Sökning: "error log clustering"

Visar resultat 1 - 5 av 8 uppsatser innehållade orden error log clustering.

1. 1. Log Frequency Analysis for Anomaly Detection in Cloud Environments

   Master-uppsats, Blekinge Tekniska Högskola/Institutionen för programvaruteknik

   Författare :Prathyusha Bendapudi; [2024]
   Nyckelord :Log Analysis; Log Frequency Patterns; anomaly detection; machine learning; cloud environments;

   Sammanfattning : Background: Log analysis has been proven to be highly beneficial in monitoring system behaviour, detecting errors and anomalies, and predicting future trends in systems and applications. However, with continuous evolution of these systems and applications, the amount of log data generated on a timely basis is increasing rapidly. LÄS MER

3. 2. Log Anomaly Detection of Structured Logs in a Distributed Cloud System

   Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknik

   Författare :David Nilsson; Albin Olsson; [2022]
   Nyckelord :Technology and Engineering;

   Sammanfattning : As computer systems grow larger and more complex, the task of maintaining the system and finding potential security threats or other malfunctions become increasingly hard. Traditionally, this has had to be done by manually examining the logs. LÄS MER

4. 3. NLP-based Failure log Clustering to Enable Batch Log Processing in Industrial DevOps Setting

   Magister-uppsats, Mälardalens universitet/Akademin för innovation, design och teknik

   Författare :Ali Homayouni; [2022]
   Nyckelord :natural language processing; failure clustering; nightly testing; industrial devops;

   Sammanfattning : The rapid development, updating, and maintenance of industrial software systems have increased the necessity for software artifact testing. Some medium and large industries are forced to automate the test analysis process due to the proliferation of test data. LÄS MER

5. 4. Anomaly Detection in Log Files Using Machine Learning Techniques

   Magister-uppsats, Blekinge Tekniska Högskola/Fakulteten för datavetenskaper

   Författare :Lakshmi Geethanjali Mandagondi; [2021]
   Nyckelord :Anomaly Detection; Log Files; Machine Learning; Clustering; Outlier Detection;

   Sammanfattning : Context: Log files are produced in most larger computer systems today which contain highly valuable information about the behavior of the system and thus they are consulted fairly often in order to analyze behavioral aspects of the system. Because of the very high number of log entries produced in some systems, it is however extremely difficult to seek out relevant information in these files. LÄS MER

7. 5. Automated error matching system using machine learning and data clustering : Evaluating unsupervised learning methods for categorizing error types, capturing bugs, and detecting outliers.

   Master-uppsats, Linköpings universitet/Programvara och system

   Författare :Jonatan Bjurenfalk; August Johnson; [2021]
   Nyckelord :Unsupervised learning; machine learning; clustering; DBSCAN; HDBSCAN; X-Means; outlier detection; error log clustering;

   Sammanfattning : For large and complex software systems, it is a time-consuming process to manually inspect error logs produced from the test suites of such systems. Whether it is for identifyingabnormal faults, or finding bugs; it is a process that limits development progress, and requires experience. LÄS MER