As the web game market grows, ensuring service stability through load testing has become increasingly important. Web games comprise a variety of functions with distinct internal logic, ranging from simple data retrieval to complex transaction processing. Therefore, a comparative performance analysis of load-testing tools that accounts for these functional characteristics is crucial for achieving reliable and efficient service operation. This paper evaluates the performance of four widely used load-testing tools—JMeter, k6, Gatling, and Locust—under representative web-game workloads. To emulate realistic database read and write patterns, we implement the core server logic of the web game Pokerogue in a cloud environment rather than simply issuing HTTP requests. We classified workload patterns into write-intensive, read-intensive, and mixed types using distributed tracing, and measured request-generation capability and system resource consumption across five key game functions. Our experiments show that each tool demonstrates distinct strengths depending on the characteristics of individual web-game functions. Specifically, k6 demonstrated high request-generation performance in write-intensive scenarios, while JMeter showed strong performance in read-oriented tasks; Gatling exhibited efficient memory usage in mixed workloads, whereas Locust proved suitable for resource-constrained environments. These results indicate that the selection of a load-testing tool should be informed not only by its request-generation performance but also by the workload characteristics of the target game function. By systematically analyzing function-specific workload patterns together with the performance and resource-usage behavior of each tool, this study aims to provide empirical evidence that can be usefully applied in practical load-testing workflows for web-game services.

The density of sweetpotato whitefly, Bemisia tabaci, on greenhouse paprika (Capsicum annuum var. angulosum) were determined by counts of the number of B. tabaci per leaflet in Jinju, Gyeungsangnamdo during 2014. Binomial sampling plans were developed based on the relationship between the mean density per leaf (m) and the proportion of leaf infested with less than T B. tabaci per leaf (PT), according to empirical model (ln(m) = α + β(ln(-ln(1-PT))). T was defined as tally threshold, and set to 1, 2, 3, 4, 5 (adults) and 1, 3, 5, 7 (pupae) per leaf in this study. Increasing sample size, regardless of tally threshold, had little effects on the precision of the binomial sampling plan. Increasing sample size had little effect on the precision of the estimated mean regardless of tally thresholds. T=1 was chosen as the best tally threshold for estimating densities of B. tabaci adults based on the precision on the model and T=3 was best tally thresholds in B. tabaci pupae. Using the results obtained in the greenhouse, simulated validation of the developed sampling plan by RVSP (Resampling Validation for Sampling Plan) indicated the suitable results.