Novel fuzzy approach for ranking test vectors

Autor:	Gergely Takacs
Rok vydání:	2012
Předmět:	Model-based testing Fuzzy classification business.industry Fuzzy set Software development Classification Tree Method computer.software_genre Machine learning Ranking Fuzzy set operations Data mining Test Management Approach Artificial intelligence business computer Mathematics
Zdroj:	SACI
DOI:	10.1109/saci.2012.6250036
Popis:	Software testing is essential part of the software development especially when the software has safety critical classification. In this paper authors introduce a method for select the right values and ranges for unit and functional testing. The key feature of this novel approach is that, test vectors can be ranked before selection in order to gain test time or quality. Fuzzy set theory is used for the ranking of the test sets. The introduced method presented on a example code, which helps the understanding of its basic principals. The authors take notes on the implementation of the test vector generation. Directions of further research are also discussed.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::9eb85e29cb282290da2f9f1835aa4690 https://doi.org/10.1109/saci.2012.6250036 Zobrazit plný text záznamu