Automated API Testing: A Model-Based Approach

[presentation]
by
Kirk Sayre, The University of Tennessee
Summary: 

API testing is difficult, even with automated support. However, with traditional automated testing solutions, the cost to create and maintain a test suite can be more than the savings realized from automated test execution. By creating a model of the API to test and generating the test scripts automatically from the model, test automation becomes more cost-effective. Kirk Sayre describes how to create models of APIs; how to take the expected use of the API under test into account with Markov chains; how to augment the models with the information needed to generate automated test scripts; and how to use and interpret test results. You'll see concrete examples of automated model-based testing of APIs written in Java, PHP, and C.

  • Create a model of an API for use in model-based testing
  • The basics of testing using Markov chain usage models
  • Analysis of white-box and black-box test results from model-based testing

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