Synthesizing client load models for performance engineering via web crawling

  • Authors:

  • Yuhong Cai;John Grundy;John Hosking

  • Affiliations:

  • University of Auckland, Auckland, New Zealand;University of Auckland, Auckland, New Zealand;University of Auckland, Auckland, New Zealand

  • Venue:
  • Proceedings of the twenty-second IEEE/ACM international conference on Automated software engineering
  • Year:
  • 2007

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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 3rd 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 3rd 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 3rd party tool load tests