## 6 Discussion and Conclusions  
In this paper, we evaluated the compression capacity of an enhanced version of the algorithm that we proposed in [21]. The original algorithm uses template miners to identify the templates. Based on the templates, a dictionary is created where each ID represents an event type. The log lines are then represented using the corresponding ID and parameter list. Using this approach, we were able to achieve around 67% compression rates. To improve this performance, we introduced several enhancements to the algorithm in this paper. First, the templates were ordered based on the number of their occurrences. Smaller IDs were assigned to the more frequent templates. As a second step, we created a dictionary for the templates in a similar manner. This resulted in encoded log messages that only contained numbers. Finally, Huffman coding was used to further compress the file. To analyze the performance of the enhanced algorithm, we conducted several experiments. The experimental results showed that each enhancement improved the compression capacity. The joint use of the parameter dictionary and Huffman coding achieved an average of 92% compression rate, which is 25% more than the original algorithm. In terms of speed, we consider our algorithm to be fast, since it only takes seconds to compress and decompress the investigated log files. We also compared our algorithm with general compressors. While general compressors are faster and achieve better compression rates, around 98%, they are not well suited for statistical applications. With the use of our algorithm, statistical questions such as 'What is the distribution of the templates?' or 'What is the frequency of the different parameters of a message type?' can easily be answered. The instances of given templates can also be found faster than in the case of general compressors. Based on our experiment we would suggest the joint use of our algorithm and general compressors, since it improves the compression rates and functions as a wrapper for the created templates and the encoded file. We only evaluated the performance on static log files, it would be beneficial to measure the compression rate, speed, and memory usage in the case of stream-like data. It would be also interesting to compare the performance of our method with the performance of other general compressors. We also want to investigate the connection between the compression rate and the \(k\)-th order empirical entropy. Conceptualization, P.M., P.L.-K. and A.K. ; methodology, P.M., P.L.-K. and A.K. ; software, P.M. and P.L.-K.; validation, P.M., P.L.-K. and A.K. ; writing-original draft preparation, P.M., P.L.-K. and A.K. ; writing-review and editing, P.M., P.L.-K. and A.K. ; supervision, A.K. ; project administration, A.K. All authors have read and agreed to the published version of the manuscript. Figure 49: The compression rates achieved by our method on the generated datasets. **Funding:** The project has been supported by grants from the \"Application Domain Specific Highly Reliable IT Solutions\" project that has been implemented with the support provided from the National Research, Development, and Innovation Fund of Hungary, financed under the Thematic Excellence Program TKP2020-NKA-06 (National Challenges Subprogram) funding scheme. **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** The data was provided by the Ericsson-ELTE Software Technology Lab. **Acknowledgments:** This publication is the partial result of the Research and Development Operational Program for the project \"Modernisation and Improvement of Technical Infrastructure for Research and Development of J. Selye University in the Fields of Nanotechnology and Intelligent Space\", ITMS 26210120042, co-funded by the European Regional Development Fund and supported by the UNKP-21-3 New National Excellence Program of the Ministry for Innovation and Technology from the source of the National Research, Development, and Innovation Fund.