Soojin Park

To enable effective change impact management in business applications, robust requirements traceability is essential. However, manual approaches are inefficient and prone to errors. While the prior Model-Driven Engineering (MDE)-based research, including the author’s theoretical models, established the principles of traceability, these approaches lacked decisive quantitative validation using metrics such as precision and recall, thereby limiting their real-world applicability. This paper addresses these limitations by introducing the CRSensor framework, which integrates the real-time automated trace link generation and dynamic refinement of the developer model. This approach enhances the reliability and completeness of organizational impact analysis, resolving key weaknesses of conventional link recovery methods. Notably, CRSensor maintains structural consistency throughout the lifecycle, overcoming reliability limitations often found in traditional information retrieval (IR)/machine learning (ML)-based traceability solutions. Empirical evaluation demonstrates that CRSensor achieves an average trace link setting performance with a precision of 0.95, a recall of 0.98, and an auto-generation rate of 80%. These results validate both the industrial applicability and the quantitative rigor of the proposed framework, paving the way for broader practical adoption.

디지털 트랜스포메이션은 기업의 경영 전략적 관점에서의 조직, 프로세스, 비즈 니스 모델, 커뮤니케이션의 광범위하고 근본적 변화를 요구하고 있으나, 성공적인 트랜스포 메이션의 핵심 선제요건 중 하나는 구성원의 IT(Information Technology) 역량이다. 공학적 배경 지식 없이 기술경영을 전공하는 학생들은 비교적 단기간에 경영관리 능력과 IT 역량을 동시에 키워야 하는 난제에 처해 있다. 이러한 이유로 효과적인 IT 역량 교육 방법은 기술경 영학 분야의 교육 이슈 중 하나로 부각되고 있다. 본 논문은 디지털 트랜스포메이션의 흐름을 주도할 수 있는 학생들을 양성하기 위한 IT 역량 교육은 “무엇”을 “어떻게” 가르쳐야 할 것 인가라는 질문에 대한 답을 찾기 위한 하나의 사례로서, 서강대학교 기술경영 전문대학원의 IT 관련 커리큘럼 리노베이션의 과정과 현재까지 교육과정 실행 결과를 제시한다. 특히, IT 역량 교육의 출발점이자 진입장벽이 되는 기초 프로그래밍 교육 과정의 피드백 결과에 대한 충분한 논의를 통해, 기술경영대학원 학생들을 위한 효율적인 IT 교육의 운영 방향에 대한 선행 참조사례를 제공하는 데 본 논문의 목적이 있다.

The middleware framework for IoT collaboration services should provide efficient solutions to context awareness and uncertainty issues among multiple collaboration domains. However, existing middleware frameworks are mostly limited to a single system, and developing self-adaptive IoT collaboration services using existing frameworks requires developers to take considerable time and effort. Furthermore, the developed IoT collaboration services are often dependent on a particular domain, which cannot easily be referenced in other domains. This paper proposes a cloud-based middleware framework that provides a set of cloud services for self-adaptive IoT collaboration services. The proposed middleware framework is generic in the sense that it clearly separates domain-dependent components from the layers that leverage existing middleware frameworks. In addition, the proposed framework allows developers to upload domain-dependent components onto the cloud, search for registered components, and launch Virtual Machine (VM) running a new MAPE cycle via a convenient web-based interface. The feasibility of the proposed framework has been shown with a simulation of an IoT collaboration service that traces a criminal suspect. The performance evaluation shows that the proposed middleware framework runs with an overhead of only 6% compared to pure Java-based middleware and is scalable as the number of VMs increases up to 16.

One of the most widely used models for specifying functional requirements is a use case model. The viewpoint of the use case model that views a system as a black box focuses on descriptions of external interactions between the system and related environments. However, for embedded systems that do not disclose most implementation logics outside the system, black box-based use case models may experience the drawback that considerable information that must be defined for system developments is omitted. To solve this shortcoming, several studies have been proposed on the use of kind of white box technique in which the dynamic behaviors of embedded systems are defined first using a state diagram and the results are reflected in the requirement specifications. However, white box-based modeling has not been widely adopted by developers due to tasks that require a lot of time in the requirement analysis phase in the initial phase of the software development life cycle. This study proposes a gray box-based requirement specification method as a trade-off between two contradictory elements (the amount of information required to develop an embedded system and the cost of the effort required during the requirement analysis phase) in terms of the two approaches, the black and the white box-based models. The proposed method suggests that an appropriate depth level of embedded system modeling is required to define the requirements. This study also proposes a mechanism that automatically generates an application programming interface for each component based on the created model. The proposed method was applied to the development of a camera sensor controller in a mobile phone, and the case results proved the feasibility of the method through discussion of the application results.

