Pairwise Test Generation Based on Parallel Genetic Algorithm with Spark

DOI

10.2991/cisia-15.2015.18How to use a DOI?

Keywords

combinatorial testing; pairwise testing; parallel genetic algorithmp; spark; test generation

Abstract

Pairwise testing is an effective combinatorial test generation technique that can generate tests covering all pairs of parameter values. Genetic algorithm has been used for pairwise test generation by researchers. It can often produce smaller test suite, but typically require a longer computation. To solve this problem, in this paper we use spark, an in-memory and iterative computing framework, to parallelize genetic algorithm for pairwise test generation. We propose fitness evaluation parallelization, which evaluates each individual’s fitness value on spark’s workers. A preliminary evaluation of the proposal algorithm is conducted to verify the effectiveness compared with those of other algorithms published in the literature. Experiments show that the proposed algorithm can generate better results among these algorithms.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - R.Z Qi
AU  - Z.J Wang
AU  - S.Y Li
PY  - 2015/06
DA  - 2015/06
TI  - Pairwise Test Generation Based on Parallel Genetic Algorithm with Spark
BT  - Proceedings of the International Conference on Computer Information Systems and Industrial Applications
PB  - Atlantis Press
SP  - 67
EP  - 70
SN  - 2352-538X
UR  - https://doi.org/10.2991/cisia-15.2015.18
DO  - 10.2991/cisia-15.2015.18
ID  - Qi2015/06
ER  -