Abstract
Conventional unit tests are still mainly handcrafted. Generalizing conventional unit tests to parameterized unit tests supports automatic test data generation. Methods that were introduced to instantiate parameterized unit tests with concrete values as test data are based on search based approaches, dynamic symbolic execution, or property based testing. In this work, we introduce an approach that retrofits existing conventional unit tests into parameterized unit tests by generalization, and generate test data by combinatorial valuation to adapt existing conventional unit test suites. We conduct an empirical study to investigate whether our test suite adaption approach is beneficial in terms of additional fault detection capabilities and code coverage. Our results show that mutation score and condition coverage increase with feasible effort compared to existing conventional unit tests.
Original language | English |
---|---|
Title of host publication | Proceedings - 2018 IEEE 11th International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2018 |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 352-355 |
Number of pages | 4 |
ISBN (Electronic) | 9781538663523 |
DOIs | |
Publication status | Published - 16 Jul 2018 |
Event | 11th IEEE International Conference on Software Testing, Verification and Validation Workshops: ICSTW 2018 - Vasteras, Sweden Duration: 9 Apr 2018 → 13 Apr 2018 |
Conference
Conference | 11th IEEE International Conference on Software Testing, Verification and Validation Workshops |
---|---|
Country/Territory | Sweden |
City | Vasteras |
Period | 9/04/18 → 13/04/18 |
Keywords
- Code coverage
- Combinatorial testing
- Mutation score
- Parameterized unit test
ASJC Scopus subject areas
- Software
- Safety, Risk, Reliability and Quality