• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.93-104
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• 2009

Modular implementation of a feature is a first step toward feature-oriented product line engineering, which develops and then utilizes core assets to configure products in terms of features. Aspect-oriented programming provides effective mechanisms for improving the modularity of feature implementations. However, as features in general are not independent of each other, changes in the implementation of one feature may cause changes to or side effects in the implementation of other features. Moreover, since the time at which a feature is incorporated into products, called feature binding time, may be various from compile time through load time to run time, a feature may have to be implemented differently depending on when the feature is bound into a product. To make each feature implementation module as independent as possible, this paper proposes aspectual implementation patterns that can effectively separate feature dependencies as well as feature binding time from feature implementation modules. These patterns enable flexible composition of feature implementation modules without affecting other modules according to feature selection. The approaches are demonstrated and evaluated based on a product line of scientific calculator applications.

• Journal of Digital Contents Society
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• v.18 no.3
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• pp.457-463
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• 2017

VOD service provides an additional revenue model for digital broadcasting companies in addition to the existing subscription fees and advertisement-based revenue models. Therefore, each digital broadcasting company develops its own VOD service and performs frequent improvement work. In this circumstance, the developer is seeking to improve the efficiency of the VOD service development. To address the needs of such developers, this study conducted a basic study to apply the feature-oriented analysis model to the development of VOD services. The feature-oriented analysis model is recognized (through a number of case studies) as an effective tool for analyzing the requirements of softwares with the functions that are interconnected organically. In this paper, we developed a feature model of VOD service and designed the primary functions of each feature and the test-cases that can test the these functions, laying the foundation for developing VOD services based on feature-oriented analysis model.

• Convergence Security Journal
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• v.17 no.3
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• pp.51-57
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• 2017

VOD service provides an additional revenue for broadcasting companies in addition to the existing subscription fees and advertisement-based revenue. Therefore, each broadcasting company develops its own VOD service and performs frequent improvement work. This leads to the development of new VOD services, so developers are considering ways to effectively handle the frequent development needs. In this background, we conducted an underlying research to apply the feature-oriented analysis model to the development of VOD service. The feature-oriented analysis model used in this study is the Feature-Oriented Domain Analysis (FODA) developed by SEI of Carnegie Mellon University. FODA provides a tool for specifying a feature model of a software domain, based on which developers determine the configuration of a software with customers. This study developed a feature model of the VOD service domain and devised the functionalities and testcases in an integrated manner with the feature model. Additionally, we proposed a VOD service development process utilizing the feature model, function specification, and testcases.

• Journal of KIISE:Software and Applications
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• v.32 no.2
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• pp.119-127
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• 2005

Product line analysis is an activity for analyzing requirements, their relationships, and constraints in a product line before engineering product line assets (e.g., architectures and components). A feature-oriented commonality and variability analysis (called feature modeling) has been considered an essential part of product line analysis. Commonality and variability analysis, although critical, is not sufficient to develop reusable and adaptable product line assets. Dependencies among features and feature binding time also have significant influences on the design of product line assets. In this paper. we propose a feature-oriented product line analysis model that extends the existing feature model in terms of three aspects (i.e., feature commonality and variability, feature dependency, and feature binding time). To validate the consistency among the three aspects we formally define the feature-oriented product line analysis model and provide rules for checking consistency.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.26-32
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• 2017

VOD (Video-On Demand) Services are considered to be one of the most successful data broadcasting services, along with Electronic Program Guides (EPGs). In particular, VOD services provide supplementary revenue for broadcasting companies in addition to the existing subscription fees and advertisement-based revenue. Therefore, each broadcasting company has developed its own VOD service and constantly seeks to improve it. This leads to the development of new VOD services, so developers are considering ways to effectively handle the frequent development needs. In this background, we conducted underlying research to apply the feature-oriented analysis model to the development of VOD services. The feature-oriented analysis model used in this study is the Feature-Oriented Domain Analysis (FODA) one developed by SEI of Carnegie Mellon University. FODA provides a tool for specifying the feature model of a software domain, based on which the developers can determine the configuration of the software with the customers. This study developed a feature model of the VOD service domain and devised the functionalities and test cases in an integrated manner with the feature model. Additionally, we proposed a VOD service development process utilizing the feature model, function specification, and test cases.

