计算机科学 ›› 2017, Vol. 44 ›› Issue (11): 98-103.doi: 10.11896/j.issn.1002-137X.2017.11.015

• 2016 年全国软件与应用学术会议 • 上一篇    下一篇

一种基于文档的移动平台间UI控件对应方法

徐同同,刘曲涛,郑晓梅,潘敏学,张天   

  1. 南京大学计算机软件新技术国家重点实验室 南京210023,南京大学计算机软件新技术国家重点实验室 南京210023,南京中医药大学信息技术学院 南京210023,南京大学计算机软件新技术国家重点实验室 南京210023,南京大学计算机软件新技术国家重点实验室 南京210023
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受基于MDE的异构数据建模及转换研究(61472180),基于场景规约的中断驱动系统的建模与验证技术研究(61502228),基于SysML和MARTE的异构数据模型转换方法研究(BK20141322),中断驱动系统的建模与分析(BK20150589)资助

Document Based Matching Method for Mobile UI Components

XU Tong-tong, LIU Qu-tao, ZHENG Xiao-mei, PAN Min-xue and ZHANG Tian   

  • Online:2018-12-01 Published:2018-12-01

摘要: 多平台开发是移动应用软件开发的一个重要特点,同时还具有版本演化快和开发周期短的要求,这给移动开发带来了巨大的挑战。由于目前主流的移动平台大多采用MVC架构模式,并且在开发上体现出了UI驱动和事件驱动的特点,因此不同平台(如iOS和Android等)之间的UI控件具有较强的对应性,这给移动应用的开发人员在多平台开发时提供了重要的参考。提出了一种基于文档来理解不同平台之间UI控件对应性的方法,该方法以iOS和Android两种移动平台为研究对象,通过自然语言处理技术来分析从官方文档中抓取的UI控件描述文字,基于空间向量模型计算控件之间的相似度,并针对移动应用的特点设计了同义词集来保证匹配的准确性。基于所提方法,对iOS和Android平台上的典型UI控件进行了具体实验,结果表明,在单控件对应性方面,该方法能找到大部分的控件对应性,具有较高的准确度。

关键词: 自然语言处理,移动开发,UI控件

Abstract: Development for multi-platform is an important requirement of developing mobile applications.At the same time,the developments should be flexible for short cycle and rapid evolution.These are challenges for mobile developments.Fortunately,most mobile platforms are designed as MVC-based and event/UI-driven.Hence the UI components are similar between different platforms,which is very helpful when developing Apps from one platform to another.This paper provided a document based matching method for uncovering the similarities of UI components between different platforms.The iOS and Android are selected,and the documentations for their UI components are extracted from the official websites.Then the NLP techniques are used to build the vector space model so as to compute the similarities of UI components between two platforms.To increase the accuracy,the sets of synonymous words were presented according to the UI features of components.The experiments were performed on a set of typical iOS and Android UI components.The results illustrate that the accuracy of the method is acceptable for the most UI components especially for those of one-one-matching.

Key words: NLP,Mobile development,UI components

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