Finding test data with specific properties via metaheuristic search
Paper i proceeding, 2013

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.

Författare

Robert Feldt

Chalmers, Data- och informationsteknik, Software Engineering

S. Poulding

University of York

2013 IEEE 24th International Symposium on Software Reliability Engineering, ISSRE 2013

350-359

Ämneskategorier

Programvaruteknik

DOI

10.1109/ISSRE.2013.6698888

ISBN

978-147992366-3

Mer information

Senast uppdaterat

2018-03-06