Abstract
Generating tests for software is an important, but difficult, task. Search-based test generation is promising, as it reduces the time required from human experts, but suffers from many problems and limitations. Namely, the inability to fully incorporate a tester's domain knowledge into the search, its difficulty in creating very complex objects, and the problems associated with variable length tests. This paper illustrates how Grammatical Evolution could address and provide a possible solution to each of these concerns.
| Original language | Undefined/Unknown |
|---|---|
| Title of host publication | Gecco 2022 Companion Proceedings of the 2022 Genetic and Evolutionary Computation Conference |
| Pages | 1946-1947 |
| Number of pages | 2 |
| ISBN (Electronic) | 9781450392686 |
| DOIs | |
| Publication status | Published - 9 Jul 2022 |
Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver