Bup-Ki Min

A UML metamodel for smart device application modeling based on Windows Phone 7 platform

Smart devices (Smartphone, Tablet PC, etc.) are becoming issues in the mobile market, and new platforms for the smart devices are emerging such as iOS and Android. Microsoft announced Windows Phone 7, a specialized platform supporting the function of the Smartphone to compete with other Smartphone platforms. Although Windows Phone 7 now supports only the Smartphone it is expected to support a variety of smart devices to compete with iOS and Android in the near future. Currently, it is difficult to develop applications for various smart devices upon a single platform because each smart device has its own hardware and user interface. To cope with this problem, a platform as well as a modeling environment must be extended to support various devices. In this paper, we move our focus to the extension of the modeling environment. To be more specifically we suggest the extended metamodel for modeling applications based on Windows Phone 7 using the UML extension mechanism. To do this, we analyze Windows Phone 7s features and classify them with respect to software elements and hardware resources. Therefore, software and hardware can be modeled independently and furthermore even if a new smart device based on Windows Phone 7 is introduced the modeling elements for the applications operated on the new device can be extended easily.

Extending UML Meta-model for Android Application

UML is a standardized general-purpose software modeling language. Using the UML, a developer can model any systems easily because the UML provides well-defined modeling concepts and notations to describe elements of a system. The UML provides a mechanism to communicate between a developer and others when they are involved in modeling a system. However, it does not provide delicate concepts to express peculiar features of a specific system. Thus, in order to cope with the problem, the UML provides the extension mechanisms. Each feature of a specific system can be described with the UML extension mechanisms. In this article, we propose a meta-model for developing an application operated on the Android platform using the UML extension mechanisms. Since the modeling elements for the Android platform do not be supported by the standard UML we are convinced that the extended meta-model will facilitate efficient modeling when developing an Android application.

Standard-Based Integrated Management System Implemented for Heterogeneous Distributed Systems in Naval Ship Combat Management System

In response to higher price tags of software applications due to costly development efforts to scale them up, how to re-use legacy systems has drawn much attention. The navy has standardized the open-architecture combat system for that reason. This study suggests a method to apply already developed software and the one yet to be developed to an AMSM-based open-architecture common service environment. The system presented here deals with common services for management and monitoring based on an open architecture, representing heterogeneous systems using abstract information models independent of the system under management. The proposed method enables management and monitoring over the system without being affected by heterogeneous environment.

Development of Information Model based Integrated Management and Monitoring System for Naval Ship Combat System with Heterogeneous Distributed Environments

In the existing naval combat system, integrated management is done based on subsystems that make up the system. The naval combat system, however, is a large-scale distributed system made up of subsystems of diverse heterogeneous environments. Although each of the subsystems can be easily managed because they are on the same platform, it is extremely difficult to integrate and manage as a single entity all subsystems that make up the naval combat system because the heterogeneous environments and distributed systems have to be taken into account. In fact, there hasn`t been a technique available to integrate and manage subsystems that make up the naval combat system, until now. In this paper, the architecture of an integrated management system is designed and implemented to provide the user with various services. Furthermore, a system that can manage subsystems of the naval combat system in an integrated way is developed.

A Method for Selecting Software Reliability Growth Models Using Partial Data

ABSTRACT Software Reliability Growth Models (SRGMs) are useful for determining the software release date or additional testing efforts by using software failure data. It is not appropriate for a SRGM to apply to all software. And besides a large number of SRGMs have already been proposed to estimate software reliability measures. Therefore selection of an optimal SRGM for use in a particular case has been an important issue. The existing methods for selecting a SRGM use the entire collected failure data. However, initial failure data may not affect the future failure occurrence and, in some cases, it results in the distorted result when evaluating the future failure. In this paper, we suggest a method for selecting a SRGM based on the evaluation goodness-of-fit using partial data. Our approach uses partial data except for inordinately unstable failure data in the entire failure data. We will find a portion of data used to select a SRGM through the comparison between the entire failure data and the partial failure data excluded the initial failure data with respect to the predictive ability of future failures. To justify our approach this paper shows that the predictive ability of future failures using partial data is more accurate than using the entire failure data with the real collected failure data.Keywords:Software Reliability, Software Reliability Growth Model, Model Selection Criteria, T-point

A Method for Selecting Software Reliability Growth Models Using Trend and Failure Prediction Ability

Software Reliability Growth Models (SRGMs) are used to quantitatively evaluate software reliability and to determine the software release date or additional testing efforts using software failure data. Because a single SRGM is not universally applicable to all kinds of software, the selection of an optimal SRGM suitable to a specific case has been an important issue. The existing methods for SRGM selection assess the goodness-of-fit of the SRGM in terms of the collected failure data but do not consider the accuracy of future failure predictions. In this paper, we propose a method for selecting SRGMs using the trend of failure data and failure prediction ability. To justify our approach, we identify problems associated with the existing SRGM selection methods through experiments and show that our method for selecting SRGMs is superior to the existing methods with respect to the accuracy of future failure prediction.