TY - GEN
T1 - A systematic approach to automatically derive test cases from use cases specified in restricted natural languages
AU - Zhang, Man
AU - Yue, Tao
AU - Ali, Shaukat
AU - Zhang, Huihui
AU - Wu, Ji
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2014.
PY - 2014
Y1 - 2014
N2 - 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 natural language (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 introduces ambiguity in their description and, in addition, test cases may not be effective since they may not be derived by systematically applying coverage criteria. In this paper, we report on 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 from flows of events), two of which are industrial case studies from the oil/gas and avionics domains. Results show that our tool was able to correctly process all the case studies and systematically (by following carefully-defined structure coverage criteria) 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.
AB - 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 natural language (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 introduces ambiguity in their description and, in addition, test cases may not be effective since they may not be derived by systematically applying coverage criteria. In this paper, we report on 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 from flows of events), two of which are industrial case studies from the oil/gas and avionics domains. Results show that our tool was able to correctly process all the case studies and systematically (by following carefully-defined structure coverage criteria) 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.
KW - Natural language
KW - Restricted test case specification
KW - Restricted use case modeling
KW - Test case specification
KW - Test cases
KW - Test generation
KW - Transformation and automation
KW - Use cases
UR - https://www.scopus.com/pages/publications/84949131542
U2 - 10.1007/978-3-319-11743-0_10
DO - 10.1007/978-3-319-11743-0_10
M3 - 会议稿件
AN - SCOPUS:84949131542
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 142
EP - 157
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
A2 - Amyot, Daniel
A2 - i Casas, Pau Fonseca
A2 - Mussbacher, Gunter
PB - Springer Verlag
T2 - 8th International Conference on System Analysis and Modeling: Models and Reusability, SAM 2014
Y2 - 29 September 2014 through 30 September 2014
ER -