@inproceedings{3ba623af440b4ce6b257ba732ea2b789,
title = "Metamorphic Testing for Adobe Data Analytics Software",
abstract = "It is challenging to test data analytics software because a test oracle might not be available. This study reports our experience of applying metamorphic testing to Adobe's data analytics software that is used for anomaly detection in a set of time series data. We make use of geometric transformations to build metamorphic relations and generate simple time series data as the source test cases. The results of this study show that metamorphic testing is highly effective for both verification and validation purposes. An investigation of the issues detected during metamorphic testing revealed three bugs in the software under test.",
keywords = "anomaly detection, geometric transformation, metamorphic relation, metamorphic testing, Time series analysis, verification and validation",
author = "Jarman, \{Darryl C.\} and Zhou, \{Zhi Quan\} and Chen, \{Tsong Yueh\}",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2nd IEEE/ACM International Workshop on Metamorphic Testing, MET 2017 ; Conference date: 22-05-2017",
year = "2017",
month = jun,
day = "28",
doi = "10.1109/MET.2017.1",
language = "English",
series = "Proceedings - 2017 IEEE/ACM 2nd International Workshop on Metamorphic Testing, MET 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "21--27",
booktitle = "Proceedings - 2017 IEEE/ACM 2nd International Workshop on Metamorphic Testing, MET 2017",
address = "United States",
}