Recent Progress in Automated Code Generation from GUI Images Using Machine Learning Techniques

被引：2

作者：

Baule, Daniel de Souza ^{[1
]}

von Wangenheim, Christiane Gresse ^{[1
]}

von Wangenheim, Aldo ^{[1
]}

Hauck, Jean C. R. ^{[1
]}

机构：

[1] Univ Fed Santa Catarina, Florianopolis, SC, Brazil

来源：

JOURNAL OF UNIVERSAL COMPUTER SCIENCE | 2020年 / 26卷 / 09期

关键词：

user interface design; machine learning; systematic mapping;

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

The manual transformation of a user interface design into code is a costly and time-consuming process. A solution can be the automation of the generation of code based on sketches or GUI design images. Recently, Machine Learning approaches have shown promising results in detecting GUI elements for such automation. Thus, to provide an overview of existing approaches, we performed a systematic mapping study. As a result, we identified and compared 20 approaches, that demonstrate good performance results being considered useful. These results can be used by researchers and practitioners in order to improve the efficiency of the GUI design process as well as continue to evolve and improve approaches for its support.

引用

下载

页码：1095 / 1127

页数：33

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