Testing the reliability of an application usually requires a good usage model that accurately captures the likely sequences of inputs that the application will receive from environment. The models being used in the literature are mostly based on Markov chains. They are used to generate test cases that are statistically close to what the application is expected to receive when in production. Based on the study of a specific case of applications, this thesis proposes a model that is created directly from the log file of the web application for reliability testing. Our proposed model is also based on Markov chains and has two components: one component, based on a modified tree, captures the most frequent behavior, while the other component is another Markov chain that captures infrequent behaviors. The result is a statistically correct model that exhibits clearly what most users do on the site.
I will also present an evaluation method for estimating the accuracy of various reliability-testing usage models. The method is based on comparison between observed users’ traces and traces inferred from the usage model. Our method gauges the accuracy of the reliability-testing usage model by calculating the sum of goodness-of-fit values of each traces and scaling the result between 0 and 1.