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Noetzold, D., Rossetto, A. G. de M., Silva, L. A., Crocker, P. & Leithardt, V. R. Q. (2024). JVM optimization: An empirical analysis of JVM configurations for enhanced web application performance. SoftwareX. 28
D. Noetzold et al., "JVM optimization: An empirical analysis of JVM configurations for enhanced web application performance", in SoftwareX, vol. 28, 2024
@article{noetzold2024_1732211882426, author = "Noetzold, D. and Rossetto, A. G. de M. and Silva, L. A. and Crocker, P. and Leithardt, V. R. Q.", title = "JVM optimization: An empirical analysis of JVM configurations for enhanced web application performance", journal = "SoftwareX", year = "2024", volume = "28", number = "", doi = "10.1016/j.softx.2024.101933", url = "https://www.sciencedirect.com/journal/softwarex" }
TY - JOUR TI - JVM optimization: An empirical analysis of JVM configurations for enhanced web application performance T2 - SoftwareX VL - 28 AU - Noetzold, D. AU - Rossetto, A. G. de M. AU - Silva, L. A. AU - Crocker, P. AU - Leithardt, V. R. Q. PY - 2024 SN - 2352-7110 DO - 10.1016/j.softx.2024.101933 UR - https://www.sciencedirect.com/journal/softwarex AB - This research presents software for empirically analyzing Java Virtual Machine (JVM) parameter configurations to enhance web application performance. Using tools like JMeter and cAdvisor in a controlled hardware environment, it collects and analyzes performance metrics. Tailored JVM settings for high request loads improved CPU efficiency by 20% and reduced memory usage by 15% compared to standard configurations. For I/O intensive operations with large files, optimized JVM configurations decreased response times by 30% and CPU usage by 25%. These findings highlight the impact of tailored JVM settings on application responsiveness and resource management, providing valuable guidance for developers and engineers. ER -