• Journal of KIISE:Software and Applications
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• v.36 no.4
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• pp.273-282
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• 2009

Missing data is one of the common problems in building analysis or prediction models using software project data. Missing imputation methods are known to be more effective missing data handling method than deleting methods in small software project data. While K nearest neighbor imputation is a proper missing imputation method in the software project data, it cannot use non-missing information of incomplete project instances. In this paper, we propose an approach to missing data imputation for numerical software project data by combining K nearest neighbor and maximum likelihood estimation; we also extend the average absolute error measure by normalization for accurate evaluation. Our approach overcomes the limitation of K nearest neighbor imputation and outperforms on our real data sets.

• Journal of Information Technology Applications and Management
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• v.13 no.4
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• pp.237-255
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• 2006

This study was exploratively performed to demonstrate the management behavior of the public software project in korea. In this study, 167 auditing reports on the public software project which were carried out during $1999{\sim}2003$, were employed and surveyed. Survey reveals that quality management was the most neglected in process of software project management relative to other 12 management areas. And configuration management, risk management, time management, and scope management follow up in order in its vulnerability in software project management.

• Journal of Information Technology Applications and Management
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• v.11 no.4
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• pp.103-120
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• 2004

Identifying validated risk factors in software risk management is imperative for project managers. Although validated risk lists were provided by previous researchers, risk list associated with software project performance areas was not provided as yet. This paper represents a first step toward understanding risk lists by various project performance areas (time, cost, and quality) to help project managers alleviating the possibility of software project failure. Four simultaneous exploratory surveys were conducted with 29 experienced software project managers. Three different risk factor ranking sets for each project performance area were compared with, the risk ranking, which was provided without clarifying specific project performance areas. The risk lists and their corresponding perceived importance were different from previous research results. This implies that identifying risk factors for specific project performance areas can provide additional information for project managers. We concluded by discussing implications of our finds for both research and improving risk management practice.

• Journal of Information Technology Applications and Management
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• v.11 no.2
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• pp.15-27
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• 2004

Most software projects inevitably involve various types and degrees of uncertainty. Without proper risk assessment and coordination, software projects can easily run out of control and consume significant additional resource. Thus, risk management techniques are critical issues to information system researchers. Previous empirical studies of U.S. software firms support the adoption of development standardization and user requirement analysis techniques in risk-based software project management. Using data collected from software projects developed in Korea during 1999-2000, we conduct a comparative study to determine how risk management strategies impact software product and process performance in countries with dissimilar IT capabilities. In addition, we offer an alternative conceptualization of residual performance risk. We show that the use of residual performance risk as an intervening variable is inappropriate in IT developing countries like Korea where the role of late stage risk control remedies are critical. A revised model is proposed that generates more reliable empirical implications for Korean software projects.

• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.65-72
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• 2018

In this paper, we have studied how to reuse common data link software by applying software product line engineering. Existing common data link software performed different stages of design, implementation, and testing without sharing the accumulated knowledge of different developers. In this situation, developers agreed that sharing the assets of each project and reusing the previously developed software would save human and time costs. Even with the initial difficulties, the common Data Link is a continually proposed project in the defense industry, so we decided to build a product line. The common data link software can be divided into two domains. Among them, the initial feature model for the GUI software was constructed, and the following procedure was studied. Through this, we propose a plan to build a product line for core assets and reuse them in newly developed projects.

• Journal of Internet Computing and Services
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• v.19 no.2
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• pp.43-48
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• 2018

Various artifacts that are produced as software R&D project progresses contain research plan, research report, software requirements and design descriptions, etc. When conducting a software R&D project, it is necessary to confirm that the developed system has implemented its research requirements well. However, various research results make it difficult to design appropriate tests. So, there is a practical need for us to comprehensively handle the planning, execution, and reporting of software test for finding and verifying information related to the research. In this paper, we propose a useful method for software test process in R&D project which supports model based software testing. The proposed method supports automation of test design and generation of test data by explicitly separating each step of System Under Test (SUT). The method utilizes the various models representing the control flow of the function to extract the information necessary for testing the system. And it supports a systematic testing process based on TMMi and ISO 29119. Finally, we show the validity of the method by implementing a prototype with basic functionality to generate test data from software behavioral models.

• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.259-266
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• 2002

The main issue in software development is the ability of software project effort and cost estimation in the early phase of software life cycle. The regression models for project effort and cost estimation are presented by function point that is a software sire. The data sets used to conduct previous studies are of ten small and not too recent. Applying these models to 789 project data developed from 1990 ; the models only explain fewer than 0.53 $R^2$(Coefficient of determination) of the data variation. Homogeneous group in accordance with project delivery rate (PDR) divides the data sets. Then this paper presents general effort estimation models using project delivery rate. The presented model has a random distribution of residuals and explains more than 0.93 $R^2$ of data variation in most of PDR ranges.

• Journal of Software Engineering Society
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• v.26 no.4
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• pp.77-92
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• 2013

To plan a software project, the manager (1)make a work breakdown structure (WBS), (2) estimate efforts for each task, (3) assign employee to each task, and (4) estimate overall schedule. When software project becomes complicated, the possible combination of WBS, effort, and employee assignments dramatically becomes larger. Software planning tool can help software project managers to deal with this complexity. In this research, we discuss with a group of experts who work in software industry, to elicit practical requirements that should be considered in the software planning technique. Considering these requirements, we develop a software project planning tool APP (Automatic Project Planner) which provide effort estimation based on historical knowledge data and automatic human resource allocation. Our technique can be the basis of reasonable and practical software project planing.

• Asia pacific journal of information systems
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• v.13 no.2
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• pp.199-217
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• 2003

Based on the IS literature on software project risk management, we developed an integrated model to investigate the risk factors and risk management factors in project development. We also analyzed the interrelation between project risk and project risk management. The questionaries are collected from 83 project leaders. We tested reliability and validity of the measure and analyzed the obtained data. The results support our risk-based hypothesis that shows the importance of risk management in reducing project risks and improving performance of project and process.

• Asia pacific journal of information systems
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• v.16 no.3
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• pp.143-158
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• 2006

Identifying risk factors in software risk management is imperative for project managers. The purpose of this paper is to provide software project risk factors validated by statistical analysis, and thus to help project managers alleviating the possibility of software project failure. Factor analysis with data collected from 264 Korean project managers and consultants identified 12 categories and 46 risk factors. T-test results showed that project managers and participants had statistically different perception on 3 risk factors among those 46 risk factors. We concluded by discussing implications of our findings and future research directions.