Modelling Request Sequences in Online-Connected Video Games

This specification describes a computer-implemented method for testing the performance of a video game server. The method comprises initializing a recurrent neural network. The recurrent neural network is trained based on requests sent from one or more client devices to the video game server. The initializing comprises inputting a start token into the recurrent neural network. An output distribution for a first-time step is generated, as an output of the recurrent neural network. The output distribution comprises a probability of generating each of a set of one or more requests to the video game server, in addition to a probability of generating a stop token. A first request from the set of one or more requests is selected based on the output distribution. The method comprises for one or more further time steps, until a stop token has been selected from output of the recurrent neural network: inputting, into the recurrent neural network, a request selected in the previous time step; generating, as an output of the recurrent neural network, an output distribution for the time step; and selecting, based on the output distribution, a request. A generated sequence of requests is stored. The generated sequence of requests comprises one or more of the requests selected at each respect time step. The generated sequence of requests is inputted into a test generator. A performance test for testing the performance of the video game server is generated by the test generator.