Semantic Similarity-Based Mobile Application Isomorphic Graphical User Interface Identification
نویسندگان
چکیده
Applying robots to mobile application testing is an emerging approach automated black-box testing. The key supporting robot the efficient modeling of GUI elements. Since under often contains a large number similar GUIs, model obtained many redundant nodes. This causes state space explosion models which has serious effect on efficiency Hence, how accurately identify isomorphic GUIs and construct quasi-concise are challenges faced today. We thus propose semantic similarity-based identifying for applications. Using this approach, information elements first identified by deep learning network models, then, structure feature vector extracted finally merged generate embedding with information. Finally, cosine similarity. Then, three experiments conducted verify generalizability effectiveness method. demonstrate that proposed method can shows high compatibility in terms cross-platform cross-device
منابع مشابه
User Interface Design in Mobile Educational Applications
Introduction: User interfaces are a crucial factor in ensuring the success of mobile applications. Mobile Educational Applications not only provide flexibility in learning, but also allow learners to learn at any time and any place. The purpose of this article is to investigate the effective factors affecting the design of the user interface in mobile educational applications. Methods: Quantita...
متن کاملGraphical User Interface Testing
Software testing is one of the major challenges in the software community today. Graphical user interface (GUI) testing is inherently more difficult than traditional, command line interface testing. This paper briefly describes why this is so, and gives an overview of the state of the art in GUI testing. The main focus of the paper is a presentation of the features of a new GUI testing tool, ca...
متن کاملNeuroSVM: A Graphical User Interface for Identification of Liver Patients
Diagnosis of liver infection at preliminary stage is important for better treatment. In today’s scenario devices like sensors are used for detection of infections. Accurate classification techniques are required for automatic identification of disease samples. In this context, this study utilizes data mining approaches for classification of liver patients from healthy individuals. Four algorith...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Mathematics
سال: 2023
ISSN: ['2227-7390']
DOI: https://doi.org/10.3390/math11030527