• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.249-259
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• 2022

Project management and deployment has gone through a long journey from traditional and agile to continuous integration, continuous deployment and continuous monitoring. Software industry benefited with the latest buzzword in the development process, DevOps that not only escalates software productivity but at the same time enhances software quality. But the implementation and assessment of DevOps practices is expository as there are no guidelines to assess and improvise DevOps application in software industries. Hence, there was a need to develop a hybrid model to assist software practitioners in DevOps implementation. The intention behind this paper is to implement the already proposed DevOps hybrid model using suggested tool chains including Jenkins, Selenium, GitLab, Ansible and Nagios automation tools through Jenkins project management environment and plugins. To achieve this implementation objective, a java application is developed with a web-based graphical interface. Further, in this paper, different challenges and benefits of Jenkins implementation shall also be outlined. The paper also presents the effectiveness of DevOps based Model implementation in software organizations. The impact of considering other automation tools and models can also be considered as a part of further research.

• Journal of Information Technology Services
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• v.9 no.4
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• pp.123-133
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• 2010

There are many occasions on which the critical decisions should be made in software projects. Those decisions are basically related to estimating and predicting project parameters such as costs, efforts, and duration. The project managers are looking for methods to make better decisions. The decisions about project parameters are recommended to be performed based on historical data of Similar projects. The measures of the tasks in past projects may have different shapes of distributions. we need to add those measures to get a predicted project measures. To add measures with different shapes of distribution, we need to use Monte Carlo Simulation. In this paper, we suggest applying Monte Carlo Simulation for supporting decision makings in software project. We implemented best-fit case and scheduling estimations with Cristal Ball, a commercial product of Monte Carlo simulation and showed how the suggested approach supports those critical decision makings.

• 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 KIISE:Software and Applications
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• v.35 no.4
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• pp.234-244
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• 2008

Since the advent of Six Sigma in 1980's, Six Sigma is widely used in various industry areas, such as manufacturing, financial, government, and service, and proves its innovation ability and value by providing lots of success stories. Several researches have been conducted to adopt Six Sigma for Software Development and Software Quality Assurance-Software Six Sigma. Although the wide use of Six Sigma, there is no software tool to support the execution of Six Sigma Project. For this reason, the Quantitative Six Sigma Project Management is required to support for measuring and analyzing Six Sigma Projects, storing and reporting the results from Six Sigma Projects, and managing Six Sigma Projects through the whole process of, DMAIC or DMADV. In this paper, we introduce the design and implementation of a Quantitative Six Sigma Project Management Framework and Tool. The execution of Six Sigma Project based on Six Sigma Project Management Tool benefits the quantification, the systematization, and the integration.

• Journal of Information Technology Services
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• v.5 no.2
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• pp.179-188
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• 2006

MDD/MDA which recently raising its head is technology that increase software development productivity through automatic transformation form higer abstract model into lower abstract model, or from model to code. This paper analyzes the effect on productivity by measuring Function Point per MM(man-month) in a software development project which performed in CBD methodology, and introduce the method of applying MDD/MDA technology in the project.

• Proceedings of the Safety Management and Science Conference
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• 2005.05a
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• pp.129-135
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• 2005

This paper proposes the interated and balanced project management system for software and IT by considering BSC, MBNQA, ISO 9001, Six Sigma, CMM and SPICE. This system can be extended to assess the various project management practices.

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1127-1136
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• 2003

Estimation of software project cost, effort and duration in the early stage of software development cycle is a difficult and key problem in software engineering. Most of models estimate the development effort using the function point that is measured from the requirement specification. This paper presents optimal team size and duration prediction based on function point in order to provide information that can be used as a guide in selecting the most Practical and productive team size for a software development project. We introduce to productive metrics and cost for decision criteria of ideal team size and duration. The experimental is based on the analysis of 300 development and enhancement software project data. These data sets are divide in two subgroups. One is a development project; the other is a maintenance project. As a result of evaluation by productivity and cost measured criteria in two subgroups, we come to the conclusion that the most successful projects has small teams and minimum duration. Also, I proposed that predictive model for team sire and duration according to function point size based on experimental results. The presented models gives a criteria for necessary team site and duration according to the software size.

• Knowledge Management Research
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• v.18 no.2
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• pp.85-102
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• 2017

With rapid development of information and communication technologies, open collaboration can be eased through the Internet. Open source software, as a representative area of open collaboration, is developed and adopted to various fields. In this research, based on organizational learning theory, we examine the impacts of exploration and exploitation on innovation performance in open source software development projects. We define knowledge exploration as a number of developers from outside organization and knowledge exploitation as the ratio of member of an organization who participated in an open source software project managed by the organization. For analysis, we collect data of 4794 projects from github which is a representative open source software development platform using Web crawler developed by Python. As a result, we find that excessive exploration has curvilinear (invers U-shape) relationship on project performance. On the other hand, exploitation with enough external developers will positively impact on project performance.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.25 no.9
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• pp.97-104
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• 2007

• Journal of Information Technology Services
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• v.13 no.2
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• pp.195-217
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• 2014

This paper has explored when implementing SW development project of the IT service corporations, what factors affect its productivity in SW development methodology. The importance of the AHP analysis surveyed from the experts in IT service companies and related committee, was shown in the order of the following processes : 1) Deployment process 2) Management process 3) Establishment process. It is measured the methodology levels of establishment, deployment and management in each project using the survey results collected from project execution members and analyzed the productivity of projects that have been executed within 2 years. Using project methodology level, productivity correlation analysis, and regression analysis, this study confirms that the methodology deployment level brings positive effects significantly to SW development productivity. The significance of this study would be not only to research and analyze SW development productivity using the real project execution data but also to underline the necessities and the importance of steady research, deployment and support for SW development productivity improvement.