대함유도무기 비행시험 업무 정립을 위한 최적 프레임워크 개발 - 표준 프로세스를 중심으로 -

안장근,김의환,조보람 한국방위산업학회 2018 韓國防衛産業學會誌 Vol.25 No.2

The purpose of this paper is to develop the framework for increasing efficiency of the business processes for anti-ship missile flight test. First of all, for establishing the framework structure definition, it is performed framework components identification, region classification, step classification and framework template. The Frame components include standard processes, standard outputs and issue checklists. Framework regions are divided into system work region, test safe region and test support region. Framework steps consist of flight test plan, flight test readiness, flight test execution and flight test follow-up step. Framework template and ID classification schemes are proposed. Since the framework structure definition, the total of 15 frameworks for anti-ship missile flight test are developed. The evaluation of the developed framework is conducted to demonstrate the practicality of the framework. It is believed that the proposed framework will contribute to anti-ship missile development through the standardized processes. 본 논문의 목적은 대함유도무기 비행시험의 업무 효율 증대를 위한 프레임워크 구조 정의와 프레임워크 개발 결과를 제시하는 것이다. 우선 프레임워크 구조 정의를 위하여 프레임워크 구성요소 식별, 영역 분류, 단계 구분 및 프레임워크 템플릿 개발을 수행하였다. 프레임워크의 구성요소는 표준 프로세스, 표준 산출물, 이슈사항 체크리스트로 구성되어 있다. 프레임워크의 영역 분류는 체계수행, 시험안전, 시험지원으로 나누어져 있다. 프레임워크의 단계 구분은 비행시험 계획, 준비, 수행, 후속으로 이루어져 있다. 프레임워크 개발을 위한 프레임워크 템플릿과 ID 식별코드 체계를 함께 제시하였다. 프레임워크 구조 정의를 한 후 대함유도무기 비행시험을 위한 총 15개 프레임워크가 개발되었다. 개발된 프레임워크에 대한 평가 설문을 실시하여 프레임워크의 실용성을 입증하였다. 대함유도무기 비행시험에 적용코자 개발된 프레임워크는 표준화된 업무 정립을 통해 대함유도무기 체계개발 성과 창출에 기여할 것으로 판단된다.

딥러닝 프레임워크의 비교

정여진(Yeojin Chung),안성만(SungMahn Ahn),양지헌(Jiheon Yang),이재준(Jaejoon Lee) 한국지능정보시스템학회 2017 지능정보연구 Vol.23 No.2

The deep learning framework is software designed to help develop deep learning models. Some of its important functions include “automatic differentiation” and “utilization of GPU”. The list of popular deep learning framework includes Caffe (BVLC) and Theano (University of Montreal). And recently, Microsofts deep learning framework, Microsoft Cognitive Toolkit, was released as open-source license, following Google’s Tensorflow a year earlier. The early deep learning frameworks have been developed mainly for research at universities. Beginning with the inception of Tensorflow, however, it seems that companies such as Microsoft and Facebook have started to join the competition of framework development. Given the trend, Google and other companies are expected to continue investing in the deep learning framework to bring forward the initiative in the artificial intelligence business. From this point of view, we think it is a good time to compare some of deep learning frameworks. So we compare three deep learning frameworks which can be used as a Python library. Those are Googles Tensorflow, Microsoft’s CNTK, and Theano which is sort of a predecessor of the preceding two. The most common and important function of deep learning frameworks is the ability to perform automatic differentiation. Basically all the mathematical expressions of deep learning models can be represented as computational graphs, which consist of nodes and edges. Partial derivatives on each edge of a computational graph can then be obtained. With the partial derivatives, we can let software compute differentiation of any node with respect to any variable by utilizing chain rule of Calculus. First of all, the convenience of coding is in the order of CNTK, Tensorflow, and Theano. The criterion is simply based on the lengths of the codes and the learning curve and the ease of coding are not the main concern. According to the criteria, Theano was the most difficult to implement with, and CNTK and Tensorflow were somewhat easier. With Tensorflow, we need to define weight variables and biases explicitly. The reason that CNTK and Tensorflow are easier to implement with is that those frameworks provide us with more abstraction than Theano. We, however, need to mention that low-level coding is not always bad. It gives us flexibility of coding. With the low-level coding such as in Theano, we can implement and test any new deep learning models or any new search methods that we can think of. The assessment of the execution speed of each framework is that there is not meaningful difference. According to the experiment, execution speeds of Theano and Tensorflow are very similar, although the experiment was limited to a CNN model. In the case of CNTK, the experimental environment was not maintained as the same. The code written in CNTK has to be run in PC environment without GPU where codes execute as much as 50 times slower than with GPU. But we concluded that the difference of execution speed was within the range of variation caused by the different hardware setup. In this study, we compared three types of deep learning framework: Theano, Tensorflow, and CNTK. According to Wikipedia, there are 12 available deep learning frameworks. And 15 different attributes differentiate each framework. Some of the important attributes would include interface language (Python, C ++, Java, etc.) and the availability of libraries on various deep learning models such as CNN, RNN, DBN, and etc. And if a user implements a large scale deep learning model, it will also be important to support multiple GPU or multiple servers. Also, if you are learning the deep learning model, it would also be important if there are enough examples and references.

