Sapienz: multi-objective automated testing for Android applications

By Ke Mao, Mark Harman, Yue Jia. International Symposium on Software Testing and Analysis, 2016

584 citations recorded by the source corpus.

Subfields: Information Systems, Software

View Paper: https://www.semanticscholar.org/paper/6fa1c7156498ebfdfd5abb58e2f9858eb2ca28a8

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

1. Yue Jia
2. Yuanyuan Zhang
3. Mark Harman
4. Federica Sarro
5. William J. Martin
6. Yang Liu
7. Zhendong Su
8. Yuting Chen

In Software

1. Yue Jia
2. Mark Harman
3. Ting Su
4. Yuanyuan Zhang
5. Yang Liu
6. Zhendong Su
7. Yuting Chen
8. Sheng Wen

Citations in the corpus

• Fuzzing: A Survey for Roadmap (2022, background): “Since the execution speed is one of the keys for the success of fuzzing, the automation of GUI applications often replaces the GUI with a faster approach and executes targets in the command-line manner [91, 106, 121].”
• Guided, stochastic model-based GUI testing of Android apps (2017, methodology): “We compare Stoat with these GUI testing tools: (1) Monkey (random fuzzing), (2) A3E [3] (systematic UI exploration), and (3) Sapienz (genetic algorithm) [13].”
• A Survey of App Store Analysis for Software Engineering (2017, methodology): “[151] introduced Sapienz, anAndroid testing tool that the authors applied to the top 1,000Google Play apps, revealing 558 previously undetected crashing test causes.”