• The Journal of Society for e-Business Studies
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• v.12 no.3
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• pp.33-47
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• 2007

The requirements have been changed during development progresses, since it is impossible to define all of software requirements. These requirements change leads to mistakes because the developers cannot completely understand the software's structure and behavior, or they cannot discover all parts affected by a change. Requirement changes have to be managed and assessed to ensure that they are feasible, make economic sense and contribute to the business needs of the customer organization. We propose a feature-oriented requirements change management method to manage requirements change with value analysis and feature-oriented traceability links including intermediate catalysis using features. Our approach offers two contributions to the study of requirements change: (1) We define requirements change tree to make user requirements change request generalize by feature level. (2) We provide overall process such as change request normalization, change impact analysis, solution dealing with change request, change request implementation, change request evaluation. In addition, we especially present the results of a case study which is carried out in asset management portal system in details.

• Journal of Platform Technology
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• v.6 no.4
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• pp.18-25
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• 2018

This paper describes a real-time human and robot tracking method in Intelligent Space with multi-camera networks. The proposed method detects candidates for humans and robots by using the histogram of oriented gradients (HOG) feature in an image. To classify humans and robots from the candidates in real time, we apply cascaded structure to constructing a strong classifier which consists of many weak classifiers as follows: a linear support vector machine (SVM) and a radial-basis function (RBF) SVM. By using the multiple view geometry, the method estimates the 3D position of humans and robots from their 2D coordinates on image coordinate system, and tracks their positions by using stochastic approach. To test the performance of the method, humans and robots are asked to move according to given rectangular and circular paths. Experimental results show that the proposed method is able to reduce the localization error and be good for a practical application of human-centered services in the Intelligent Space.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.232-240
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• 2022

To fulfill user expectations, the rapid evolution of software techniques and approaches has necessitated reliable and flawless software operations. Aging prediction in the software under operation is becoming a basic and unavoidable requirement for ensuring the systems' availability, reliability, and operations. In this paper, an improved evolutionary computing-driven extreme learning scheme (ECD-ELM) has been suggested for object-oriented software aging prediction. To perform aging prediction, we employed a variety of metrics, including program size, McCube complexity metrics, Halstead metrics, runtime failure event metrics, and some unique aging-related metrics (ARM). In our suggested paradigm, extracting OOP software metrics is done after pre-processing, which includes outlier detection and normalization. This technique improved our proposed system's ability to deal with instances with unbalanced biases and metrics. Further, different dimensional reduction and feature selection algorithms such as principal component analysis (PCA), linear discriminant analysis (LDA), and T-Test analysis have been applied. We have suggested a single hidden layer multi-feed forward neural network (SL-MFNN) based ELM, where an adaptive genetic algorithm (AGA) has been applied to estimate the weight and bias parameters for ELM learning. Unlike the traditional neural networks model, the implementation of GA-based ELM with LDA feature selection has outperformed other aging prediction approaches in terms of prediction accuracy, precision, recall, and F-measure. The results affirm that the implementation of outlier detection, normalization of imbalanced metrics, LDA-based feature selection, and GA-based ELM can be the reliable solution for object-oriented software aging prediction.

• Journal of Multimedia Information System
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• v.2 no.1
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• pp.171-178
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• 2015

This article describes 3 dimensional (3D) face recognition system using histogram of oriented gradients (HOG) based on face curvature. The surface curvatures in the face contain the most important personal feature information. In this paper, 3D face images are recognized by the face components: cheek, eyes, mouth, and nose. For the proposed approach, the first step uses the face curvatures which present the facial features for 3D face images, after normalization using the singular value decomposition (SVD). Fisherface method is then applied to each component curvature face. The reason for adapting the Fisherface method maintains the surface attribute for the face curvature, even though it can generate reduced image dimension. And histogram of oriented gradients (HOG) descriptor is one of the state-of-art methods which have been shown to significantly outperform the existing feature set for several objects detection and recognition. In the last step, the linear discriminant analysis is explained for each component. The experimental results showed that the proposed approach leads to higher detection accuracy rate than other methods.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.281-284
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• 2017

최근 임베디드 시스템 개발이 Model Driven Engineering 방식으로 변화하면서 요구사항과 모델 간의 추적성을 보장하는 것이 매우 중요해졌다. 이 논문에서는 기존의 FDD(Feature Driven Development)와 FOSE(Feature Oriented Software Engineering) 방법론에 적용된 feature 개념을 재정의하여 이를 AUTOSAR platform에 적용하는 방법을 제시하며 요구사항부터 model, code까지 추적성을 검증한다.