and industry track.
Structuring the research landscape according to the log data life-cycle.

Main Results:

Logging presents challenges across both open-source and industrial software development.
Machine learning offers potential for log recommendation through source code analysis, but practical application and usability need further validation.
Limited research has focused on efficient log data persistence.
Significant opportunities exist for analyzing application logs and evaluating advanced log analysis techniques within DevOps environments.

Conclusions:

A comprehensive understanding of logging research is vital for advancing the field and facilitating technology transfer.
While machine learning shows promise, practical adoption of log analysis tools requires addressing usability concerns.
Efficient log data management and the application of modern analysis techniques in DevOps are key areas for future research and development.