• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.333-338
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• 2007

소프트웨어 개발 프로젝트의 15%는 시작하기도 전에 종결되며, 66%의 프로젝트는 실패로 간주되고 있다. 또한 평균적으로, 완료된 프로젝트의 43%가 비용을 초과하는 것으로 나타났다. 실제로 2002년도 미국에서 소프트웨어 프로젝트의 투자 실패로 인한 손실은 비용의 초과로 생긴 170억 달러를 포함해 총 손실 금액이 380억 달러인 것으로 추정하고 있다. 이러한 문제점을 해결하고자 하는 여러 시도 중에 하나가 ISBSG(International Software Benchmarking Standard Group, 2004)으로, 소프트웨어 프로젝트 관련 데이터를 국제적으로 수집하여 위와 같은 문제의 원인을 밝히고자 노력하고 있다. 본 연구는 ISBSG에서 수집한 데이터를 이용해 소프트웨어 시스템과 관련된 요인 중에서 기능성 품질, 문서화품질, 훈련정도, 소프트웨어크기, 전체결함수, 사업요구사항충족, 사용편리성, 목표달성이라는 6개 변수 간의 연관성을 분석하였다. 분석대상 프로젝트는 49개이고, 분석 방법으로는 SURE(Seemingly Unrelated REgression)를 사용하였다. 분석 결과 소프트웨어 기능성품질은 사업요구사항충족, 사용편리성과 정의 관계를 가지며, 사용편리성은 사업요구사항충족과 정의 관계를 가지는 것으로 밝혀졌다. 또한 사업요구사항충족은 목표달성과 정의 관계를 가지고 있다.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.7
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• pp.295-302
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• 2023

Software requirements written in natural language may have different meanings from the stakeholders' viewpoint. When designing an architecture based on quality attributes, it is necessary to accurately classify quality attribute requirements because the efficient design is possible only when appropriate architectural tactics for each quality attribute are selected. As a result, although many natural language processing models have been studied for the classification of requirements, which is a high-cost task, few topics improve classification performance with the imbalanced quality attribute datasets. In this study, we first show that the classification model can automatically classify the Korean requirement dataset through experiments. Based on these results, we explain that data augmentation through EDA(Easy Data Augmentation) techniques and undersampling strategies can improve the imbalance of quality attribute datasets, and show that they are effective in classifying requirements. The results improved by 5.24%p on F1-score, indicating that handling imbalanced data helps classify Korean requirements of classification models. Furthermore, detailed experiments of EDA illustrate operations that help improve classification performance.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.99-109
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• 2021

In recent machine learning studies, in order to consider the quality and completeness of data, derivation of non-functional requirements for data has been proposed from the viewpoint of requirements engineering. In particular, requirements engineers have defined data requirements in machine learning. In this study, data requirements were derived at the data acquisition (DAQ) stage, where data is collected and stored before data preprocessing. Through this, it is possible to express the requirements of all data required in the existing DAQ system, the presence of tasks (functions) satisfying them, and the relationship between the requirements and functions. In addition, it is possible to elicit requirements and to define the relationship, so that a software design document can be produced, and a systematic approach and direction can be established in terms of software design and maintenance. This research using existing DAQ system cases, scenarios and use cases for requirements engineering approach are created, and data requirements for each case are extracted based on them, and the relationship between requirements, functions, and goals is illustrated through goal modeling. Through the research results, it was possible to extract the non-functional requirements of the system, especially the data requirements, from the DAQ system using requirements engineering.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.35 no.1
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• pp.127-148
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• 2024

This study aimed to propose considerations for attributes and their standardization strategies during the data collection process for electronic publications by domestic distributors for the National Library of Korea. The research identified a total of 21 essential and optional attributes based on a survey and a Focused Group Interview (FGI) with the staff responsible for legal deposit and acquisition tasks at the National Library of Korea. Additional attributes were found necessary during the data quality verification process, leading to the specification of essential and optional attributes for various types of materials, including eBooks, audiobooks, webtoons, and web novels. The standardization of attribute values, essential for enhancing the identifiability and management efficiency of electronic publications, included adherence to ISO 8601 rules for dates and times, clear designation of limited-range attribute values such as file format and adult content, and detailed description of information related to titles. Furthermore, the study highlighted the need for establishing standardized metadata requirements and continuous data quality management and monitoring systems.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.1415-1418
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• 2009

최근 보안용 소프트웨어에 대한 결함사항이 증대됨에 따라, 관련 서비스 즉, 보안용 소프트웨어 품질을 평가하고 개선하기 위한 기술이 집중적으로 요구되며 품질평가 방안에 대한 연구와 시험기술 개발이 요구된다. 따라서 본 연구에서는 보안용 소프트웨어의 기능성과 일반적 요구사항의 시험 인증 사례를 통해 수집데이터를 근거로 필수적으로 확보해야 할 품질 수준을 정의하고 품질수준을 도출과 결함의 유형 분석을 통하여 기능성 개발단계 상의 취약부분을 도출함으로써 품질향상을 최적화하고자 한다.