A well-defined and prioritized set of use cases enables the enhancement of an entire system by focusing on more important use cases identified in the previous iteration. These use cases are given more opportunities to be refined and tested. Until now, use case prioritization has been done from a user perspective, and through balanced measurement of actors/ objects usage. Lack of cost consideration for realization, however, renders it ineffective for economic purposes. Hence, this study incorporates the ‘value’ concept, based on cost benefit analysis, in use case prioritization for embedded systems. The use case satisfaction level is used as the surrogate for ‘benefit’, and the complexity of implementation for ‘cost’. Based on the value, use cases are prioritized. As a proof-of-concept, we apply our value-based prioritization method to the development of a camera system in a cellular phone.

Starting with the Internet of Things (IoT), new forms of system operation concepts have emerged to provide creative services through collaborations among autonomic devices. Following these paradigmatic changes, the ability of each participating system to automatically diagnose the degree of quality it is providing is inevitable. This paper proposed a method to automatically detect symptoms that hinder certain quality attributes. The method consisted of three steps: (1) extracting information from real usage logs and automatically generating an activity model from the captured information; (2) merging multiple user activity models into a single, representative model; and (3) detecting differences between the representative user activity model, and an expected activity model. The proposed method was implemented in a domain-independent framework, workable on the Android platform. Unlike other related works, we used quantitative evaluation results to show the benefits of applying the proposed method to five Android-based, open-source mobile applications. The evaluation results showed that the average precision rate for the automatic detection of symptoms was 70%, and the success rate for user implementation of usage scenarios demonstrated an improvement of around 21%, when the automatically detected symptoms were resolved.

With the emergence of various forms of smart devices and new paradigms such as the Internet of Things (IoT) concept, the IT (Information Technology) service areas are expanding explosively compared to the provision of services by single systems. A new system operation concept that has emerged in accordance with such technical trends is the IT ecosystem. The IT ecosystem can be considered a special type of system of systems in which multiple systems with various degrees of autonomy achieve common goals while adapting to the given environment. The single systems that participate in the IT ecosystem adapt autonomously to the current situation based on collected data from sensors. Furthermore, to maintain the services supported by the whole IT ecosystem sustainably, the configuration of single systems that participate in the IT ecosystem also changes appropriately in accordance with the changed situation. In order to support the IT ecosystem, this paper proposes an architecture framework that supports dynamic configuration changes to achieve the goal of the whole IT ecosystem, while ensuring the autonomy of single systems through the collection of data from sensors so as to recognize the situational context of individual participating systems. For the feasibility evaluation of the proposed framework, a simulated example of an IT ecosystem for unmanned forest management was constructed, and the quantitative evaluation results are discussed in terms of the extent to which the proposed architecture framework can continuously provide sustainable services in response to diverse environmental context changes.

This study examined the security of SCADA system and its protocols, more specifically, SCADA/DNP3 protocol security. To achieve the study goals, a SCADA simulation environment is designed for water pumping process through connectivity of intelligent sensors, the payload is constructed, and security is deployed inside DNP3 protocol stack and then bytes are multicast to subcontrollers.

Cloud computing has emerged as more than just a piece of technology, it is rather a new IT paradigm. The philosophy behind cloud computing shares its view with green computing where computing environments and resources are not as subjects to own but as subjects of sustained use. However, converting currently used IT services to Software as a Service (SaaS) cloud computing environments introduces several new risks. To mitigate such risks, existing software development processes must undergo significant remodeling. This study analyzes actual cases of SaaS cloud computing environment adoption as a way to derive four new best practices for software development and incorporates the identified best practices for currently-in-use processes. Furthermore, this study presents a design for generic software development processes that implement the proposed best practices. The design for the generic process has been applied to reinforce the weak points found in SaaS cloud service development practices used by eight enterprises currently developing or operating actual SaaS cloud computing services. Lastly, this study evaluates the applicability of the proposed SaaS cloud oriented development process through analyzing the feedback data collected from actual application to the development of a SaaS cloud service Astation.