Automotive Cluster UI Design Based on Time and Path from the Perspective of the ‘Passenger’

김현지,정의철 한국디자인학회 2019 디자인학연구 Vol.32 No.3

Background One important design issue is the examination of how the user interface (UI) supports the new user role in future mobility. However, there are few design studies on the passenger’s cognitive needs and behavior in autonomous vehicles (AVs) based on empirical data. There is no doubt that autonomous mobility technologies are growing. The technology is already aiding the driving experience, and it will change the mobility culture and the transition of ‘driver’ into ‘passenger.’ This study is based on the premise that future AVs are capable of performing all driving tasks and proposes a set of passenger-centered automotive cluster UI designs for future mobility employing two factors: time and path. A collection of empirical data is provided to understand the passenger’s perspective. Methods In this study, a solid set of empirical data on the cognitive needs of passengers is collected. Human cognitive characteristics and driving tasks are investigated from various viewpoints to understand the passenger’s perspective. The cognitive relationship in the driving environment is analyzed through a literature review on situation awareness (SA) and structuring of the data flow framework. The framework is further explored by connecting the technological role transformation to the passenger. Three sets of user tests and in-depth interviews were undertaken to construct the empirical database on the passenger. The user tests were designed employing the Wizard of Oz method, and the results were summarized using descriptive and exploratory analysis. Based on these insights, a set of UI designs from the perspective of the passenger was proposed, and usability tests were conducted to verify its effectiveness and usability. Results The results of the tests demonstrate that a major percentage of the information request was related to time (current time and duration) and path (vehicle location and surroundings). Based on the data, a UI framework was built. Two usage scenarios were designed, time-full and time-less, for better in-situation comprehension. Time- and route-based UI were proposed to flow with the scenarios. A usability test was conducted, and a passenger’s cognitive framework was defined. There are two aspects to this study: the data flow frameworks of the driver/passenger, and the UI design proposal for the future AVs. The detailed data relationship between the user, the vehicle, and the road is determined as a framework. Also, the driver's data perceiving flow is analyzed to understand the data flow change due to AVs. Furthermore, the cognitive framework of the passenger was proposed based on the data. Conclusions This study provides a solid understanding of drivers’ emerging needs when they are relieved of the cognitive burden of driving tasks. The UI features for AVs are introduced based on the empirical data and research related to the provision of better situation awareness, focusing on time and location. This study contributes to the extant literature by observing the perspective of passengers in autonomous vehicles based on a qualitative study. The proposed UI design will be further explored as a communication method between the system and the passive user in future mobility. Background One important design issue is the examination of how the user interface (UI) supports the new user role in future mobility. However, there are few design studies on the passenger’s cognitive needs and behavior in autonomous vehicles (AVs) based on empirical data. There is no doubt that autonomous mobility technologies are growing. The technology is already aiding the driving experience, and it will change the mobility culture and the transition of ‘driver’ into ‘passenger.’ This study is based on the premise that future AVs are capable of performing all driving tasks and proposes a set of passenger-centered automotive cluster UI designs for future mobility employing two factors: time and path. A collection of empirical data is provided to understand the passenger’s perspective. Methods In this study, a solid set of empirical data on the cognitive needs of passengers is collected. Human cognitive characteristics and driving tasks are investigated from various viewpoints to understand the passenger’s perspective. The cognitive relationship in the driving environment is analyzed through a literature review on situation awareness (SA) and structuring of the data flow framework. The framework is further explored by connecting the technological role transformation to the passenger. Three sets of user tests and in-depth interviews were undertaken to construct the empirical database on the passenger. The user tests were designed employing the Wizard of Oz method, and the results were summarized using descriptive and exploratory analysis. Based on these insights, a set of UI designs from the perspective of the passenger was proposed, and usability tests were conducted to verify its effectiveness and usability. Results The results of the tests demonstrate that a major percentage of the information request was related to time (current time and duration) and path (vehicle location and surroundings). Based on the data, a UI framework was built. Two usage scenarios were designed, time-full and time-less, for better in-situation comprehension. Time- and route-based UI were proposed to flow with the scenarios. A usability test was conducted, and a passenger’s cognitive framework was defined. There are two aspects to this study: the data flow frameworks of the driver/passenger, and the UI design proposal for the future AVs. The detailed data relationship between the user, the vehicle, and the road is determined as a framework. Also, the driver's data perceiving flow is analyzed to understand the data flow change due to AVs. Furthermore, the cognitive framework of the passenger was proposed based on the data. Conclusions This study provides a solid understanding of drivers’ emerging needs when they are relieved of the cognitive burden of driving tasks. The UI features for AVs are introduced based on the empirical data and research related to the provision of better situation awareness, focusing on time and location. This study contributes to the extant literature by observing the perspective of passengers in autonomous vehicles based on a qualitative study. The proposed UI design will be further explored as a communication method between the system and the passive user in future mobility.

