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Metamorphic Testing for Adobe Analytics Data Collection JavaScript Library

Conference Paper


Abstract


  • © 2018 Association for Computing Machinery. In recent years, metamorphic testing has been successfully and systematically adopted within Adobe Systems to improve the cost effectiveness of its software process. In this industry experience report, we present a case where metamorphic testing has been applied to the Data Collection JavaScript Library of Adobe Analytics. This type of software is difficult to test using traditional approaches. The application of metamorphic testing alleviated the oracle problem, and detected real-life bugs in the system under test as well as compatibility problems between the system and its environment, namely, the Internet Explorer browser. Our results further justify the adoption of metamorphic testing as a simple yet effective approach in industrial settings.

Authors


  •   Wang, Zhenyu (external author)
  •   Towey, Dave (external author)
  •   Zhi Quan (George) Zhou
  •   Chen, Tsong Yueh (external author)

Publication Date


  • 2018

Citation


  • Wang, Z., Towey, D., Zhou, Z. & Chen, T. (2018). Metamorphic Testing for Adobe Analytics Data Collection JavaScript Library. 2018 ACM/IEEE International Conference on Software Engineering (pp. 34-37). Association for Computing Machinery (ACM).

Scopus Eid


  • 2-s2.0-85051244511

Start Page


  • 34

End Page


  • 37

Abstract


  • © 2018 Association for Computing Machinery. In recent years, metamorphic testing has been successfully and systematically adopted within Adobe Systems to improve the cost effectiveness of its software process. In this industry experience report, we present a case where metamorphic testing has been applied to the Data Collection JavaScript Library of Adobe Analytics. This type of software is difficult to test using traditional approaches. The application of metamorphic testing alleviated the oracle problem, and detected real-life bugs in the system under test as well as compatibility problems between the system and its environment, namely, the Internet Explorer browser. Our results further justify the adoption of metamorphic testing as a simple yet effective approach in industrial settings.

Authors


  •   Wang, Zhenyu (external author)
  •   Towey, Dave (external author)
  •   Zhi Quan (George) Zhou
  •   Chen, Tsong Yueh (external author)

Publication Date


  • 2018

Citation


  • Wang, Z., Towey, D., Zhou, Z. & Chen, T. (2018). Metamorphic Testing for Adobe Analytics Data Collection JavaScript Library. 2018 ACM/IEEE International Conference on Software Engineering (pp. 34-37). Association for Computing Machinery (ACM).

Scopus Eid


  • 2-s2.0-85051244511

Start Page


  • 34

End Page


  • 37