Guided, stochastic model-based GUI testing of Android apps

By Ting Su, Guozhu Meng, Yuting Chen, Ke Wu, Weiming Yang, Yao Yao, G. Pu, Yang Liu, Zhendong Su. ESEC/SIGSOFT FSE, 2017

391 citations recorded by the source corpus.

Subfields: Software, Signal Processing

View Paper: https://www.semanticscholar.org/paper/cfb1f25a91eee93ecfcc2693c7b4e096fa10f3ac

Citations in the corpus

• Superion: Grammar-Aware Greybox Fuzzing (2018, neutral): “, compiler fuzzing [17, 19, 38, 39, 43, 60], kernel fuzzing [18, 32, 57], IoT (Internet of Things) fuzzing [15], OS fuzzing [48], smart contract fuzzing [36], GUI testing [59], and deep learning system testing [44].”
• Software Testing With Large Language Models: Survey, Landscape, and Vision (2023, neutral): “Similarly, when it comes to mobile GUI testing, existing studies with random-/rule-based methods [9], [10], model-based methods [11], [12], and learning-based methods [13] are unable to understand the semantic information of the GUI page and often fall short in achieving comprehensive coverage…”