To work efficiently with DSS, most users need assistance in representation conversion, i. e., translating the specific outcome from the DSS into the universal language of visual. In generally, it is much easier to und...To work efficiently with DSS, most users need assistance in representation conversion, i. e., translating the specific outcome from the DSS into the universal language of visual. In generally, it is much easier to understand the results from the DSS if they are translated into charts, maps, and other scientific displays, because visualization exploits human natural ability to recognize and understand visual pattern. In this paper we discuss the concept of visualization for DSS. AniGraftool, a software system, is introduced as an example of Visualized User Interface for DSS.展开更多
The user interface is a central component of any mo de rn application program. It determines how well end users accept, learn, and effi ciently work with the application program. The user interface is very difficult t...The user interface is a central component of any mo de rn application program. It determines how well end users accept, learn, and effi ciently work with the application program. The user interface is very difficult to design, to implement, to modify. It takes approximately 70% of the time requ ired for designing an application program. All the existing tools for user interface design can be divided into two basic c ategories-Interface Builders and Model-based Interface development tools, whic h trace their roots from user interface management systems. Interface Builders a re the most widespread and excellent to create layouts and manipulate widgets. H owever, Interface Builders have the follow demerits. An interface designed using Interface Builders can contain hundreds of procedures. Interface Builders give us no possibility to develop different pieces of the same interface separately. They do not help us in managing user tasks and can be used only by programmers. Model-based interface development tools have attracted a high degree of interes t in last few years. The basic premise of model based technology is that the interface development can be fully supported by declarative models of all user interface characteristics such as their presen tation, dialogue, domain of application etc, and then the user interface develop ment can be centered around such models. The high potential of this technology has not been realized yet. This fact has the following reasons. The known interface models are partial representations of interfaces. They cannot be readily modified by developers, and are not publicly available to the HCI community. The central ingredient for success in model-ba sed systems is a declarative, complete, versatile interface model that can expre ss a wide variety of interface designs. Therefore tool developers have to avoid the following disadvantages of current interface models: inflexibility, system- dependence, and incompleteness. The main idea to achieve these model character istics mention above is to use ontologies. This broadened interest in ontologies is based on the fact that they provide ma chine-understandable representation of semantics for information, and a shared and common understanding of a domain that can be communicated between people and across application systems. Support in data, information, and knowledge exchang e becomes the key issue in current computer technology. At the moment we are on the brink of the second Web generation called Semantic Web or Knowledgeable Web. Given the increasing amount of information available on-line, this kind of sup port is becoming more important day by day. The main idea of the proposed approach is to replace interface models by appropr iate ontologies. Some parts of these ontologies will be available from the Inter net; the other parts will be built by developers. As a result of the Semantic We b development we will have increasing the number of ontologies formally describe d in the Internet. The terminology and content of these ontologies will be inter nationally standardized. Reusing these ontologies will bring down the cost of de velopment and improve the quality of user interface. The parts of a user interface model are-a domain ontology model, a dialog ontol ogy model, presentation ontology model, "business- logic" variable ontology mod el and correspondences between these parts. Thus, the user interface development based on ontologies is an evolution of th e model-based approach, where appropriate ontologies are used instead of models .展开更多
移动互联网信息无障碍(mobile Internet information accessibility,MIIA)旨在确保移动应用内容对所有用户(包括视障人士等)都能平等、便捷、无障碍地获取和使用.系统综述移动互联网信息无障碍领域的最新研究进展,重点分析总结移动端GUI...移动互联网信息无障碍(mobile Internet information accessibility,MIIA)旨在确保移动应用内容对所有用户(包括视障人士等)都能平等、便捷、无障碍地获取和使用.系统综述移动互联网信息无障碍领域的最新研究进展,重点分析总结移动端GUI(graphical user interface)语义表征与理解、无障碍检测以及布局修复等方面的研究成果.分析表明,从传统启发式规则方法到深度学习驱动的自动化工具,相关技术逐渐提升了检测的精度和适应性,同时也揭示了在应对复杂动态交互和多样化用户需求方面的挑战,并对未来研究方向进行了展望.移动互联网信息无障碍技术已显著改善了视障用户的数字体验,但仍需不断创新与优化,以实现真正普惠与包容的数字社会.展开更多
移动应用是近10年来兴起的新型计算模式,深刻地影响人民的生活方式.移动应用主要以图形用户界面(graphical user interface,GUI)方式交互,而对其进行人工测试需要消耗大量人力和物力.为此,研究者提出针对移动应用GUI的测试自动生成技术...移动应用是近10年来兴起的新型计算模式,深刻地影响人民的生活方式.移动应用主要以图形用户界面(graphical user interface,GUI)方式交互,而对其进行人工测试需要消耗大量人力和物力.为此,研究者提出针对移动应用GUI的测试自动生成技术以提升测试效率并检测潜在缺陷.收集了145篇相关论文,系统地梳理、分析和总结现有工作.提出了“测试生成器-测试环境”研究框架,将该领域的研究按照所属模块进行分类.特别地,依据测试生成器所基于的方法,将现有方法大致分为基于随机、基于启发式搜索、基于模型、基于机器学习和基于测试迁移这5个类别.此外,还从缺陷类别和测试动作等其他分类维度梳理现有方法.收集了该领域中较有影响力的数据集和开源工具.最后,总结当前面临的挑战并展望未来的研究方向.展开更多
文摘To work efficiently with DSS, most users need assistance in representation conversion, i. e., translating the specific outcome from the DSS into the universal language of visual. In generally, it is much easier to understand the results from the DSS if they are translated into charts, maps, and other scientific displays, because visualization exploits human natural ability to recognize and understand visual pattern. In this paper we discuss the concept of visualization for DSS. AniGraftool, a software system, is introduced as an example of Visualized User Interface for DSS.