딥러닝 오픈소스 프레임워크의 사례연구를 통한 도입 전략 도출

최은주(Eunjoo Choi),이준영(Junyeong Lee),한인구(Ingoo Han) 한국지능정보시스템학회 2020 지능정보연구 Vol.26 No.4

Many companies on information and communication technology make public their own developed AI technology, for example, Googles TensorFlow, Facebooks PyTorch, Microsofts CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framewo

사용자 행동 분석 프레임워크 제안

김혜린 ( Kim Hye Lin ),이민주 ( Lee Min Ju ),박승호 ( Park Seung Ho ) 디자인융복합학회 2017 디자인융복합연구 Vol.16 No.5

본 연구는 언어학적 해석 기반의 사용자 중심 디자인 방법론을 제시하고 그 가치를 증명하는 것이다. 연구의 결과로 제안된 사용자 행동 분석 프레임워크는 문장구조와 그 성분들 간의 통사구조가 사용자의 상황과 행동을 설명하는데 있어 논리적 근간이 될 수 있다고 보았다. 이를 기반으로 사용자 행동과 사용자 콘텍스트에 대해 미시적 관점으로 정의와 분류를 진행하였다. 또한 사용자 행동이 목적 지향적 특성의 패턴구조가 있음을 파악하고 이를 전제로 하는 사용자 행동 시퀀스를 구성했다. 다음으로 사용자 행동과 사용자 태도, 사용자 콘텍스트 간의 관계와 의의를 정의하여 사용자 행동 분석 프레임워크를 도출하였다. 프레임워크의 검증을 위해서는 사용자의 경험을 수집하고 프레임워크에 항목화를 실시한 사례연구를 진행하고 프레임워크의 연구적, 실무적 효용가치를 알아보기 위하여 현업 실무자들에게 전문가 평가를 실시하였다. 이를 통해 프레임워크가 가진 정성, 정량적 분석 틀로서의 가치를 증명하였고 향후 개발방향을 수립할 수 있었다. This study proposes and demonstrates the value of user - centered design methodology based on linguistic analysis. The results of the proposed user behavioural analysis framework suggested that the syntactic structure between the sentence structure and its components could be a logical basis for explaining the user's situation and behavior. Based on this, the definitions and classifications of user interactions and user contexts were conducted in a microscopically context. User behavior has also been established to identify pattern structures of purposeful nature and constitutes a user behavior sequence that prioritizes them. Next, the User Experience Analysis Framework was derived by defining the relationship between User Behavior and User Behavior and User Context and User Context. To verify the framework of the framework, a professional assessment was conducted to conduct a review of the user's experience and conduct a study of the framework of the framework and conduct of the framework of the framework of the framework and practical utility of the framework. Through this, it was possible to identify the value of the qualitative and quantitative framework of the framework and the future direction of development.

