Mobile Test Script Generation from Natural Language Descriptions

Abstract

Mobile applications are increasingly integral to our daily lives. Currently, the correctness of GUI functions of mobile application is mainly ensured by executing manually written test scripts. However, manually writing these test scripts is not only time-consuming but also costly. Moreover, test scripts are highly vulnerable to application modifications and prone to corruption. In this paper, we propose a novel approach for writing test scripts that enables testers to directly express test intents in natural language within the script. Additionally, we present a new test script generation tool that transforms these test intents into their corresponding test events. Our proposed tool, named GenDroid, employs pre-trained models in conjunction with random forest to facilitate the conversion of test intents into the respective test scripts. To further alleviate the workload of testers and enable them to focus on composing critical test intents, we leverage the application’s UI transfer graph to facilitate the automated generation of other test events, such as jump actions, throughout the generation process. Our results indicate an intent coverage of 88.1%, a notable 20.68% improvement compared to the similar-purpose tool, seq2act.