Fumihiko Kitayama

Design of a framework for dynamic content adaptation to Web-enabled terminals and enterprise applications

The paper describes the design of a framework for enterprise Web applications that adapts their contents to various types of Web-enabled terminals, such as wearable devices, PDAs, and automobile PCs. Such terminals have different capabilities as regards their processing units, user interaction, and communication. Thus, applications must dynamically adapt their contents to each type of device when they provide service sessions. On the other hand, applications that serve various dynamic contents from databases and transactions need to be connected to back-end systems, namely, business objects designed independently of the Web applications. For reuse and easy development of such adaptive and enterprise systems, the framework should separate three concerns: (1) design of business objects, (2) design of logical Web contents, and (3) design of the content adaptation. The paper reports the authors experience in designing, implementing, and applying a framework to a banking system using small display devices, and discusses the design.

An authoring technology for multidevice Web applications

The rapid proliferation of mobile computing devices has increased the complexity and cost of cross-platform application development. Multidevice authoring technology (MDAT) lets developers build a generic application common to multiple devices and customize it for specific devices. We developed MDAT an end-to-end development methodology and toolset, to reduce the complexity of creating interactive, form-based Web applications that execute on heterogeneous devices. Web application refers to conventional, servlet-based Web applications as well as portlet applications. A portlet is a Web application component that a Web portal server aggregates with other portlets.

JSP splitting for improving execution performance

Splitting a JSP (JavaServer Pages) page into fragments can improve the execution performance of JSP pages when the Web application server can separately cache the Web page fragments obtained by executing the JSP fragments. If a JSP page is split into fragments according to the update frequency of each portion of the Web page obtained by executing the JSP page, all of the split JSP fragments do not need to be executed again when only a single cached part of a Web page expires. In addition, the fragments of a JSP page can be reused by other JSP pages. In both cases, the execution results of all of the JSP fragments split from the JSP page must be the same as from the JSP page before it was split. In this paper, we propose JSP splitting, which is a method of splitting a JSP page into fragments maintaining the data and control dependences existing in the original JSP page. JSP splitting automatically detects the portions needed to maintain the data and control dependences of a JSP page for the portions that developers want to split from the JSP page. We implemented JSP splitting with a GUI tool, and confirmed that the split JSP fragments were executed in the same as the way as the JSP page before the split. Experimental results show that the response time to access a Web page can be reduced by splitting a JSP page into fragments and setting different caching periods for the Web page fragments obtained by executing the JSP fragments.

Trace Mining from Distributed Assembly Databases for Causal Analysis

Hierarchical structures of components often appear in industry, such as the components of cars. We focus on association mining from the hierarchically assembled data items that are characterized with identity labels such as lot numbers. Massive and physically distributed product databases make it difficult to directly find the associations of deep-level items. We propose a top-down algorithm using virtual lot numbers to mine association rules from the hierarchical databases. Virtual lot numbers delegate the identity information of the subcomponents to upper-level lot numbers without modifications to the databases. Our pruning method reduces the number of enumerated items and avoids redundant access to the databases. Experiments show that the algorithm works an order of magnitude faster than a naive approach.