국가회계 개념체계 제정을 위한 기초(안)에 관한 연구

김이배,박성환,남혜정,이아영 한국정부회계학회 2018 정부회계연구 Vol.16 No.1

우리나라는 국가회계법, 국가회계기준에 관한 규칙 등 법령체계를 갖추고 2011회계연도부터 발생주의 국가재무제표를 공시하게 되었다. 그러나 국가회계기준 및 국가회계예규의 제정 및 개정, 해석의논리적 근거가 되는 개념체계는 제정되지 않았다. 이로 인하여 국가회계기준이나 예규가 상충되거나일관성을 결여하는 경우가 발생하고 있는 상황이다. 본 연구에서는 일반목적 국가회계 재무보고를 위한 개념체계의 기초(안)을 제시하고자 하였다. 본 연구는 국제적 정합성을 높이기 위해 IPSASB에서 제정한 국제공공부문 일반목적 재무보고를 위한 개념체계를 기초로 개념체계의 초안을 작성하였다. 그리고 개념체계(안)의 작성과정에서 우리나라와 국가회계 법령체계가 유사한 프랑스의 개념체계를 참조하였다. 국가회계 개념체계의 제정과 관련하여 향후에는 다음의 과제가 논의될 필요가 있다. 첫째, 국가회계실체와 보고실체에 대한 논의가 필요하다. 현재는 국가회계실체만 국가회계기준에 관한 규칙에 열거하고 있다. 개념체계(안)에서는 국가회계실체와 보고실체를 각각 달리 정의하고 있다. 이러한 정의에 의하여 현행 국가회계실체와 보고실체는크게 달라질 수 있다. 둘째, 현금흐름에 대한 정보를 재무제표에 포함시켜야 하는지에 대한 논의가 필요하다. 현재 개념체계(안)에서는 현금흐름에 대한 정보를 재무제표에 포함시키는 것으로 정리하였으나 현행 국가결산서의 세입・세출결산서로 대체할 수도 있을 것이다. 셋째, 개념체계의 제정과 함께 기존의 국가회계기준에 관한 규칙이나 예규 등에 포함되어 있는 개념체계와 관련된 내용을 재정비 할 필요가 있다. 넷째, 해외 선진사례에서는 수년에 걸쳐 개념보고서의 기초(안)을 작성하고 공청회 등을 거쳐 의견을 수렴하여 개념체계의 전체적인 틀을 완성하는 접근방법을 사용하고 있다. 우리나라의 경우에도 개념체계의 제정과정에 관한 로드맵을 작성하고 추진할 수 있는 계획의 수립이 필요하다. 다섯째, 개념체계를 법령체계에 포함시키고 있는 국가는 없는 것으로 판단된다. 그러나 개념체계의 역할과 권위가 인정될 수 있도록 개념체계에 대한 위상을 정립할 필요가 있다. Korean government has adopted the accruals accounting and releases the financial statements based on accruals accounting since 2011. For the accrual-based government financial reporting, Korea has made various efforts by re-organizing the government accounting act and the rules on government accounting standards. However, the conceptual framework, which a logical basis for the formulation, revision and interpretation of government accounting standards has not been established yet. The absence of a conceptual framework may cause many problems such as the conflicts and inconsistency between government accounting standards and published rulings. To address this concern, this paper suggests the conceptual framework for general purpose financial reporting by government. We propose the preliminary version of conceptual framework and compare it with the provisions which was developed and approved by the International Public Sector Accounting Standards Board(IPSASB). The conceptual framework of this paper is consists of eight chapters including preface. In preface, we introduce the purpose of government accounting conceptual frame and definition and characteristics of government entities. In chapter 1, we introduce the role and position of conceptual framework and applied entities. In chapter 2, we define the purpose of general financial reporting and users and information they need. Chapter 3 includes the definition of reporting entities and accounting entities. Chapter 4 introduces the information qualities in government financial reporting. In chapter 5 and 6, we identify and define the components of financial statements. And explain the recognition of the components. Chapter 7 and 8 provide measurement of assets and liabilities and presentation, respectively. We suggest the issues that need to discuss for the conceptual framework in the future. First, more discussion is required to define and discriminate the government accounting entities and reporting entities. Although the government accounting entities are listed in government accounting standards, the definitions of government accounting entities and reporting entities are different in conceptual framework. Second, the debate on whether the cash flow information should included in financial statements is another concern. Third, the road map for conceptual framework is needed for establishment of successful conceptual framework. Finally, there is no country that includes the conceptual framework in the statutory system. Therefore, it is necessary to establish the status of the conceptual framework so that the role and authority of the conceptual framework can be recognized.

