Generating probabilistic and intensity-varying workload for Web-based software systems

Abstract This paper presents an approach and a corresponding tool for generating probabilistic and intensity-varying workload for Web-based software systems. The workload to be generated is specified in two types of models. An application model specifies the possible interactions with the Web-based software system, as well as all required low-level protocol details by means of a hierarchical finite state machine. Based on the ap-plication model, the probabilistic usage is specified in corresponding user behavior models by means of Markov chains. Our tool Markov4JMeter implements our approach to probabilistic workload generation by extend-ing the popular workload generation tool JMeter. A case study demon-strates how probabilistic workload for a sample Web application can be modeled and executed using Markov4JMeter.