Finding Test Data with Specific Properties via Metaheuristic Search
by R. Feldt and S. Poulding
For software testing to be effective the test data should cover a large and diverse range of the possible input domain. Boltzmann samplers were recently introduced as a systematic method to randomly generate data with a range of sizes from combinatorial classes, and there are a number of automated testing frameworks that serve a similar purpose. However, size is only one of many possible properties that data generated for software testing should exhibit. For the testing of realistic software systems we also need to trade off between multiple different properties or search for specific instances of data that combine several properties. In this paper we propose a general search-based framework for finding test data with specific properties. In particular, we use a metaheuristic, differential evolution, to search for stochastic models for the data generator. Evaluation of the framework demonstrates that it is more general and flexible than existing solutions based on random sampling.
This paper won the Best research paper award at ISSRE 2013.


  author =    "Robert Feldt and Simon Poulding",
  title =     "Finding Test Data with Specific Properties via Metaheuristic Search",
  booktitle = "Proceedings of the International Symposium on Software Reliability Engineering (ISSRE)",
  year =      "2013",
  pages =     "350--359",
  publisher = "IEEE",
  keywords =  "Search-based software testing, Automated testing",