CCR 역량 프레임워크 개발 준거를 활용한 OECD 학습 프레임워크 분석의 시사점 탐색

김정효 ( Kim¸ Jeonghyo ),유창완 ( Yu¸ Changwan ) 인하대학교 교육연구소 2020 교육문화연구 Vol.26 No.6

본 연구는 OECD 2030 학습 프레임워크 분석을 통해 차기 국가 수준 교육과정에서의 역량 개발 방안을 탐색하고자 하였다. 이를 위해 국제기구 및 국가별 교육과정의 역량 프레임워크의 개발 배경 및 목표, 역량 프레임워크의 구조 및 요소를 살펴보았다. 또한 CCR 프레임워크 개발 시 적용한 다섯 가지의 준거에 따라 OECD 학습 프레임워크를 중점적으로 분석하되, 타 국가의 역량 프레임워크와도 비교·분석하였다. 연구 결과, OECD 학습 프레임워크에서의 역량은 국가별 역량에 비해 비교적 포괄적으로 제시하고 있고, 간결성 측면에서는 국가별 역량에 비해 미흡하다. 국가별 역량과 마찬가지로 중복성은 높은 편이고, 추상성의 수준은 적절하지만 개선이 필요하며, 전 세계적 유의미성은 높은 것으로 나타났다. 결론적으로 차기 국가 교육과정에서는 역량 프레임워크의 구조화를 위해서 CCR 개발 준거에 기초한 역량 프레임워크를 개발할 필요가 있으며, OECD Education 2030 연구의 긍정적 요소인 OECD 학습 프레임워크의 신생 역량 및 역량의 위계화 방식을 차기 교육과정에 반영할 것을 제안하였다. This study aimed to explore the ways to develop competencies pursued in the next national-level curriculum through an analysis of the OECD 2030 Learning Framework. To this end, the backgrounds and goals of development of competency frameworks of international organizations and national curricula, and the structures and elements of competency frameworks were examined. In addition, according to the five criteria applied in the development of the CCR framework(Comprehensive, Compact, Uncorrelated, Appropriate Layer of Abstraction, Globally Relevant), the OECD learning framework was mainly analyzed, but compared and analyzed with the competency frameworks of other countries. As a result of the study, it was found that the competencies in the OECD learning framework are presented more relatively comprehensively than the competencies of other national frameworks(Comprehensiveness). In terms of Compactness, they are insufficient compared to the competencies of other national frameworks. Redundancy is high(Uncorrelatedness). The level of abstraction is appropriate but is in need of improvement(Appropriate Layer of Abstraction). The Globally Relevance is high. The study proposed to structuralize a competency framework for developing the next national curriculum based on the CCR development criteria. Furthermore, the emerging competencies and the hierarchical methods to structuralize the competencies applied in the OECD Learning Framework need to be considered.

The Internet Design Framework for Improvement of Users’ Positive Emotions

Chunmao Wu,Xuefei Li,동초희 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.8

This study proposes an internet design framework for users to improve their positive emotions when they are in a negative mood. First, the literature review focuses on the definition of emotion, positive emotional design in internet experiences, and emotion regulation. Second, in order to construct an internet design framework that improves positive emotion, this paper adopts a qualitative analysis method to analyze 70 collected studies in the area of regulating emotion and stimulating positive emotions. Additionally, bibliometrics and statistics are conducted to summarize the framework and strategies. Third, two cases of internet design are presented: (a) Internet design that improves users' positive emotions is examined under the background of extreme rainstorm as an example; an applet service design is provided by case study; (b) in the context of COVID-19, we developed an Internet of things interactive design that improves users’ positive emotions. Fourth, the internet design framework and the results of the case studies are analyzed and discussed. Finally, an internet design framework is proposed to improve users’ positive emotions when they are in a negative mood, which includes the Detachment–empathy framework, External–protection framework, Ability–strengthen framework, Perspective–transformation framework, and Macro–cognitive framework. The framework can help designers to generate design ideas accurately and quickly when users are in a negative mood, to improve subjective well-being, and contribute to the development of internet experience design.

