Name
Abstract | ||
|---|---|---|
Search-based testing can be applied to automatically generate unit tests that achieve high levels of code coverage on object-oriented classes. However, test generation takes time, in particular if projects consist of many classes, like in the case of the Guava library. To allow search-based test generation to scale up and to integrate it better into software development, continuous test generation applies test generation incrementally during continuous integration. In this paper, we report on the application of continuous test generation with EvoSuite at the SSBSE’15 challenge on the Guava library. Our results show that continuous test generation reduces the time spent on automated test generation by 96 %, while increasing code coverage by 13.9 % on average. |
Year | Venue | Field |
|---|---|---|
2015 | SSBSE | Code coverage,SCALE-UP,Computer science,Simulation,Unit testing,Search based testing,Artificial intelligence,Test compression,Continuous integration,Computer engineering,Software development,Machine learning |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| José Creissac Campos | 1 | 473 | 42.36 |
| Gordon Fraser | 2 | 2625 | 116.22 |
| Andrea Arcuri | 3 | 2630 | 92.48 |
| Rui Abreu | 4 | 3 | 1.39 |