TY - GEN
T1 - Test transfer across mobile apps through semantic mapping
AU - Lin, Jun Wei
AU - Jabbarvand, Reyhaneh
AU - Malek, Sam
N1 - Funding Information:
This work was supported in part by awards CCF-1618132 and CNS-1823262 from the National Science Foundation.
Publisher Copyright:
© 2019 IEEE.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2019/11
Y1 - 2019/11
N2 - GUI-based testing has been primarily used to examine the functionality and usability of mobile apps. Despite the numerous GUI-based test input generation techniques proposed in the literature, these techniques are still limited by (1) lack of context-aware text inputs; (2) failing to generate expressive tests; and (3) absence of test oracles. To address these limitations, we propose CraftDroid, a framework that leverages information retrieval, along with static and dynamic analysis techniques, to extract the human knowledge from an existing test suite for one app and transfer the test cases and oracles to be used for testing other apps with the similar functionalities. Evaluation of CraftDroid on real-world commercial Android apps corroborates its effectiveness by achieving 73% precision and 90% recall on average for transferring both the GUI events and oracles. In addition, 75% of the attempted transfers successfully generated valid and feature-based tests for popular features among apps in the same category.
AB - GUI-based testing has been primarily used to examine the functionality and usability of mobile apps. Despite the numerous GUI-based test input generation techniques proposed in the literature, these techniques are still limited by (1) lack of context-aware text inputs; (2) failing to generate expressive tests; and (3) absence of test oracles. To address these limitations, we propose CraftDroid, a framework that leverages information retrieval, along with static and dynamic analysis techniques, to extract the human knowledge from an existing test suite for one app and transfer the test cases and oracles to be used for testing other apps with the similar functionalities. Evaluation of CraftDroid on real-world commercial Android apps corroborates its effectiveness by achieving 73% precision and 90% recall on average for transferring both the GUI events and oracles. In addition, 75% of the attempted transfers successfully generated valid and feature-based tests for popular features among apps in the same category.
KW - GUI testing
KW - Natural language processing
KW - Semantic similarity
KW - Test migration
KW - Test transfer
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U2 - 10.1109/ASE.2019.00015
DO - 10.1109/ASE.2019.00015
M3 - Conference contribution
AN - SCOPUS:85078894089
T3 - Proceedings - 2019 34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019
SP - 42
EP - 53
BT - Proceedings - 2019 34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 34th IEEE/ACM International Conference on Automated Software Engineering, ASE 2019
Y2 - 10 November 2019 through 15 November 2019
ER -