AuthorsM. Zhang, T. Yue, S. Ali, H. Zhang and J. Wu
EditorsD. Amyot, P. F. i. Casas and G. Mussbacher
TitleA Systematic Approach to Automatically Derive Test Cases From Use Cases Specified in Restricted Natural Languages
AfilliationSoftware Engineering, Software Engineering, Software Engineering
Project(s)The Certus Centre (SFI)
StatusPublished
Publication TypeProceedings, refereed
Year of Publication2014
Conference Name8th System Analysis and Modelling Conference (SAM'14)
PublisherSpringer
Place PublishedSwitzerland
KeywordsConference
Abstract

In many domains, such as avionics, oil and gas, and maritime, a common practice is to derive and execute test cases manually from requirements, where both requirements and test cases are specified in NL by domain experts. The manual execution of test cases is largely dependent on the domain experts who wrote the test cases. The process of manual writing of requirements and test cases introduce ambiguity in their description and in addition test cases may not be effective since they may not be derived by systematic applying coverage criteria. In this paper, we report a systematic approach to support automatic derivation of manually executable test cases from use cases. Both use cases and test cases are specified in restricted NLs along with carefully defined templates implemented in a tool. We evaluate our approach with four case studies (in total having 30 use cases and 579 steps of flow of events), two of which are industrial case studies from the oil and gas and avionics domains. Results show that our tool was able to correctly process all the case studies and systematically (by following the carefully defined structure coverage criterion) generate 30 TCSs and 389 test cases. Moreover our approach allows defining different test coverage criteria on requirements other than the one already implemented in our tool.

Citation KeySimula.simula.2822