Yoshitaka Atarashi

An approach to evaluate time-dependent changes in feature constraints

Feature selections mining is the process of discovering potentially feature associations and constraints in data. Especially, mining from time-series data obtains feature constraint trends. In this paper, we describe an approach to evaluate feature constraint trends and present results of two case studies. Feature selections mining was applied to a product transactions database at Hitachi. The product transactions had 148 optional features, and 8,372 products were derived from the product line. Both case studies focus on transaction-time periods: time series and time intervals. Feature selections mining discovered feature constraints around 100 rules in each study, and determined they constantly change.

HMI Development of Derived Products by Model-Driven Prototyping Tool for In-Vehicle System

The number of man-months of HMI (human machine interface) development for embedded systems is increasing because of internationalization. Even though functions of embedded systems such as in-vehicle systems are largely the same for each country, the HMI design has to be customized to specific languages and requirements. For instance, adjusting the width and font of text improves its visibility. However, this creates a new issue regarding HMI design management. We report here on HMI development of derived products, which are assumed to be developed with common functions and customized HMI, by using a model-driven prototyping tool for in-vehicle systems. The prototyping tool we developed is based on open source software including an image editor, Eclipse plug-in, relational database, servlet, and Web browser. In addition, XML for the prototyping tool is defined in order to represent derived product support features. In experiments, this prototyping tool enabled HMI designers of an in-vehicle system to check the HMI design more quickly and easily than in a traditional HMI development process.