• Information Systems Review
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• v.10 no.1
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• pp.91-113
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• 2008

Recently, as most functional business activities in an enterprise are supported by computerized information systems, data duplication and inconsistency among functional information systems become serious problems. It brings people to have many interests on data quality management. This paper presents a case study in which a company had improved their data quality by enhancing their data quality management processes. Though the case study, we describe main issues and risk factors in the process of data quality improvement projects as well as solutions to resolve the issues, which can be referred by other companies who pursue data quality improvement. Also, the improvement effects are evaluated by multidimensional perspectives which include quantitative and qualitative measures on data quality, productivity, customer satisfaction, organization, and culture.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.12
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• pp.549-560
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• 2015

There is a wide variety of data quality attributes such as the ones proposed by the ISO/IEC organization and also by many other domestic and international institutions. However, it takes considerable time and costs to apply those criteria and guidelines to real environment. Therefore, it needs to define data quality evaluation attributes which are easily applicable and are not influenced by organizational environment limitations. The purpose of this paper is to derive data quality attributes and order of their priorities based on customer requirements for managing the process systematically and evaluating the data quantitatively. This study identifies the customer cognitive constructs of data quality attributes using the RGT(Repertory Grid Technique) based on a Korean quality standard model (DQC-M). Also the correlation analysis on the identified constructs is conducted, and the evaluation attributes is prioritized and ranked using the AHP. As the results of this paper, the consistent system, the accurate data, the efficient environment, the flexible management, and the continuous improvement are derived at the first level of the data quality evaluation attributes. Also, Control Compliance(13%), Regulatory Compliance(10%), Requirement Completeness(9.6%), Accuracy(8.4%), and Traceability(6.8%) are ranked on the top 5 of the 19 attributes in the second level.

• 한국IT서비스학회:학술대회논문집
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• 2007.11a
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• pp.345-350
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• 2007

최근 기업의 각 업무가 정보화 되면서 부문별, 업무별 정보시스템의 데이터 간에 심각한 중복성과 불일치성의 문제가 대두되면서 데이터 품질관리에 관심이 집중되고 있다. 본 연구는 실제로 데이터 표준 관리와 데이터 요구사항 관리를 통매 데이터 품질 관리 프로세스를 개선한 사례를 제시함으로써 데이터 품질 향상을 위해 노력하는 타 기업들에게 도움을 주고자 하였다. 또한, 개선된 데이터 품질 관리 프로세스에 대한 다차원적인 평가로서 데이터 품질, 생산성, 고객만족도, 조직 및 문화의 측면에서 정성 적이고 정량적인 지표를 통한 개선효과를 살펴보고 평가함으로써 제안된 프로세스에 의해 품질수준이 향상되었음을 검증하였고 평가 분석을 통한 시사점을 도출하였다.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.7
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• pp.205-212
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• 2020

Defects are an important factor in the quality of software developments. In order to manage defects, we propose additional information of search and classification. Additional information suggests a systematic classification scheme and method of operation. In this study, we propose additional information at the requirements analysis stage for defect management.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.148-150
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• 2012

최근 대용량 스트림 데이터에 대한 요구사항이 발생하고 있다. 이때 모든 대용량 스트림을 실시간으로 좋은 서비스를 제공하는 것은 실제적으로 불가능하다. 즉 대용량 스트림 데이터에 대한 QoS(Quality of Service: 서비스 품질)이 중요한 이슈가 되고 있다. 이러한 QoS를 정의하기 위해서는 센서 스트림 데이터에 대한 우선순위 부여방법이 가장 원천적으로 중요한 사항이 된다. 현재 센서 네트워크상에서의 서비스 품질은 연구되고 있지만 미들웨어 레이어에서의 우선순위 부여 방법에 대한 연구가 미비하다. 센서 스트림은 자체적으로는 우선순위를 가질 수 없으므로 사용자 질의 우선순위와 센서 스트림의 발생 시간등을 고려하여 대용량 센서 스트림에 대한 우선순위를 부여하는 방법을 제안한다.