Algorithm or Representation?: An empirical study on how SAPIENZ achieves coverage

DIEGO GARBERVETSKY; IVAN ARSCUSCHIN MORENO; JUAN PABLO GALEOTTI

Madrid

Conferencia; 1st International Conference on Automation of Software Test,; 2020

IEEE/ACM

Testing is a very important and expensive part of developing Android applications. Several tools for automatically testing Android applications have been proposed. In particular, Sapienz is a search-based tool that has been recently deployed in an industrial setting. Although it has been shown that Sapienz outperforms several state-of-the-art tools, it is still to be seen what features of Sapienz impact the most on its effectiveness.We conducted an extensive empirical study where we compare the impact of the search algorithm and the usage of motif genes, a more compact representation of individuals. Our empirical study shows that the usage of motif genes improves statement coverage both for evolutionary algorithms and random approaches. In particular, our study shows that although the evolutionary algorithm used by Sapienz (i.e., NSGA-II) outperforms other search algorithms, it is not statistically distinguishable from Random Search. These facts cast doubts about the use of evolutionary algorithms in the context of Android test generation and suggest that motif genes have a great impact on the overall effectiveness.