文摘The user interface is a central component of any mo de rn application program. It determines how well end users accept, learn, and effi ciently work with the application program. The user interface is very difficult to design, to implement, to modify. It takes approximately 70% of the time requ ired for designing an application program. All the existing tools for user interface design can be divided into two basic c ategories-Interface Builders and Model-based Interface development tools, whic h trace their roots from user interface management systems. Interface Builders a re the most widespread and excellent to create layouts and manipulate widgets. H owever, Interface Builders have the follow demerits. An interface designed using Interface Builders can contain hundreds of procedures. Interface Builders give us no possibility to develop different pieces of the same interface separately. They do not help us in managing user tasks and can be used only by programmers. Model-based interface development tools have attracted a high degree of interes t in last few years. The basic premise of model based technology is that the interface development can be fully supported by declarative models of all user interface characteristics such as their presen tation, dialogue, domain of application etc, and then the user interface develop ment can be centered around such models. The high potential of this technology has not been realized yet. This fact has the following reasons. The known interface models are partial representations of interfaces. They cannot be readily modified by developers, and are not publicly available to the HCI community. The central ingredient for success in model-ba sed systems is a declarative, complete, versatile interface model that can expre ss a wide variety of interface designs. Therefore tool developers have to avoid the following disadvantages of current interface models: inflexibility, system- dependence, and incompleteness. The main idea to achieve these model character istics mention above is to use ontologies. This broadened interest in ontologies is based on the fact that they provide ma chine-understandable representation of semantics for information, and a shared and common understanding of a domain that can be communicated between people and across application systems. Support in data, information, and knowledge exchang e becomes the key issue in current computer technology. At the moment we are on the brink of the second Web generation called Semantic Web or Knowledgeable Web. Given the increasing amount of information available on-line, this kind of sup port is becoming more important day by day. The main idea of the proposed approach is to replace interface models by appropr iate ontologies. Some parts of these ontologies will be available from the Inter net; the other parts will be built by developers. As a result of the Semantic We b development we will have increasing the number of ontologies formally describe d in the Internet. The terminology and content of these ontologies will be inter nationally standardized. Reusing these ontologies will bring down the cost of de velopment and improve the quality of user interface. The parts of a user interface model are-a domain ontology model, a dialog ontol ogy model, presentation ontology model, "business- logic" variable ontology mod el and correspondences between these parts. Thus, the user interface development based on ontologies is an evolution of th e model-based approach, where appropriate ontologies are used instead of models .
文摘移动互联网信息无障碍(mobile Internet information accessibility,MIIA)旨在确保移动应用内容对所有用户(包括视障人士等)都能平等、便捷、无障碍地获取和使用.系统综述移动互联网信息无障碍领域的最新研究进展,重点分析总结移动端GUI(graphical user interface)语义表征与理解、无障碍检测以及布局修复等方面的研究成果.分析表明,从传统启发式规则方法到深度学习驱动的自动化工具,相关技术逐渐提升了检测的精度和适应性,同时也揭示了在应对复杂动态交互和多样化用户需求方面的挑战,并对未来研究方向进行了展望.移动互联网信息无障碍技术已显著改善了视障用户的数字体验,但仍需不断创新与优化,以实现真正普惠与包容的数字社会.
文摘移动应用是近10年来兴起的新型计算模式,深刻地影响人民的生活方式.移动应用主要以图形用户界面(graphical user interface,GUI)方式交互,而对其进行人工测试需要消耗大量人力和物力.为此,研究者提出针对移动应用GUI的测试自动生成技术以提升测试效率并检测潜在缺陷.收集了145篇相关论文,系统地梳理、分析和总结现有工作.提出了“测试生成器-测试环境”研究框架,将该领域的研究按照所属模块进行分类.特别地,依据测试生成器所基于的方法,将现有方法大致分为基于随机、基于启发式搜索、基于模型、基于机器学习和基于测试迁移这5个类别.此外,还从缺陷类别和测试动作等其他分类维度梳理现有方法.收集了该领域中较有影响力的数据集和开源工具.最后,总结当前面临的挑战并展望未来的研究方向.