A Systematic Approach for Quantitative Analysis of Multidisciplinary Design Optimization Framework

KIM, Sangho,PARK, Jungkeun,LEE, Jeong-Oog,LEE, Jae-Woo THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIEN 2010 Transactions of the Japan Society for Aeronautical Vol.52 No.178

<P>An efficient Multidisciplinary Design and Optimization (MDO) framework for an aerospace engineering system should use and integrate distributed resources such as various analysis codes, optimization codes, Computer Aided Design (CAD) tools, Data Base Management Systems (DBMS), etc. in a heterogeneous environment, and need to provide user-friendly graphical user interfaces. In this paper, we propose a systematic approach for determining a reference MDO framework and for evaluating MDO frameworks. The proposed approach incorporates two well-known methods, Analytic Hierarchy Process (AHP) and Quality Function Deployment (QFD), in order to provide a quantitative analysis of the qualitative criteria of MDO frameworks. Identification and hierarchy of the framework requirements and the corresponding solutions for the reference MDO frameworks, the general one and the aircraft oriented one were carefully investigated. The reference frameworks were also quantitatively identified using AHP and QFD. An assessment of three in-house frameworks was then performed. The results produced clear and useful guidelines for improvement of the in-house MDO frameworks and showed the feasibility of the proposed approach for evaluating an MDO framework without a human interference.</P>

컴포넌트 프레임웍의 실용적 참조 모델

허진선(Jin Sun Her),김수동(Soo Dong Kim) 한국정보과학회 2006 정보과학회논문지 : 소프트웨어 및 응용 Vol.33 No.6

컴포넌트 기반 소프트웨어 공학(CBSE)은 재사용 가능한 소프트웨어 부품을 이용하여 어플리케이션을 개발하는 새로운 패러다임이다. 그러나 소프트웨어 부품을 조립하는 과정에 부품들 간에 불일치 문제가 발생하여 CBSE를 수행함에 있어 부담이 되고 있다. 따라서, 컴포넌트의 재사용 단위보다는 큰 프레임웍(Framework)이 요구되고 있으며 프레임웍은 관련 있는 컴포넌트와 커넥터들 그리고 도메인에 특화된 아키텍처로 구성된다. 프레임웍은 컴포넌트보다 많은 장점을 가지고 있지만, 프레임웍을 구성하는 핵심 요소들과 내부 구조는 명확히 정의되지 않고 있다. 즉, 현재까지 제시된 대부분의 프레임웍 모델들은 실용적이지 못한 개념적인 수준에 머물러 있다. 본 논문에서는 실용적인 수준의 프레임웍 참조 모델을 제안하고 프레임웍의 핵심 요소들을 정의한다. 프레임웍의 구체적인 구성요소들, 컴포넌트와 프레임웍의 상호 관련성, 커넥터의 확장된 개념들, 그리고 프레임웍 내에서의 특화된 아키텍처의 의미에 대해서 명확히 식별한다. 본 논문에서 제안된 프레임웍은 Java, J2EE, CORBA Component Model (CCM) 그리고 .NET과 같은 객체지향 기반 미들웨어에서 실용적으로 구현될 수 있을 것이다. Component-Based Software Engineering (CBSE) is widely accepted as new paradigms for building applications with reusable assets. Mismatch problems occur while integrating the assets and make a burden in CBSE. Therefore, a larger-grained reuse unit than a component such as a framework is required, and it consists of relevant components, connectors and domain-specific architecture. The benefits of frameworks over components are commonly known, however, the key elements and internal structure of framework has not been clearly defined. We believe most of the framework models proposed in recent works remain at conceptual level. In this paper, we propose apractical-level framework reference model, and define key elements of frameworks. The research goal is to precisely identify concrete elements of a framework, inter-connection of components within a framework, extended notion of connectors, and tailored meaning of architecture in a framework. Hence, the proposed framework can be practically implemented in common object-oriented languages and with middleware such as Java, J2EE, CORBA Component Model (CCM) and .NET.