Cited By
View all- Khalili FMariani LMohebbi APezzè MTerragni V(2024)Semantic matching in GUI test reuseEmpirical Software Engineering10.1007/s10664-023-10406-829:3Online publication date: 9-May-2024
The ineffectiveness of domain-specific word embedding models for GUI test reuse
Authors: 
Farideh Khalili, Ali Mohebbi, Valerio Terragni, 
Mauro Pezzè, 
Leonardo Mariani, 
Abbas HeydarnooriAuthors Info & Claims
Pages 560 - 564
Abstract
Reusing test cases across similar applications can significantly reduce testing effort. Some recent test reuse approaches successfully exploit word embedding models to semantically match GUI events across Android apps. It is a common understanding that word embedding models trained on domain-specific corpora perform better on specialized tasks. Our recent study confirms this understanding in the context of Android test reuse. It shows that word embedding models trained with a corpus of the English descriptions of apps in the Google Play Store lead to a better semantic matching of Android GUI events. Motivated by this result, we hypothesize that we can further increase the effectiveness of semantic matching by partitioning the corpus of app descriptions into domain-specific corpora. Our experiments do not confirm our hypothesis. This paper sheds light on this unexpected negative result that contradicts the common understanding.
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Index Terms
- The ineffectiveness of domain-specific word embedding models for GUI test reuse
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Published In
May 2022
698 pages
ISBN:9781450392983
DOI:10.1145/3524610
- Conference Chairs:
- Ayushi Rastogi,
- Rosalia Tufano,
- General Chair:
- Gabriele Bavota,
- Program Chairs:
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- Sonia Haiduc
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Published: 20 October 2022
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View all- Khalili FMariani LMohebbi APezzè MTerragni V(2024)Semantic matching in GUI test reuseEmpirical Software Engineering10.1007/s10664-023-10406-829:3Online publication date: 9-May-2024
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