Abstract

Abstract

Accurate web application performance testing relies on the use of loading tests based on a realistic client behaviour load model. Unfortunately developing such load models and associated test plans and scripts is tedious and error-prone with most existing web performance testing tools providing limited client load modelling capabilities. We describe a new approach and toolset that we have developed, MaramaMTE+, which improves the ability to model realistic web client load behaviour, automatically generates complex web application testing plans and scripts, and integrates load behaviour modelling with a generic performance engineering tool. MaramaMTE+ uses a stochastic form chart as its client loading model. A 3 rd party web crawler application extracts structural information from a target web site, aggregating the collected data into a crawler database that is then used for form chart model generation. The performance engineer then augments this synthesized form chart with client loading probabilities. Realistic web loading tests for a 3 rd party web load testing tool are then automatically generated from this resultant stochastic form chart client load model. We describe the development of our MaramaMTE+ environment, example usage of the tool, and compare and contrast the results obtained from our generated performance load tests against hand-built 3 rd party tool load tests.

Assessing the likely run-time performance of applications using thin-client architectures during their design is very difficult. We describe SoftArch/Thin, a thinclient test-bed generator that synthesises performance testbed thin-client and server code from high-level software architecture models. This generated code is performance tested using a third-party tool and the results summarised. Architecture models can be evolved and tests repeated during application development to inform software engineers of realistic performance characteristics of their designs. Our environment currently supports J2EE and ASP.NET-based thin-client code generation and performance testing.