• Journal of the Korea Society of Computer and Information
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• v.17 no.8
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• pp.123-133
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• 2012

Recently, as IT convergence has seen rapid growth the role and scope of software has been extended. many software companies are trying to improve the software quality and project outcome using software process improvement approach to cope with increasing software demands and software quality. Although software process improvement is difficult task which requires a lot of cost and time, there is still insufficient objective evidence on business benefits by its deployment. The purpose of this study is to analyze the relationship between software process improvement and software project productivity. That is, we investigated whether there is difference in software development productivity depends on software engineering level using statistical methods. We found that the software development productivity is different across the software engineering levels and the higher software engineering level can lead to improved software development productivity.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.57-64
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• 2000

In this paper we consider a Markovian perfect debugging model for which the software failure is caused by two types of faults, one which is easily detected and the other which is difficult to detect. When a failure occurs, a perfect debugging is immediately performed and consequently one fault is reduced from fault contents. We also treat the debugging time as a variable to develop a new debugging model. Several measures, including the distribution of first passage time to the specified number of removed faults, are also obtained using the proposed debugging model, Numerical examples are provided for illustrative purposes.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.507-514
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• 2001

In recent years, the development and the embodiment of information analysis system has been sprightly carried out in several fields of study. In this study, as and extension of these studies, we develop a system for multivariate analysis which might be widely used in social and natural sciences. This multivariate analysis system is developed by using multivariate analysis procedures in SAS/STAT software. Also, the system supply users with he environment of GUI(Graphical User Interface), which is constructed with AF(application frame) and SCL(screen control language) of SAS software, in order to help users to use the system with easy.

• Journal of Korean Society for Quality Management
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• v.27 no.1
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• pp.195-210
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• 1999

The multiplicity of software packages brings about a choice problem to the end-user and a multi-fold intensity to the competing developer. This study intends to provide guidelines solving the problems for both the end-user and the developer of packages for automatic statistical analyses. For the purpose, we adopt an appropriate evaluation model in terms of user-perceived quality through the applicable criteria and an evaluation method. The result of empirical study is described, which shows that the weight of each criterion is dynamic along usage levels. Briefly, functionality, usability, and reliability are key factors to contribute to the perceived quality. The empirical study also illustrates a comparative analysis on the dominant products, SAS and SPSS, in Korea.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.11
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• pp.997-1004
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• 2012

In enterprise software projects, performance issues have become more critical during recent decades. While developing software products, many performance tests are executed in the earlier development phase against the newly added code pieces to detect possible performance regressions. In our previous research, we introduced the framework to enable automated performance anomaly detection and reduce the analysis overhead for identifying the root causes, and showed Statistical Process Control (SPC) can be successfully applied to anomaly detection. In this paper, we explain the special performance trend in which the existing anomaly detection system can hardly detect the noticeable performance change especially when a performance regression is introduced and recovered again a while later. Within the fixed number of sampling period, the fluctuation gets aggravated and the lower and upper control limit get relaxed so that sometimes the existing system hardly detect the noticeable performance change. To resolve the issue, we apply dynamically tuned sampling window size based on the performance trend, and Fuzzy theory to find an appropriate size of the moving window.

• Journal of Information Technology Services
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• v.8 no.2
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• pp.1-22
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• 2009

Recently, improving service quality for customer satisfaction is one of the most important issues and the task for the growth of company. Furthermore, plenty studies are going on progress to develop service quality in IT industry. There have been so many researches of product quality on package software but yet the service quality of package software has been rarely studied before. Thus, the purpose of this study is to formulate a scheme on how to enhance the competitivity of package software company by analyzing the impacts of these two factors on the customer satisfaction, Word-of-Mouth intention and the reuse intention. The study models have been designed and the hypotheses have been made through the examination of the precedent literature about package software product and service quality. A questionnaire survey was performed to collect information, and the unit of analysis was a person who used package software. This study used the statistical technique such as regression analysis. This study may be utilized as basic data for building marketing strategies when package software companies offer service to customers.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.851-865
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• 2017

Ransomware such as WannaCry is a global issue and methods to defend against malware attacks are important. We have to be able to classify the malware types efficiently in order to minimize the damage from malwares. This study makes models to classify malware properly with various statistical techniques. Several classification techniques such as logistic regression, random forest, gradient boosting, and support vector machine are used to construct models. This study also helps us understand key variables to classify the type of malicious software.

• Journal of Korea Society of Industrial Information Systems
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• v.5 no.3
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• pp.18-29
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• 2000

This study presents a cost of efforts estimation model under the environment of developing a software using component software package tools. The approach taken was to drive from variety of sources in an attempt to identify the most significant factors. These sources ranged from already existing cost models like COTS integration cost and COCOMO models to information gathered in a data collection survey. Once the candidate drivers had been identified, the next step was to interview with the experts who had been experienced more than 5 years in component development area to identify the most significant driving factors. From those selected drivers, I established the Cost Estimation Model which is suitable for the developing a software using component software package tools by applying the general from of the well-know COCOMO software cost estimation model. To established the best fit in Korean Software industry, I used Regression statistical analysis with 31 data collections.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.65-78
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• 2023

Investigations on information security factors re- main elusive at small and medium enterprises (SMEs), es- specially for custom-made software solutions. This article aims to investigate, classify, adopt factors from recent literature addressing information security resources. SMEs al- ready have information security in place, but they are not easy to adopt through the negotiation processes between the in-house software development companies and custom-made software clients at SMEs. This article proposes a strategic framework for implementing the process of adoption of the information security factors at SMEs after conducting a systematic snapshot approach for investigating and classifying the resources. The systematic snapshot was conducted using a search strategy with inclusion and exclusion criteria to retain 128 final reviewed papers from a large number of papers within the period of 2001-2022. These papers were analyzed based on a classification schema including management, organizational, development, and environmental categories in software development lifecycle (SDLC) phases in order to define new security factors. The reviewed articles addressed research gaps, trends, and common covered evidence-based decisions based on the findings of the systematic mapping. Hence, this paper boosts the broader cooperation between in-house software development companies and their clients to elicit, customize, and adopt the factors based on clients' demands.

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.430-435
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• 2004

Nonhomogeneous Poisson Process is often used to model failure times which occurred in software reliability and hardware reliability models. It can be characterized by its intensity functions or mean value functions. Many parametric intensity models have been proposed to account for the failure mechanism in real situation. In this paper, we propose a Bayesian semiparametric approach based on beta-mixtures. Two real datasets are analyzed.