# New Model for Defining and Implementing Performance Tests
## 2 Literature Review
Ultimately, the authors came to the following conclusions: compared to SoapUI, JMeter is more suitable for client-server architecture. JMeter handles a higher load of HTTP user requests compared to SoapUI, it is also open source and no infrastructure is required for its installation. The tool is based on Java, so it is platform independent. JMeter can be used to test the load of large projects and generate more accurate results in graphs and Extensible Markup Language (XML) formats. The article lacked a representation of what a given test environment looks like. Also, not indicated was the ability to track the occupancy of server resources during testing. Publication [5] proposes a performance testing scheme for mobile applications based on LoadRunner, an automated testing tool developed in the C programming language. The solution supports performance testing of applications in C, Java, Visual Basic (VB), JavaScript, etc. The test tool can generate a large number of concurrent user sessions, or concurrent users, to realize concurrent load. Real-time performance monitoring makes it possible to perform tests on the business system and, consequently, to detect bottlenecks, e.g., detect memory leaks, overloaded components, and other system defects. The tests performed are well described, but the paper does not provide a general scheme for conducting the test and exact methods for tracking key resources of the server under test. The authors of the article [6] describe application performance analysis using Apache-Jmeter, and SoapUI. Apache-Jmeter is pointed out as a useful tool for testing server performance under heavy load. SoapUI, on the other hand, verifies the quality of service of a specific application under variable load. The authors described how load tests should be designed and created a table where it is shown how to identify whether a test is a load test according to various characteristics. The paper [7] analyzed the impact of more realistic dynamic load on network performance metrics. A typical e-commerce scenario was evaluated and various dynamic user behaviors were reproduced. The results were compared with those obtained using traditional workloads. The authors created their test model and showed what their network topology looks like. To define the dynamic workloads, they used the Dweb model, which allows them to model behaviors that cannot be represented with such accuracy using traditional approaches. The authors found that dynamic workloads degraded server performance more than traditional workloads. The authors of the article [8] aimed to present a method for estimating server load based on measurements of external network traffic obtained at an observation point close to the server. In conducting the study, the time from TCP SYN to SYN + ACK segments on the server side was measured. It was found that SRT on servers varies throughout the day depending on their load. The concept introduced in paper [9] describes an AI-based framework for autonomous performance testing of software systems. It uses model-free reinforcement learning (specifically Q-learning) with multiple experience bases to determine performance breaking points for CPU-intensive, memory-intensive, and disk-intensive applications. This approach allows the system to learn and optimize stress testing without relying on performance models. However, the article primarily focuses on describing the framework and its theoretical use, without providing practical examples of its implementation. Publication [10] presents an analysis of indicators and testing methods of the performance testing of the web, and put forward some testing process and methods to optimize the strategy. The paper has the merit of providing a detailed definition of stress and load testing and a number of strategies for optimizing test performance. However, its focus is strictly on web application testing, which limits the broader applicability of the tests. Article [11] demonstrates the usage of the model-driven architecture (MDA) to performance testing.